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authorMitja Felicijan <mitja.felicijan@gmail.com>2026-02-12 20:57:17 +0100
committerMitja Felicijan <mitja.felicijan@gmail.com>2026-02-12 20:57:17 +0100
commitb333b06772c89d96aacb5490d6a219fba7c09cc6 (patch)
tree211df60083a5946baa2ed61d33d8121b7e251b06 /llama.cpp/ggml/src/ggml-cpu/llamafile/sgemm.cpp
downloadllmnpc-b333b06772c89d96aacb5490d6a219fba7c09cc6.tar.gz
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diff --git a/llama.cpp/ggml/src/ggml-cpu/llamafile/sgemm.cpp b/llama.cpp/ggml/src/ggml-cpu/llamafile/sgemm.cpp
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@@ -0,0 +1,3681 @@
+// Copyright 2024 Mozilla Foundation
+//
+// Permission is hereby granted, free of charge, to any person obtaining
+// a copy of this software and associated documentation files (the
+// "Software"), to deal in the Software without restriction, including
+// without limitation the rights to use, copy, modify, merge, publish,
+// distribute, sublicense, and/or sell copies of the Software, and to
+// permit persons to whom the Software is furnished to do so, subject to
+// the following conditions:
+//
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+//
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+// MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS
+// BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
+// ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
+// CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+// SOFTWARE.
+
+//
+// _ _ ___ _ _ ___
+// | |_(_)_ _ _ _| _ ) | /_\ / __|
+// | _| | ' \ || | _ \ |__ / _ \\__ \.
+// \__|_|_||_\_, |___/____/_/ \_\___/
+// |__/
+//
+// BASIC LINEAR ALGEBRA SUBPROGRAMS
+//
+//
+// This file implements multithreaded CPU matrix multiplication for the
+// common contiguous use case C = Aᵀ * B. These kernels are designed to
+// have excellent performance[1] for matrices that fit in the CPU cache
+// without imposing any overhead such as cache filling or malloc calls.
+//
+// This implementation does not guarantee any upper bound with rounding
+// errors, which grow along with k. Our goal's to maximally exploit the
+// hardware for performance, and then use whatever resources remain for
+// improving numerical accuracy.
+//
+// [1] J. Tunney, ‘LLaMA Now Goes Faster on CPUs’, Mar. 2024. [Online].
+// Available: https://justine.lol/matmul/. [Accessed: 29-Mar-2024].
+
+#if defined(__GNUC__)
+#pragma GCC diagnostic ignored "-Wpedantic"
+#pragma GCC diagnostic ignored "-Wignored-attributes"
+#endif
+
+#include "sgemm.h"
+#include "ggml-impl.h"
+#include "ggml-cpu-impl.h"
+#include "ggml-quants.h"
+#include "simd-mappings.h"
+
+#include <array>
+#include <type_traits>
+
+#ifdef _MSC_VER
+#define NOINLINE __declspec(noinline)
+#else
+#define NOINLINE __attribute__((__noinline__))
+#endif
+
+#if defined(__ARM_NEON) || defined(__AVX512F__) || defined(__VXE__) || defined(__VXE2__)
+#define VECTOR_REGISTERS 32
+#else
+#define VECTOR_REGISTERS 16
+#endif
+
+#if defined(__riscv_v_intrinsic)
+#define LMUL 4
+#endif
+
+#define MM256_SET_M128I(a, b) _mm256_insertf128_si256(_mm256_castsi128_si256(b), (a), 1)
+
+namespace {
+
+inline float unhalf(ggml_fp16_t d) {
+ return GGML_CPU_FP16_TO_FP32(d);
+}
+
+////////////////////////////////////////////////////////////////////////////////////////////////////
+// VECTORIZED ARITHMETIC OPERATIONS
+
+#if defined(__SSE__) || defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
+inline __m128 add(__m128 x, __m128 y) { return _mm_add_ps(x, y); }
+inline __m128 sub(__m128 x, __m128 y) { return _mm_sub_ps(x, y); }
+inline __m128 mul(__m128 x, __m128 y) { return _mm_mul_ps(x, y); }
+#endif // __SSE__
+
+#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
+inline __m256 add(__m256 x, __m256 y) { return _mm256_add_ps(x, y); }
+inline __m256 sub(__m256 x, __m256 y) { return _mm256_sub_ps(x, y); }
+inline __m256 mul(__m256 x, __m256 y) { return _mm256_mul_ps(x, y); }
+#endif // __AVX__
+
+#if defined(__AVX512F__)
+inline __m512 add(__m512 x, __m512 y) { return _mm512_add_ps(x, y); }
+inline __m512 sub(__m512 x, __m512 y) { return _mm512_sub_ps(x, y); }
+inline __m512 mul(__m512 x, __m512 y) { return _mm512_mul_ps(x, y); }
+#endif // __AVX512F__
+
+#if defined(__ARM_NEON)
+inline float32x4_t add(float32x4_t x, float32x4_t y) { return vaddq_f32(x, y); }
+inline float32x4_t sub(float32x4_t x, float32x4_t y) { return vsubq_f32(x, y); }
+inline float32x4_t mul(float32x4_t x, float32x4_t y) { return vmulq_f32(x, y); }
+#endif // __ARM_NEON
+
+#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
+inline float16x8_t add(float16x8_t x, float16x8_t y) { return vaddq_f16(x, y); }
+inline float16x8_t sub(float16x8_t x, float16x8_t y) { return vsubq_f16(x, y); }
+inline float16x8_t mul(float16x8_t x, float16x8_t y) { return vmulq_f16(x, y); }
+#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+
+#if defined(__VXE__) || defined(__VXE2__)
+inline float32x4_t add(float32x4_t x, float32x4_t y) { return vec_add(x, y); }
+inline float32x4_t sub(float32x4_t x, float32x4_t y) { return vec_sub(x, y); }
+inline float32x4_t mul(float32x4_t x, float32x4_t y) { return vec_mul(x, y); }
+#endif
+
+#if defined(__MMA__)
+#include "sgemm-ppc.h"
+#endif
+////////////////////////////////////////////////////////////////////////////////////////////////////
+// VECTORIZED FUSED MULTIPLY ADD
+
+/**
+ * Computes a * b + c.
+ */
+template <typename T, typename U>
+inline U madd(T a, T b, U c) {
+ return add(mul(a, b), c);
+}
+
+#if defined(__FMA__)
+#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
+template <>
+inline __m256 madd(__m256 a, __m256 b, __m256 c) {
+ return _mm256_fmadd_ps(a, b, c);
+}
+#endif
+#if defined(__AVX512F__)
+template <>
+inline __m512 madd(__m512 a, __m512 b, __m512 c) {
+ return _mm512_fmadd_ps(a, b, c);
+}
+#endif
+#if defined(__AVX512BF16__)
+template <>
+inline __m512 madd(__m512bh a, __m512bh b, __m512 c) {
+ return _mm512_dpbf16_ps(c, a, b);
+}
+template <>
+inline __m256 madd(__m256bh a, __m256bh b, __m256 c) {
+ return _mm256_dpbf16_ps(c, a, b);
+}
+#endif
+#endif
+
+#if defined(__ARM_FEATURE_FMA)
+template <>
+inline float32x4_t madd(float32x4_t a, float32x4_t b, float32x4_t c) {
+ return vfmaq_f32(c, b, a);
+}
+#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && !defined(_MSC_VER)
+template <>
+inline float16x8_t madd(float16x8_t a, float16x8_t b, float16x8_t c) {
+ return vfmaq_f16(c, b, a);
+}
+#endif
+#endif
+
+#if defined(__VXE__) || defined(__VXE2__)
+template <>
+inline float32x4_t madd(float32x4_t a, float32x4_t b, float32x4_t c) {
+ return vec_madd(a, b, c);
+}
+#endif
+
+#if defined(__riscv_zvfh)
+template <>
+inline vfloat32m1_t madd(vfloat16mf2_t a, vfloat16mf2_t b, vfloat32m1_t c) {
+ return __riscv_vfwmacc_vv_f32m1(c, a, b, __riscv_vsetvlmax_e32m1());
+}
+inline vfloat32m2_t madd(vfloat16m1_t a, vfloat16m1_t b, vfloat32m2_t c) {
+ return __riscv_vfwmacc_vv_f32m2(c, a, b, __riscv_vsetvlmax_e32m2());
+}
+inline vfloat32m4_t madd(vfloat16m2_t a, vfloat16m2_t b, vfloat32m4_t c) {
+ return __riscv_vfwmacc_vv_f32m4(c, a, b, __riscv_vsetvlmax_e32m4());
+}
+inline vfloat32m8_t madd(vfloat16m4_t a, vfloat16m4_t b, vfloat32m8_t c) {
+ return __riscv_vfwmacc_vv_f32m8(c, a, b, __riscv_vsetvlmax_e32m8());
+}
+inline vfloat32m1_t madd(vfloat32m1_t a, vfloat32m1_t b, vfloat32m1_t c) {
+ return __riscv_vfmacc_vv_f32m1(c, a, b, __riscv_vsetvlmax_e32m1());
+}
+inline vfloat32m2_t madd(vfloat32m2_t a, vfloat32m2_t b, vfloat32m2_t c) {
+ return __riscv_vfmacc_vv_f32m2(c, a, b, __riscv_vsetvlmax_e32m2());
+}
+inline vfloat32m4_t madd(vfloat32m4_t a, vfloat32m4_t b, vfloat32m4_t c) {
+ return __riscv_vfmacc_vv_f32m4(c, a, b, __riscv_vsetvlmax_e32m4());
+}
+inline vfloat32m8_t madd(vfloat32m8_t a, vfloat32m8_t b, vfloat32m8_t c) {
+ return __riscv_vfmacc_vv_f32m8(c, a, b, __riscv_vsetvlmax_e32m8());
+}
+#endif
+
+#if defined(__riscv_zvfbfwma)
+inline vfloat32m1_t madd(vbfloat16mf2_t a, vbfloat16mf2_t b, vfloat32m1_t c) {
+ return __riscv_vfwmaccbf16_vv_f32m1(c, a, b, __riscv_vsetvlmax_e32m1());
+}
+inline vfloat32m2_t madd(vbfloat16m1_t a, vbfloat16m1_t b, vfloat32m2_t c) {
+ return __riscv_vfwmaccbf16_vv_f32m2(c, a, b, __riscv_vsetvlmax_e32m2());
+}
+inline vfloat32m4_t madd(vbfloat16m2_t a, vbfloat16m2_t b, vfloat32m4_t c) {
+ return __riscv_vfwmaccbf16_vv_f32m4(c, a, b, __riscv_vsetvlmax_e32m4());
+}
+#endif
+
+////////////////////////////////////////////////////////////////////////////////////////////////////
+// VECTORIZED HORIZONTAL SUM
+
+#if defined(__ARM_NEON)
+inline float hsum(float32x4_t x) {
+ return vaddvq_f32(x);
+}
+#endif // __ARM_NEON
+
+#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && !defined(_MSC_VER)
+inline float hsum(float16x8_t x) {
+ return vaddvq_f32(vaddq_f32(vcvt_f32_f16(vget_low_f16(x)),
+ vcvt_f32_f16(vget_high_f16(x))));
+}
+#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+
+#if defined(__VXE__) || defined(__VXE2__)
+inline float hsum(float32x4_t x) {
+ float32x4_t tmp = x + vec_reve(x);
+ return tmp[0] + tmp[1];
+}
+#endif
+
+#if defined(__SSE__) || defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
+inline float hsum(__m128 x) {
+#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
+ x = _mm_add_ps(x, _mm_movehl_ps(x, x));
+ x = _mm_add_ss(x, _mm_movehdup_ps(x));
+#else
+ __m128 t;
+ t = _mm_shuffle_ps(x, x, _MM_SHUFFLE(2, 3, 0, 1));
+ x = _mm_add_ps(x, t);
+ t = _mm_movehl_ps(t, x);
+ x = _mm_add_ss(x, t);
+#endif
+ return _mm_cvtss_f32(x);
+}
+#endif
+
+#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
+inline float hsum(__m256 x) {
+ return hsum(_mm_add_ps(_mm256_extractf128_ps(x, 1),
+ _mm256_castps256_ps128(x)));
+}
+#endif // __AVX__
+
+#if defined(__AVX512F__)
+inline float hsum(__m512 x) {
+ return _mm512_reduce_add_ps(x);
+}
+#endif // __AVX512F__
+
+#if defined(__riscv_zvfh)
+inline float hsum(vfloat32m1_t x) {
+ return __riscv_vfmv_f_s_f32m1_f32(
+ __riscv_vfredusum_vs_f32m1_f32m1(x, __riscv_vfmv_v_f_f32m1(0, 1), __riscv_vsetvlmax_e32m1()));
+}
+inline float hsum(vfloat32m2_t x) {
+ return __riscv_vfmv_f_s_f32m1_f32(
+ __riscv_vfredusum_vs_f32m2_f32m1(x, __riscv_vfmv_v_f_f32m1(0, 1), __riscv_vsetvlmax_e32m2()));
+}
+inline float hsum(vfloat32m4_t x) {
+ return __riscv_vfmv_f_s_f32m1_f32(
+ __riscv_vfredusum_vs_f32m4_f32m1(x, __riscv_vfmv_v_f_f32m1(0, 1), __riscv_vsetvlmax_e32m4()));
+}
+inline float hsum(vfloat32m8_t x) {
+ return __riscv_vfmv_f_s_f32m1_f32(
+ __riscv_vfredusum_vs_f32m8_f32m1(x, __riscv_vfmv_v_f_f32m1(0, 1), __riscv_vsetvlmax_e32m8()));
+}
+#endif
+
+////////////////////////////////////////////////////////////////////////////////////////////////////
+// VECTORIZED MEMORY LOADING
+
+template <typename T, typename U> T load(const U *);
+
+#if defined(__ARM_NEON)
+template <> inline float32x4_t load(const float *p) {
+ return vld1q_f32(p);
+}
+#if !defined(_MSC_VER)
+// FIXME: this should check for __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
+template <> inline float16x8_t load(const ggml_fp16_t *p) {
+ return vld1q_f16((const float16_t *)p);
+}
+template <> inline float32x4_t load(const ggml_fp16_t *p) {
+ return vcvt_f32_f16(vld1_f16((const float16_t *)p));
+}
+#endif // _MSC_VER
+#endif // __ARM_NEON
+
+#if defined(__VXE__) || defined(__VXE2__)
+template <> inline float32x4_t load(const ggml_fp16_t * p) {
+ float tmp[4];
+
+ for (int i = 0; i < 4; i++) {
+ tmp[i] = GGML_CPU_FP16_TO_FP32(p[i]);
+ }
+
+ return vec_xl(0, (const float *)(tmp));
+}
+template <> inline float32x4_t load(const float * p) {
+ return vec_xl(0, p);
+}
+#endif
+
+#if defined(__SSE__) || defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
+template <> inline __m128 load(const float *p) {
+ return _mm_loadu_ps(p);
+}
+#endif // __SSE__
+
+#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
+template <> inline __m256 load(const float *p) {
+ return _mm256_loadu_ps(p);
+}
+#endif // __AVX__
+
+#if defined(__AVX2__) || defined(__AVX512F__)
+template <> inline __m256 load(const ggml_bf16_t *p) {
+ return _mm256_castsi256_ps(
+ _mm256_slli_epi32(_mm256_cvtepu16_epi32(_mm_loadu_si128((const __m128i *)p)), 16));
+}
+#endif // __AVX2__
+
+#if defined(__F16C__)
+template <> inline __m256 load(const ggml_fp16_t *p) {
+ return _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)p));
+}
+#endif // __F16C__
+
+#if defined(__AVX512F__)
+template <> inline __m512 load(const float *p) {
+ return _mm512_loadu_ps(p);
+}
+template <> inline __m512 load(const ggml_fp16_t *p) {
+ return _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)p));
+}
+template <> inline __m512 load(const ggml_bf16_t *p) {
+ return _mm512_castsi512_ps(
+ _mm512_slli_epi32(_mm512_cvtepu16_epi32(_mm256_loadu_si256((const __m256i *)p)), 16));
+}
+#endif // __AVX512F__
+
+#if defined(__AVX512BF16__)
+template <> inline __m512bh load(const ggml_bf16_t *p) {
+ return (__m512bh)_mm512_loadu_ps((const float *)p);
+}
+template <> inline __m256bh load(const ggml_bf16_t *p) {
+ return (__m256bh)_mm256_loadu_ps((const float *)p);
+}
+template <> inline __m512bh load(const float *p) {
+ return _mm512_cvtne2ps_pbh(_mm512_loadu_ps(p + 16), _mm512_loadu_ps(p));
+}
+template <> inline __m256bh load(const float *p) {
+ return _mm512_cvtneps_pbh(_mm512_loadu_ps(p));
+}
+#endif
+
+#if defined(__riscv_zvfh)
+template <> inline vfloat16mf2_t load(const ggml_fp16_t *p) {
+ return __riscv_vle16_v_f16mf2(reinterpret_cast<const _Float16 *>(p), __riscv_vsetvlmax_e16mf2());
+}
+template <> inline vfloat16m1_t load(const ggml_fp16_t *p) {
+ return __riscv_vle16_v_f16m1(reinterpret_cast<const _Float16 *>(p), __riscv_vsetvlmax_e16m1());
+}
+template <> inline vfloat16m2_t load(const ggml_fp16_t *p) {
+ return __riscv_vle16_v_f16m2(reinterpret_cast<const _Float16 *>(p), __riscv_vsetvlmax_e16m2());
+}
+template <> inline vfloat16m4_t load(const ggml_fp16_t *p) {
+ return __riscv_vle16_v_f16m4(reinterpret_cast<const _Float16 *>(p), __riscv_vsetvlmax_e16m4());
+}
+template <> inline vfloat32m1_t load(const float *p) {
+ return __riscv_vle32_v_f32m1(p, __riscv_vsetvlmax_e32m1());
+}
+template <> inline vfloat32m2_t load(const float *p) {
+ return __riscv_vle32_v_f32m2(p, __riscv_vsetvlmax_e32m2());
+}
+template <> inline vfloat32m4_t load(const float *p) {
+ return __riscv_vle32_v_f32m4(p, __riscv_vsetvlmax_e32m4());
+}
+template <> inline vfloat32m8_t load(const float *p) {
+ return __riscv_vle32_v_f32m8(p, __riscv_vsetvlmax_e32m8());
+}
+#endif
+
+#if defined(__riscv_zvfbfwma)
+template <> inline vbfloat16mf2_t load(const ggml_bf16_t *p) {
+ return __riscv_vle16_v_bf16mf2(reinterpret_cast<const __bf16*>(p), __riscv_vsetvlmax_e16mf2());
+}
+template <> inline vbfloat16m1_t load(const ggml_bf16_t *p) {
+ return __riscv_vle16_v_bf16m1(reinterpret_cast<const __bf16*>(p), __riscv_vsetvlmax_e16m1());
+}
+template <> inline vbfloat16m2_t load(const ggml_bf16_t *p) {
+ return __riscv_vle16_v_bf16m2(reinterpret_cast<const __bf16*>(p), __riscv_vsetvlmax_e16m2());
+}
+#endif
+
+#if defined(__riscv_zvfh)
+template <typename T> T set_zero();
+
+template <> inline vfloat16mf2_t set_zero() {
+ return __riscv_vfmv_v_f_f16mf2(0, __riscv_vsetvlmax_e16mf2());
+}
+template <> inline vfloat16m1_t set_zero() {
+ return __riscv_vfmv_v_f_f16m1(0, __riscv_vsetvlmax_e16m1());
+}
+template <> inline vfloat16m2_t set_zero() {
+ return __riscv_vfmv_v_f_f16m2(0, __riscv_vsetvlmax_e16m2());
+}
+template <> inline vfloat16m4_t set_zero() {
+ return __riscv_vfmv_v_f_f16m4(0, __riscv_vsetvlmax_e16m4());
+}
+template <> inline vfloat32m1_t set_zero() {
+ return __riscv_vfmv_v_f_f32m1(0.0f, __riscv_vsetvlmax_e32m1());
+}
+template <> inline vfloat32m2_t set_zero() {
+ return __riscv_vfmv_v_f_f32m2(0, __riscv_vsetvlmax_e32m2());
+}
+template <> inline vfloat32m4_t set_zero() {
+ return __riscv_vfmv_v_f_f32m4(0, __riscv_vsetvlmax_e32m4());
+}
+template <> inline vfloat32m8_t set_zero() {
+ return __riscv_vfmv_v_f_f32m8(0, __riscv_vsetvlmax_e32m8());
+}
+#endif
+
+#if defined(__riscv_v_intrinsic)
+template <typename T> size_t vlmax() {
+ if constexpr (std::is_same_v<T, vfloat16mf2_t>) { return __riscv_vsetvlmax_e16mf2(); }
+ else if constexpr (std::is_same_v<T, vfloat16m1_t>) { return __riscv_vsetvlmax_e16m1(); }
+ else if constexpr (std::is_same_v<T, vfloat16m2_t>) { return __riscv_vsetvlmax_e16m2(); }
+ else if constexpr (std::is_same_v<T, vfloat16m4_t>) { return __riscv_vsetvlmax_e16m4(); }
+ else if constexpr (std::is_same_v<T, vfloat32m1_t>) { return __riscv_vsetvlmax_e32m1(); }
+ else if constexpr (std::is_same_v<T, vfloat32m2_t>) { return __riscv_vsetvlmax_e32m2(); }
+ else if constexpr (std::is_same_v<T, vfloat32m4_t>) { return __riscv_vsetvlmax_e32m4(); }
+ else if constexpr (std::is_same_v<T, vfloat32m8_t>) { return __riscv_vsetvlmax_e32m8(); }
+ return 0;
+}
+#endif
+
+////////////////////////////////////////////////////////////////////////////////////////////////////
+// FLOATING POINT MATRIX MULTIPLICATION
+
+template <int M>
+static inline int64_t BLOCK_SIZE(size_t m) {
+ const int64_t NB_BLOC_M = (m + M - 1) / M;
+ return (m % NB_BLOC_M == 0) ? m / NB_BLOC_M : (m / NB_BLOC_M) + 1;
+}
+
+static constexpr inline int64_t BLOC_POS(int64_t ib, int64_t ibN, int64_t bloc_size) {
+ return ib < ibN ? ib * bloc_size : ibN * bloc_size + (ib - ibN) * (bloc_size - 1);
+}
+
+template <int KN, typename D, typename V, typename TA, typename TB, typename TC>
+class tinyBLAS {
+ public:
+ tinyBLAS(const ggml_compute_params * params, int64_t k,
+ const TA *A, int64_t lda,
+ const TB *B, int64_t ldb,
+ TC *C, int64_t ldc)
+ : params(params), A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc) {
+ }
+
+ bool matmul(int64_t m, int64_t n) {
+ if (k % KN != 0)
+ return false;
+ // compute RM for only need tile with size RM&RM-1
+#if VECTOR_REGISTERS == 32
+ if (m % 16 == 0 && (m/16 >= params->nth)) {
+ const int64_t SIZE_N = BLOCK_SIZE<6>(n);
+ mnpack<4, 6, 4>(m, n, SIZE_N, 12);
+ return true;
+ }
+ if (m % 8 == 0 ) {
+ const int64_t SIZE_N = BLOCK_SIZE<6>(n);
+ mnpack<4, 6, 2>(m, n, SIZE_N, 12);
+ return true;
+ }
+ if (m % 4 == 0) {
+ const int64_t SIZE_N = BLOCK_SIZE<6>(n);
+ mnpack<4, 6, 1>(m, n, SIZE_N, 12);
+ return true;
+ }
+#else // VECTOR_REGISTERS == 16
+ if (m % 16 == 0 && (m/16 >= params->nth)) {
+ const int64_t SIZE_N = BLOCK_SIZE<3>(n);
+ mnpack<4, 3, 4>(m, n, SIZE_N, 24);
+ return true;
+ }
+ if (m % 8 == 0 ) {
+ const int64_t SIZE_N = BLOCK_SIZE<3>(n);
+ mnpack<4, 3, 2>(m, n, SIZE_N, 24);
+ return true;
+ }
+ if (m % 4 == 0) {
+ const int64_t SIZE_N = BLOCK_SIZE<3>(n);
+ mnpack<4, 3, 1>(m, n, SIZE_N, 24);
+ return true;
+ }
+#endif
+ return false;
+ }
+
+ private:
+ template <int RM, int RN, int BM>
+ inline void mnpack(int64_t m, int64_t n, int64_t SIZE_N, int64_t BN) {
+ if (SIZE_N == RN) {
+ return gemm<RM, RN, BM>(m, n, BN);
+ }
+ if constexpr (RN > 1) {
+ return mnpack<RM, RN-1, BM>(m, n, SIZE_N, BN);
+ } else {
+ GGML_LOG_ERROR("mnpack<%d, %d> bloc size not supported\n", RM, (int)SIZE_N);
+ GGML_ASSERT(false); // we have miss something.
+ }
+ }
+
+ template <int RM, int RN>
+ inline void gemm_bloc(int64_t ii, int64_t jj) {
+ D Cv[RN][RM] = {};
+ for (int64_t l = 0; l < k; l += KN) {
+ // help compiler for op order.
+ if constexpr (RM <= RN) {
+ V Av[RM];
+ for (int64_t i = 0; i < RM; ++i) {
+ Av[i] = load<V>(A + lda * (ii + i) + l);
+ }
+ for (int64_t j = 0; j < RN; ++j) {
+ V Bv = load<V>(B + ldb * (jj + j) + l);
+ for (int64_t i = 0; i < RM; ++i) {
+ Cv[j][i] = madd(Av[i], Bv, Cv[j][i]);
+ }
+ }
+ } else {
+ V Bv[RN];
+ for (int64_t j = 0; j < RN; ++j) {
+ Bv[j] = load<V>(B + ldb * (jj + j) + l);
+ }
+ for (int64_t i = 0; i < RM; ++i) {
+ V Av = load<V>(A + lda * (ii + i) + l);
+ for (int64_t j = 0; j < RN; ++j) {
+ Cv[j][i] = madd(Av, Bv[j], Cv[j][i]);
+ }
+ }
+ }
+ }
+ for (int64_t j = 0; j < RN; ++j)
+ for (int64_t i = 0; i < RM; ++i)
+ C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
+ }
+
+ template <int RM, int RN, int BM>
+ NOINLINE void gemm(int64_t m, int64_t n, int64_t BN) {
+ GGML_ASSERT(m % (RM * BM) == 0);
+ const int64_t ytiles = m / (RM * BM);
+ const int64_t xtiles = (n + RN -1) / RN;
+ const int64_t jj_RN = (xtiles - (xtiles * RN - n));
+
+ // "round" bloc_size to "nearest" BN
+ const int64_t NB_BN = xtiles < BN ? 1 : (xtiles + BN / 2) / BN;
+ const int64_t SIZE_BN = xtiles % NB_BN == 0 ? xtiles / NB_BN : xtiles / NB_BN + 1;
+ const int64_t jj_BN = (NB_BN - (NB_BN * SIZE_BN - xtiles));
+ const int64_t nb_job = ytiles * NB_BN;
+
+ if (params->ith == 0) {
+ GGML_ASSERT( jj_BN * SIZE_BN + (NB_BN - jj_BN) * (SIZE_BN - 1) == xtiles);
+ // Every thread starts at ith, so the first unprocessed chunk is nth. This save a bit of coordination right at the start.
+ ggml_threadpool_chunk_set(params->threadpool, params->nth);
+ }
+
+ ggml_barrier(params->threadpool);
+
+ int64_t job = params->ith;
+ while (job < nb_job) {
+ const int64_t ii = (job % ytiles) * RM * BM;
+ const int64_t jb = job / ytiles;
+ const int64_t jr0 = BLOC_POS(jb , jj_BN, SIZE_BN);
+ const int64_t jrN = BLOC_POS(jb+1, jj_BN, SIZE_BN);
+
+ const int64_t jj0 = BLOC_POS(jr0, jj_RN, RN);
+ const int64_t jj2 = BLOC_POS(jrN, jj_RN, RN);
+ const int64_t jj1 = jj2 < jj_RN * RN ? jj2 : jj_RN * RN;
+
+ for (int64_t bi = 0; bi < BM * RM; bi += RM) {
+ int64_t jj = jj0;
+ for (; jj < jj1; jj += RN) {
+ gemm_bloc<RM, RN>(ii + bi, jj);
+ }
+ if constexpr (RN > 1) {
+ for (; jj < jj2; jj += RN - 1) {
+ gemm_bloc<RM, RN-1>(ii + bi, jj);
+ }
+ }
+ GGML_ASSERT(jj == jj2);
+ }
+
+ job = ggml_threadpool_chunk_add(params->threadpool, 1);
+ }
+
+ ggml_barrier(params->threadpool);
+ return;
+ }
+
+ const ggml_compute_params * params;
+ const TA *const A;
+ const TB *const B;
+ TC *const C;
+ const int64_t k;
+ const int64_t lda;
+ const int64_t ldb;
+ const int64_t ldc;
+};
+
+#if defined(__riscv_v_intrinsic)
+template <typename D, typename V, typename TA, typename TB, typename TC>
+class tinyBLAS_RVV {
+ public:
+ tinyBLAS_RVV(const ggml_compute_params * params, int64_t k,
+ const TA *A, int64_t lda,
+ const TB *B, int64_t ldb,
+ TC *C, int64_t ldc)
+ : params(params), A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc) {
+ }
+
+ bool matmul(int64_t m, int64_t n) {
+ if (k % vlmax<V>() != 0) {
+ return false;
+ }
+
+#if LMUL == 1
+ if (m % 16 == 0 && (m/16 >= params->nth)) {
+ const int64_t SIZE_N = BLOCK_SIZE<6>(n);
+ mnpack<4, 6, 4>(m, n, SIZE_N, 12);
+ return true;
+ }
+ if (m % 8 == 0 ) {
+ const int64_t SIZE_N = BLOCK_SIZE<6>(n);
+ mnpack<4, 6, 2>(m, n, SIZE_N, 12);
+ return true;
+ }
+ if (m % 4 == 0) {
+ const int64_t SIZE_N = BLOCK_SIZE<6>(n);
+ mnpack<4, 6, 1>(m, n, SIZE_N, 12);
+ return true;
+ }
+#elif LMUL == 2
+ if (m % 16 == 0 && (m/16 >= params->nth)) {
+ const int64_t SIZE_N = BLOCK_SIZE<3>(n);
+ mnpack<4, 3, 4>(m, n, SIZE_N, 24);
+ return true;
+ }
+ if (m % 8 == 0 ) {
+ const int64_t SIZE_N = BLOCK_SIZE<3>(n);
+ mnpack<4, 3, 2>(m, n, SIZE_N, 24);
+ return true;
+ }
+ if (m % 4 == 0) {
+ const int64_t SIZE_N = BLOCK_SIZE<3>(n);
+ mnpack<4, 3, 1>(m, n, SIZE_N, 24);
+ return true;
+ }
+#else // LMUL = 4
+ if (m % 16 == 0 && (m/16 >= params->nth)) {
+ const int64_t SIZE_N = BLOCK_SIZE<2>(n);
+ mnpack<2, 2, 8>(m, n, SIZE_N, 36);
+ return true;
+ }
+ if (m % 8 == 0 ) {
+ const int64_t SIZE_N = BLOCK_SIZE<2>(n);
+ mnpack<2, 2, 4>(m, n, SIZE_N, 36);
+ return true;
+ }
+ if (m % 4 == 0) {
+ const int64_t SIZE_N = BLOCK_SIZE<2>(n);
+ mnpack<2, 2, 2>(m, n, SIZE_N, 36);
+ return true;
+ }
+#endif
+ return false;
+ }
+
+ private:
+ template<int RM, int RN, int BM>
+ inline void mnpack(int64_t m, int64_t n, int64_t SIZE_N, int64_t BN) {
+ if (SIZE_N == RN) {
+ return gemm<RM, RN, BM>(m, n, BN);
+ }
+ if constexpr (RN > 1) {
+ return mnpack<RM, RN-1, BM>(m, n, SIZE_N, BN);
+ } else {
+ GGML_LOG_ERROR("mnpack<%d, %d> bloc size not supported\n", RM, (int)SIZE_N);
+ GGML_ASSERT(false); // we have miss something.
+ }
+ }
+
+ inline void gemm_bloc_4x6(int64_t ii, int64_t jj) {
+ size_t vl = vlmax<V>();
+ D Cv00 = set_zero<D>();
+ D Cv01 = set_zero<D>();
+ D Cv02 = set_zero<D>();
+ D Cv03 = set_zero<D>();
+ D Cv10 = set_zero<D>();
+ D Cv11 = set_zero<D>();
+ D Cv12 = set_zero<D>();
+ D Cv13 = set_zero<D>();
+ D Cv20 = set_zero<D>();
+ D Cv21 = set_zero<D>();
+ D Cv22 = set_zero<D>();
+ D Cv23 = set_zero<D>();
+ D Cv30 = set_zero<D>();
+ D Cv31 = set_zero<D>();
+ D Cv32 = set_zero<D>();
+ D Cv33 = set_zero<D>();
+ D Cv40 = set_zero<D>();
+ D Cv41 = set_zero<D>();
+ D Cv42 = set_zero<D>();
+ D Cv43 = set_zero<D>();
+ D Cv50 = set_zero<D>();
+ D Cv51 = set_zero<D>();
+ D Cv52 = set_zero<D>();
+ D Cv53 = set_zero<D>();
+
+ for (int64_t l = 0; l < k; l += vl) {
+ V Bv0 = load<V>(B + ldb * (jj + 0) + l);
+ V Bv1 = load<V>(B + ldb * (jj + 1) + l);
+ V Bv2 = load<V>(B + ldb * (jj + 2) + l);
+ V Bv3 = load<V>(B + ldb * (jj + 3) + l);
+ V Bv4 = load<V>(B + ldb * (jj + 4) + l);
+ V Bv5 = load<V>(B + ldb * (jj + 5) + l);
+
+ V Av0 = load<V>(A + lda * (ii + 0) + l);
+ Cv00 = madd(Av0, Bv0, Cv00);
+ Cv10 = madd(Av0, Bv1, Cv10);
+ Cv20 = madd(Av0, Bv2, Cv20);
+ Cv30 = madd(Av0, Bv3, Cv30);
+ Cv40 = madd(Av0, Bv4, Cv40);
+ Cv50 = madd(Av0, Bv5, Cv50);
+
+ V Av1 = load<V>(A + lda * (ii + 1) + l);
+ Cv01 = madd(Av1, Bv0, Cv01);
+ Cv11 = madd(Av1, Bv1, Cv11);
+ Cv21 = madd(Av1, Bv2, Cv21);
+ Cv31 = madd(Av1, Bv3, Cv31);
+ Cv41 = madd(Av1, Bv4, Cv41);
+ Cv51 = madd(Av1, Bv5, Cv51);
+
+ V Av2 = load<V>(A + lda * (ii + 2) + l);
+ Cv02 = madd(Av2, Bv0, Cv02);
+ Cv12 = madd(Av2, Bv1, Cv12);
+ Cv22 = madd(Av2, Bv2, Cv22);
+ Cv32 = madd(Av2, Bv3, Cv32);
+ Cv42 = madd(Av2, Bv4, Cv42);
+ Cv52 = madd(Av2, Bv5, Cv52);
+
+ V Av3 = load<V>(A + lda * (ii + 3) + l);
+ Cv03 = madd(Av3, Bv0, Cv03);
+ Cv13 = madd(Av3, Bv1, Cv13);
+ Cv23 = madd(Av3, Bv2, Cv23);
+ Cv33 = madd(Av3, Bv3, Cv33);
+ Cv43 = madd(Av3, Bv4, Cv43);
+ Cv53 = madd(Av3, Bv5, Cv53);
+ }
+
+ C[ldc * (jj + 0) + (ii + 0)] = hsum(Cv00);
+ C[ldc * (jj + 0) + (ii + 1)] = hsum(Cv01);
+ C[ldc * (jj + 0) + (ii + 2)] = hsum(Cv02);
+ C[ldc * (jj + 0) + (ii + 3)] = hsum(Cv03);
+ C[ldc * (jj + 1) + (ii + 0)] = hsum(Cv10);
+ C[ldc * (jj + 1) + (ii + 1)] = hsum(Cv11);
+ C[ldc * (jj + 1) + (ii + 2)] = hsum(Cv12);
+ C[ldc * (jj + 1) + (ii + 3)] = hsum(Cv13);
+ C[ldc * (jj + 2) + (ii + 0)] = hsum(Cv20);
+ C[ldc * (jj + 2) + (ii + 1)] = hsum(Cv21);
+ C[ldc * (jj + 2) + (ii + 2)] = hsum(Cv22);
+ C[ldc * (jj + 2) + (ii + 3)] = hsum(Cv23);
+ C[ldc * (jj + 3) + (ii + 0)] = hsum(Cv30);
+ C[ldc * (jj + 3) + (ii + 1)] = hsum(Cv31);
+ C[ldc * (jj + 3) + (ii + 2)] = hsum(Cv32);
+ C[ldc * (jj + 3) + (ii + 3)] = hsum(Cv33);
+ C[ldc * (jj + 4) + (ii + 0)] = hsum(Cv40);
+ C[ldc * (jj + 4) + (ii + 1)] = hsum(Cv41);
+ C[ldc * (jj + 4) + (ii + 2)] = hsum(Cv42);
+ C[ldc * (jj + 4) + (ii + 3)] = hsum(Cv43);
+ C[ldc * (jj + 5) + (ii + 0)] = hsum(Cv50);
+ C[ldc * (jj + 5) + (ii + 1)] = hsum(Cv51);
+ C[ldc * (jj + 5) + (ii + 2)] = hsum(Cv52);
+ C[ldc * (jj + 5) + (ii + 3)] = hsum(Cv53);
+ }
+
+ inline void gemm_bloc_4x5(int64_t ii, int64_t jj) {
+ size_t vl = vlmax<V>();
+ D Cv00 = set_zero<D>();
+ D Cv01 = set_zero<D>();
+ D Cv02 = set_zero<D>();
+ D Cv03 = set_zero<D>();
+ D Cv10 = set_zero<D>();
+ D Cv11 = set_zero<D>();
+ D Cv12 = set_zero<D>();
+ D Cv13 = set_zero<D>();
+ D Cv20 = set_zero<D>();
+ D Cv21 = set_zero<D>();
+ D Cv22 = set_zero<D>();
+ D Cv23 = set_zero<D>();
+ D Cv30 = set_zero<D>();
+ D Cv31 = set_zero<D>();
+ D Cv32 = set_zero<D>();
+ D Cv33 = set_zero<D>();
+ D Cv40 = set_zero<D>();
+ D Cv41 = set_zero<D>();
+ D Cv42 = set_zero<D>();
+ D Cv43 = set_zero<D>();
+
+ for (int64_t l = 0; l < k; l += vl) {
+ V Bv0 = load<V>(B + ldb * (jj + 0) + l);
+ V Bv1 = load<V>(B + ldb * (jj + 1) + l);
+ V Bv2 = load<V>(B + ldb * (jj + 2) + l);
+ V Bv3 = load<V>(B + ldb * (jj + 3) + l);
+ V Bv4 = load<V>(B + ldb * (jj + 4) + l);
+
+ V Av0 = load<V>(A + lda * (ii + 0) + l);
+ Cv00 = madd(Av0, Bv0, Cv00);
+ Cv10 = madd(Av0, Bv1, Cv10);
+ Cv20 = madd(Av0, Bv2, Cv20);
+ Cv30 = madd(Av0, Bv3, Cv30);
+ Cv40 = madd(Av0, Bv4, Cv40);
+
+ V Av1 = load<V>(A + lda * (ii + 1) + l);
+ Cv01 = madd(Av1, Bv0, Cv01);
+ Cv11 = madd(Av1, Bv1, Cv11);
+ Cv21 = madd(Av1, Bv2, Cv21);
+ Cv31 = madd(Av1, Bv3, Cv31);
+ Cv41 = madd(Av1, Bv4, Cv41);
+
+ V Av2 = load<V>(A + lda * (ii + 2) + l);
+ Cv02 = madd(Av2, Bv0, Cv02);
+ Cv12 = madd(Av2, Bv1, Cv12);
+ Cv22 = madd(Av2, Bv2, Cv22);
+ Cv32 = madd(Av2, Bv3, Cv32);
+ Cv42 = madd(Av2, Bv4, Cv42);
+
+ V Av3 = load<V>(A + lda * (ii + 3) + l);
+ Cv03 = madd(Av3, Bv0, Cv03);
+ Cv13 = madd(Av3, Bv1, Cv13);
+ Cv23 = madd(Av3, Bv2, Cv23);
+ Cv33 = madd(Av3, Bv3, Cv33);
+ Cv43 = madd(Av3, Bv4, Cv43);
+ }
+
+ C[ldc * (jj + 0) + (ii + 0)] = hsum(Cv00);
+ C[ldc * (jj + 0) + (ii + 1)] = hsum(Cv01);
+ C[ldc * (jj + 0) + (ii + 2)] = hsum(Cv02);
+ C[ldc * (jj + 0) + (ii + 3)] = hsum(Cv03);
+ C[ldc * (jj + 1) + (ii + 0)] = hsum(Cv10);
+ C[ldc * (jj + 1) + (ii + 1)] = hsum(Cv11);
+ C[ldc * (jj + 1) + (ii + 2)] = hsum(Cv12);
+ C[ldc * (jj + 1) + (ii + 3)] = hsum(Cv13);
+ C[ldc * (jj + 2) + (ii + 0)] = hsum(Cv20);
+ C[ldc * (jj + 2) + (ii + 1)] = hsum(Cv21);
+ C[ldc * (jj + 2) + (ii + 2)] = hsum(Cv22);
+ C[ldc * (jj + 2) + (ii + 3)] = hsum(Cv23);
+ C[ldc * (jj + 3) + (ii + 0)] = hsum(Cv30);
+ C[ldc * (jj + 3) + (ii + 1)] = hsum(Cv31);
+ C[ldc * (jj + 3) + (ii + 2)] = hsum(Cv32);
+ C[ldc * (jj + 3) + (ii + 3)] = hsum(Cv33);
+ C[ldc * (jj + 4) + (ii + 0)] = hsum(Cv40);
+ C[ldc * (jj + 4) + (ii + 1)] = hsum(Cv41);
+ C[ldc * (jj + 4) + (ii + 2)] = hsum(Cv42);
+ C[ldc * (jj + 4) + (ii + 3)] = hsum(Cv43);
+ }
+
+ inline void gemm_bloc_4x4(int64_t ii, int64_t jj) {
+ size_t vl = vlmax<V>();
+ D Cv00 = set_zero<D>();
+ D Cv01 = set_zero<D>();
+ D Cv02 = set_zero<D>();
+ D Cv03 = set_zero<D>();
+ D Cv10 = set_zero<D>();
+ D Cv11 = set_zero<D>();
+ D Cv12 = set_zero<D>();
+ D Cv13 = set_zero<D>();
+ D Cv20 = set_zero<D>();
+ D Cv21 = set_zero<D>();
+ D Cv22 = set_zero<D>();
+ D Cv23 = set_zero<D>();
+ D Cv30 = set_zero<D>();
+ D Cv31 = set_zero<D>();
+ D Cv32 = set_zero<D>();
+ D Cv33 = set_zero<D>();
+
+ for (int64_t l = 0; l < k; l += vl) {
+ V Av0 = load<V>(A + lda * (ii + 0) + l);
+ V Av1 = load<V>(A + lda * (ii + 1) + l);
+ V Av2 = load<V>(A + lda * (ii + 2) + l);
+ V Av3 = load<V>(A + lda * (ii + 3) + l);
+
+ V Bv0 = load<V>(B + ldb * (jj + 0) + l);
+ Cv00 = madd(Av0, Bv0, Cv00);
+ Cv01 = madd(Av1, Bv0, Cv01);
+ Cv02 = madd(Av2, Bv0, Cv02);
+ Cv03 = madd(Av3, Bv0, Cv03);
+
+ V Bv1 = load<V>(B + ldb * (jj + 1) + l);
+ Cv10 = madd(Av0, Bv1, Cv10);
+ Cv11 = madd(Av1, Bv1, Cv11);
+ Cv12 = madd(Av2, Bv1, Cv12);
+ Cv13 = madd(Av3, Bv1, Cv13);
+
+ V Bv2 = load<V>(B + ldb * (jj + 2) + l);
+ Cv20 = madd(Av0, Bv2, Cv20);
+ Cv21 = madd(Av1, Bv2, Cv21);
+ Cv22 = madd(Av2, Bv2, Cv22);
+ Cv23 = madd(Av3, Bv2, Cv23);
+
+ V Bv3 = load<V>(B + ldb * (jj + 3) + l);
+ Cv30 = madd(Av0, Bv3, Cv30);
+ Cv31 = madd(Av1, Bv3, Cv31);
+ Cv32 = madd(Av2, Bv3, Cv32);
+ Cv33 = madd(Av3, Bv3, Cv33);
+ }
+
+ C[ldc * (jj + 0) + (ii + 0)] = hsum(Cv00);
+ C[ldc * (jj + 0) + (ii + 1)] = hsum(Cv01);
+ C[ldc * (jj + 0) + (ii + 2)] = hsum(Cv02);
+ C[ldc * (jj + 0) + (ii + 3)] = hsum(Cv03);
+ C[ldc * (jj + 1) + (ii + 0)] = hsum(Cv10);
+ C[ldc * (jj + 1) + (ii + 1)] = hsum(Cv11);
+ C[ldc * (jj + 1) + (ii + 2)] = hsum(Cv12);
+ C[ldc * (jj + 1) + (ii + 3)] = hsum(Cv13);
+ C[ldc * (jj + 2) + (ii + 0)] = hsum(Cv20);
+ C[ldc * (jj + 2) + (ii + 1)] = hsum(Cv21);
+ C[ldc * (jj + 2) + (ii + 2)] = hsum(Cv22);
+ C[ldc * (jj + 2) + (ii + 3)] = hsum(Cv23);
+ C[ldc * (jj + 3) + (ii + 0)] = hsum(Cv30);
+ C[ldc * (jj + 3) + (ii + 1)] = hsum(Cv31);
+ C[ldc * (jj + 3) + (ii + 2)] = hsum(Cv32);
+ C[ldc * (jj + 3) + (ii + 3)] = hsum(Cv33);
+ }
+
+ inline void gemm_bloc_4x3(int64_t ii, int64_t jj) {
+ size_t vl = vlmax<V>();
+ D Cv00 = set_zero<D>();
+ D Cv01 = set_zero<D>();
+ D Cv02 = set_zero<D>();
+ D Cv03 = set_zero<D>();
+ D Cv10 = set_zero<D>();
+ D Cv11 = set_zero<D>();
+ D Cv12 = set_zero<D>();
+ D Cv13 = set_zero<D>();
+ D Cv20 = set_zero<D>();
+ D Cv21 = set_zero<D>();
+ D Cv22 = set_zero<D>();
+ D Cv23 = set_zero<D>();
+
+ for (int64_t l = 0; l < k; l += vl) {
+ V Av0 = load<V>(A + lda * (ii + 0) + l);
+ V Av1 = load<V>(A + lda * (ii + 1) + l);
+ V Av2 = load<V>(A + lda * (ii + 2) + l);
+ V Av3 = load<V>(A + lda * (ii + 3) + l);
+
+ V Bv0 = load<V>(B + ldb * (jj + 0) + l);
+ Cv00 = madd(Av0, Bv0, Cv00);
+ Cv01 = madd(Av1, Bv0, Cv01);
+ Cv02 = madd(Av2, Bv0, Cv02);
+ Cv03 = madd(Av3, Bv0, Cv03);
+
+ V Bv1 = load<V>(B + ldb * (jj + 1) + l);
+ Cv10 = madd(Av0, Bv1, Cv10);
+ Cv11 = madd(Av1, Bv1, Cv11);
+ Cv12 = madd(Av2, Bv1, Cv12);
+ Cv13 = madd(Av3, Bv1, Cv13);
+
+ V Bv2 = load<V>(B + ldb * (jj + 2) + l);
+ Cv20 = madd(Av0, Bv2, Cv20);
+ Cv21 = madd(Av1, Bv2, Cv21);
+ Cv22 = madd(Av2, Bv2, Cv22);
+ Cv23 = madd(Av3, Bv2, Cv23);
+ }
+
+ C[ldc * (jj + 0) + (ii + 0)] = hsum(Cv00);
+ C[ldc * (jj + 0) + (ii + 1)] = hsum(Cv01);
+ C[ldc * (jj + 0) + (ii + 2)] = hsum(Cv02);
+ C[ldc * (jj + 0) + (ii + 3)] = hsum(Cv03);
+ C[ldc * (jj + 1) + (ii + 0)] = hsum(Cv10);
+ C[ldc * (jj + 1) + (ii + 1)] = hsum(Cv11);
+ C[ldc * (jj + 1) + (ii + 2)] = hsum(Cv12);
+ C[ldc * (jj + 1) + (ii + 3)] = hsum(Cv13);
+ C[ldc * (jj + 2) + (ii + 0)] = hsum(Cv20);
+ C[ldc * (jj + 2) + (ii + 1)] = hsum(Cv21);
+ C[ldc * (jj + 2) + (ii + 2)] = hsum(Cv22);
+ C[ldc * (jj + 2) + (ii + 3)] = hsum(Cv23);
+ }
+
+ inline void gemm_bloc_4x2(int64_t ii, int64_t jj) {
+ size_t vl = vlmax<V>();
+ D Cv00 = set_zero<D>();
+ D Cv01 = set_zero<D>();
+ D Cv02 = set_zero<D>();
+ D Cv03 = set_zero<D>();
+ D Cv10 = set_zero<D>();
+ D Cv11 = set_zero<D>();
+ D Cv12 = set_zero<D>();
+ D Cv13 = set_zero<D>();
+
+ for (int64_t l = 0; l < k; l += vl) {
+ V Av0 = load<V>(A + lda * (ii + 0) + l);
+ V Av1 = load<V>(A + lda * (ii + 1) + l);
+ V Av2 = load<V>(A + lda * (ii + 2) + l);
+ V Av3 = load<V>(A + lda * (ii + 3) + l);
+
+ V Bv0 = load<V>(B + ldb * (jj + 0) + l);
+ Cv00 = madd(Av0, Bv0, Cv00);
+ Cv01 = madd(Av1, Bv0, Cv01);
+ Cv02 = madd(Av2, Bv0, Cv02);
+ Cv03 = madd(Av3, Bv0, Cv03);
+
+ V Bv1 = load<V>(B + ldb * (jj + 1) + l);
+ Cv10 = madd(Av0, Bv1, Cv10);
+ Cv11 = madd(Av1, Bv1, Cv11);
+ Cv12 = madd(Av2, Bv1, Cv12);
+ Cv13 = madd(Av3, Bv1, Cv13);
+ }
+
+ C[ldc * (jj + 0) + (ii + 0)] = hsum(Cv00);
+ C[ldc * (jj + 0) + (ii + 1)] = hsum(Cv01);
+ C[ldc * (jj + 0) + (ii + 2)] = hsum(Cv02);
+ C[ldc * (jj + 0) + (ii + 3)] = hsum(Cv03);
+ C[ldc * (jj + 1) + (ii + 0)] = hsum(Cv10);
+ C[ldc * (jj + 1) + (ii + 1)] = hsum(Cv11);
+ C[ldc * (jj + 1) + (ii + 2)] = hsum(Cv12);
+ C[ldc * (jj + 1) + (ii + 3)] = hsum(Cv13);
+ }
+
+ inline void gemm_bloc_4x1(int64_t ii, int64_t jj) {
+ size_t vl = vlmax<V>();
+ D Cv00 = set_zero<D>();
+ D Cv01 = set_zero<D>();
+ D Cv02 = set_zero<D>();
+ D Cv03 = set_zero<D>();
+
+ for (int64_t l = 0; l < k; l += vl) {
+ V Av0 = load<V>(A + lda * (ii + 0) + l);
+ V Av1 = load<V>(A + lda * (ii + 1) + l);
+ V Av2 = load<V>(A + lda * (ii + 2) + l);
+ V Av3 = load<V>(A + lda * (ii + 3) + l);
+
+ V Bv0 = load<V>(B + ldb * (jj + 0) + l);
+ Cv00 = madd(Av0, Bv0, Cv00);
+ Cv01 = madd(Av1, Bv0, Cv01);
+ Cv02 = madd(Av2, Bv0, Cv02);
+ Cv03 = madd(Av3, Bv0, Cv03);
+ }
+
+ C[ldc * (jj + 0) + (ii + 0)] = hsum(Cv00);
+ C[ldc * (jj + 0) + (ii + 1)] = hsum(Cv01);
+ C[ldc * (jj + 0) + (ii + 2)] = hsum(Cv02);
+ C[ldc * (jj + 0) + (ii + 3)] = hsum(Cv03);
+ }
+
+ inline void gemm_bloc_2x2(int64_t ii, int64_t jj) {
+ size_t vl = vlmax<V>();
+ D Cv00 = set_zero<D>();
+ D Cv01 = set_zero<D>();
+ D Cv10 = set_zero<D>();
+ D Cv11 = set_zero<D>();
+
+ for (int64_t l = 0; l < k; l += vl) {
+ V Av0 = load<V>(A + lda * (ii + 0) + l);
+ V Av1 = load<V>(A + lda * (ii + 1) + l);
+
+ V Bv0 = load<V>(B + ldb * (jj + 0) + l);
+ Cv00 = madd(Av0, Bv0, Cv00);
+ Cv01 = madd(Av1, Bv0, Cv01);
+
+ V Bv1 = load<V>(B + ldb * (jj + 1) + l);
+ Cv10 = madd(Av0, Bv1, Cv10);
+ Cv11 = madd(Av1, Bv1, Cv11);
+ }
+
+ C[ldc * (jj + 0) + (ii + 0)] = hsum(Cv00);
+ C[ldc * (jj + 0) + (ii + 1)] = hsum(Cv01);
+ C[ldc * (jj + 1) + (ii + 0)] = hsum(Cv10);
+ C[ldc * (jj + 1) + (ii + 1)] = hsum(Cv11);
+ }
+
+ inline void gemm_bloc_2x1(int64_t ii, int64_t jj) {
+ size_t vl = vlmax<V>();
+ D Cv00 = set_zero<D>();
+ D Cv01 = set_zero<D>();
+
+ for (int64_t l = 0; l < k; l += vl) {
+ V Av0 = load<V>(A + lda * (ii + 0) + l);
+ V Av1 = load<V>(A + lda * (ii + 1) + l);
+
+ V Bv0 = load<V>(B + ldb * (jj + 0) + l);
+ Cv00 = madd(Av0, Bv0, Cv00);
+ Cv01 = madd(Av1, Bv0, Cv01);
+ }
+
+ C[ldc * (jj + 0) + (ii + 0)] = hsum(Cv00);
+ C[ldc * (jj + 0) + (ii + 1)] = hsum(Cv01);
+ }
+
+ template <int RM, int RN>
+ inline void gemm_bloc(int64_t ii, int64_t jj) {
+ if constexpr (RM == 4) {
+ if constexpr (RN == 6) { return gemm_bloc_4x6(ii, jj); }
+ if constexpr (RN == 5) { return gemm_bloc_4x5(ii, jj); }
+ if constexpr (RN == 4) { return gemm_bloc_4x4(ii, jj); }
+ if constexpr (RN == 3) { return gemm_bloc_4x3(ii, jj); }
+ if constexpr (RN == 2) { return gemm_bloc_4x2(ii, jj); }
+ if constexpr (RN == 1) { return gemm_bloc_4x1(ii, jj); }
+ } else if constexpr (RM == 2) {
+ if constexpr (RN == 2) { return gemm_bloc_2x2(ii, jj); }
+ if constexpr (RN == 1) { return gemm_bloc_2x1(ii, jj); }
+ }
+ }
+
+ template <int RM, int RN, int BM>
+ NOINLINE void gemm(int64_t m, int64_t n, int64_t BN) {
+ GGML_ASSERT(m % (RM * BM) == 0);
+ const int64_t ytiles = m / (RM * BM);
+ const int64_t xtiles = (n + RN -1) / RN;
+ const int64_t jj_RN = (xtiles - (xtiles * RN - n));
+
+ // "round" bloc_size to "nearest" BN
+ const int64_t NB_BN = xtiles < BN ? 1 : (xtiles + BN / 2) / BN;
+ const int64_t SIZE_BN = xtiles % NB_BN == 0 ? xtiles / NB_BN : xtiles / NB_BN + 1;
+ const int64_t jj_BN = (NB_BN - (NB_BN * SIZE_BN - xtiles));
+ const int64_t nb_job = ytiles * NB_BN;
+
+ if (params->ith == 0) {
+ GGML_ASSERT( jj_BN * SIZE_BN + (NB_BN - jj_BN) * (SIZE_BN - 1) == xtiles);
+ // Every thread starts at ith, so the first unprocessed chunk is nth. This save a bit of coordination right at the start.
+ ggml_threadpool_chunk_set(params->threadpool, params->nth);
+ }
+
+ ggml_barrier(params->threadpool);
+
+ int64_t job = params->ith;
+ while (job < nb_job) {
+ const int64_t ii = (job % ytiles) * RM * BM;
+ const int64_t jb = job / ytiles;
+ const int64_t jr0 = BLOC_POS(jb , jj_BN, SIZE_BN);
+ const int64_t jrN = BLOC_POS(jb+1, jj_BN, SIZE_BN);
+
+ const int64_t jj0 = BLOC_POS(jr0, jj_RN, RN);
+ const int64_t jj2 = BLOC_POS(jrN, jj_RN, RN);
+ const int64_t jj1 = jj2 < jj_RN * RN ? jj2 : jj_RN * RN;
+
+ for (int64_t bi = 0; bi < BM * RM; bi += RM) {
+ int64_t jj = jj0;
+ for (; jj < jj1; jj += RN) {
+ gemm_bloc<RM, RN>(ii + bi, jj);
+ }
+ if constexpr (RN > 1) {
+ for (; jj < jj2; jj += RN - 1) {
+ gemm_bloc<RM, RN-1>(ii + bi, jj);
+ }
+ }
+ GGML_ASSERT(jj == jj2);
+ }
+
+ job = ggml_threadpool_chunk_add(params->threadpool, 1);
+ }
+
+ ggml_barrier(params->threadpool);
+ return;
+ }
+
+ const ggml_compute_params * params;
+ const TA *const A;
+ const TB *const B;
+ TC *const C;
+ const int64_t k;
+ const int64_t lda;
+ const int64_t ldb;
+ const int64_t ldc;
+};
+#endif
+
+//////////////////////////////////////////////////////////////////////////////////////////
+// QUANT ZERO MATRIX MULTIPLICATION
+
+#if defined(__ARM_FEATURE_DOTPROD)
+template <typename TA>
+class tinyBLAS_Q0_ARM {
+ public:
+ tinyBLAS_Q0_ARM(int64_t k,
+ const TA *A, int64_t lda,
+ const block_q8_0 *B, int64_t ldb,
+ float *C, int64_t ldc,
+ int ith, int nth)
+ : A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
+ }
+
+ void matmul(int64_t m, int64_t n) {
+ mnpack(0, m, 0, n);
+ }
+
+ private:
+ NOINLINE void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int64_t mc, nc, mp, np;
+ switch ((MIN(m - m0, 3) << 4) | MIN(n - n0, 3ll)) {
+ case 0x33:
+ mc = 3;
+ nc = 3;
+ gemm<3, 3>(m0, m, n0, n);
+ break;
+ case 0x32:
+ mc = 3;
+ nc = 2;
+ gemm<3, 2>(m0, m, n0, n);
+ break;
+ case 0x23:
+ mc = 2;
+ nc = 3;
+ gemm<2, 3>(m0, m, n0, n);
+ break;
+ case 0x22:
+ mc = 2;
+ nc = 2;
+ gemm<2, 2>(m0, m, n0, n);
+ break;
+ case 0x31:
+ mc = 3;
+ nc = 1;
+ gemm<3, 1>(m0, m, n0, n);
+ break;
+ case 0x13:
+ mc = 1;
+ nc = 3;
+ gemm<1, 3>(m0, m, n0, n);
+ break;
+ case 0x21:
+ mc = 2;
+ nc = 1;
+ gemm<2, 1>(m0, m, n0, n);
+ break;
+ case 0x12:
+ mc = 1;
+ nc = 2;
+ gemm<1, 2>(m0, m, n0, n);
+ break;
+ case 0x11:
+ mc = 1;
+ nc = 1;
+ gemm<1, 1>(m0, m, n0, n);
+ break;
+ default:
+ return;
+ }
+ mp = m0 + (m - m0) / mc * mc;
+ np = n0 + (n - n0) / nc * nc;
+ mnpack(mp, m, n0, np);
+ mnpack(m0, m, np, n);
+ }
+
+ template <int RM, int RN>
+ NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int64_t ytiles = (m - m0) / RM;
+ int64_t xtiles = (n - n0) / RN;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ if (end > tiles)
+ end = tiles;
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = m0 + job / xtiles * RM;
+ int64_t jj = n0 + job % xtiles * RN;
+ float32x4_t Cv[RN][RM] = {};
+ for (int64_t l = 0; l < k; ++l)
+ for (int64_t j = 0; j < RN; ++j)
+ for (int64_t i = 0; i < RM; ++i)
+ Cv[j][i] = vmlaq_n_f32(Cv[j][i],
+ vcvtq_f32_s32(vdotq_s32(
+ vdotq_s32(vdupq_n_s32(0),
+ load_lo(A + lda * (ii + i) + l),
+ load_lo(B + ldb * (jj + j) + l)),
+ load_hi(A + lda * (ii + i) + l),
+ load_hi(B + ldb * (jj + j) + l))),
+ unhalf(A[lda * (ii + i) + l].d) *
+ unhalf(B[ldb * (jj + j) + l].d));
+ for (int64_t j = 0; j < RN; ++j)
+ for (int64_t i = 0; i < RM; ++i)
+ C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
+ }
+ }
+
+ inline int8x16_t load_lo(const block_q8_0 *b) {
+ return vld1q_s8(b->qs);
+ }
+
+ inline int8x16_t load_hi(const block_q8_0 *b) {
+ return vld1q_s8(b->qs + 16);
+ }
+
+ inline int8x16_t load_lo(const block_q4_0 *b) {
+ return vsubq_s8(vreinterpretq_s8_u8(vandq_u8(vld1q_u8(b->qs),
+ vdupq_n_u8(0x0f))),
+ vdupq_n_s8(0x8));
+ }
+
+ inline int8x16_t load_hi(const block_q4_0 *b) {
+ return vsubq_s8(vreinterpretq_s8_u8(vshrq_n_u8(vld1q_u8(b->qs), 4)),
+ vdupq_n_s8(0x8));
+ }
+
+ const TA *const A;
+ const block_q8_0 *const B;
+ float *const C;
+ const int64_t k;
+ const int64_t lda;
+ const int64_t ldb;
+ const int64_t ldc;
+ const int ith;
+ const int nth;
+};
+#endif // __ARM_FEATURE_DOTPROD
+
+#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__)
+template <typename TA, typename TB, typename TC>
+class tinyBLAS_Q0_AVX {
+ public:
+ tinyBLAS_Q0_AVX(int64_t k,
+ const TA *A, int64_t lda,
+ const TB *B, int64_t ldb,
+ TC *C, int64_t ldc,
+ int ith, int nth)
+ : A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
+ const int8_t kvalues_iq4nl[16] = {
+ -127, -104, -83, -65,
+ -49, -35, -22, -10,
+ 1, 13, 25, 38,
+ 53, 69, 89, 113
+ };
+
+ iq4nlt = _mm_loadu_si128((const __m128i *)kvalues_iq4nl);
+ }
+
+ void matmul(int64_t m, int64_t n) {
+ mnpack(0, m, 0, n);
+ }
+
+ private:
+ void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int64_t mc, nc, mp, np;
+ switch ((MIN(m - m0, 4) << 4) | MIN(n - n0, 4)) {
+#if VECTOR_REGISTERS == 32
+ case 0x44:
+ mc = 4;
+ nc = 4;
+#if defined(__AVX2__) && defined(__F16C__)
+ gemm4xN<4>(m0, m, n0, n);
+#else
+ gemm<4, 4>(m0, m, n0, n);
+#endif
+ break;
+ case 0x43:
+ mc = 4;
+ nc = 3;
+#if defined(__AVX2__) && defined(__F16C__)
+ gemm4xN<3>(m0, m, n0, n);
+#else
+ gemm<4, 3>(m0, m, n0, n);
+#endif
+ break;
+ case 0x34:
+ mc = 3;
+ nc = 4;
+#if defined(__AVX2__) && defined(__F16C__)
+ gemmMx4<3>(m0, m, n0, n);
+#else
+ gemm<3, 4>(m0, m, n0, n);
+#endif
+ break;
+ case 0x33:
+ mc = 3;
+ nc = 3;
+ gemm<3, 3>(m0, m, n0, n);
+ break;
+ case 0x42:
+ mc = 4;
+ nc = 2;
+#if defined(__AVX2__) && defined(__F16C__)
+ gemm4xN<2>(m0, m, n0, n);
+#else
+ gemm<4, 2>(m0, m, n0, n);
+#endif
+ break;
+ case 0x24:
+ mc = 2;
+ nc = 4;
+#if defined(__AVX2__) && defined(__F16C__)
+ gemmMx4<2>(m0, m, n0, n);
+#else
+ gemm<2, 4>(m0, m, n0, n);
+#endif
+ break;
+#else
+ case 0x44:
+ case 0x43:
+ case 0x42:
+ mc = 4;
+ nc = 2;
+#if defined(__AVX2__) && defined(__F16C__)
+ gemm4xN<2>(m0, m, n0, n);
+#else
+ gemm<4, 2>(m0, m, n0, n);
+#endif
+ break;
+ case 0x34:
+ case 0x24:
+ mc = 2;
+ nc = 4;
+#if defined(__AVX2__) && defined(__F16C__)
+ gemmMx4<2>(m0, m, n0, n);
+#else
+ gemm<2, 4>(m0, m, n0, n);
+#endif
+ break;
+ case 0x33:
+#endif
+ case 0x32:
+ mc = 3;
+ nc = 2;
+ gemm<3, 2>(m0, m, n0, n);
+ break;
+ case 0x23:
+ mc = 2;
+ nc = 3;
+ gemm<2, 3>(m0, m, n0, n);
+ break;
+ case 0x41:
+ mc = 4;
+ nc = 1;
+#if defined(__AVX2__) && defined(__F16C__)
+ gemm4xN<1>(m0, m, n0, n);
+#else
+ gemm<4, 1>(m0, m, n0, n);
+#endif
+ break;
+ case 0x22:
+ mc = 2;
+ nc = 2;
+ gemm<2, 2>(m0, m, n0, n);
+ break;
+ case 0x14:
+ mc = 1;
+ nc = 4;
+#if defined(__AVX2__) && defined(__F16C__)
+ gemmMx4<1>(m0, m, n0, n);
+#else
+ gemm<1, 4>(m0, m, n0, n);
+#endif
+ break;
+ case 0x31:
+ mc = 3;
+ nc = 1;
+ gemm<3, 1>(m0, m, n0, n);
+ break;
+ case 0x13:
+ mc = 1;
+ nc = 3;
+ gemm<1, 3>(m0, m, n0, n);
+ break;
+ case 0x21:
+ mc = 2;
+ nc = 1;
+ gemm<2, 1>(m0, m, n0, n);
+ break;
+ case 0x12:
+ mc = 1;
+ nc = 2;
+ gemm<1, 2>(m0, m, n0, n);
+ break;
+ case 0x11:
+ mc = 1;
+ nc = 1;
+ gemm<1, 1>(m0, m, n0, n);
+ break;
+ default:
+ return;
+ }
+ mp = m0 + (m - m0) / mc * mc;
+ np = n0 + (n - n0) / nc * nc;
+ mnpack(mp, m, n0, np);
+ mnpack(m0, m, np, n);
+ }
+
+#if defined(__AVX2__) && defined(__F16C__)
+// Templated functions for gemm of dimensions 4xN
+ template <int RN>
+ NOINLINE void gemm4xN(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int64_t ytiles = (m - m0) / 4;
+ int64_t xtiles = (n - n0) / RN;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ if (end > tiles)
+ end = tiles;
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = m0 + job / xtiles * 4;
+ int64_t jj = n0 + job % xtiles * RN;
+ __m256 Cv[RN][4] = {};
+ for (int64_t l = 0; l < k; ++l) {
+ uint64_t a_delta = ((uint64_t)A[lda * (ii + 3) + l].d << 48) | ((uint64_t)A[lda * (ii + 2) + l].d << 32) | ((uint64_t)A[lda * (ii + 1) + l].d << 16) | (A[lda * (ii + 0) + l].d);
+ // Convert delta values for four blocks to float values
+ __m128 da = _mm_cvtph_ps(_mm_set_epi64x(0, a_delta));
+ __m256i avec0 = load(A + lda * (ii + 0) + l);
+ __m256i avec1 = load(A + lda * (ii + 1) + l);
+ __m256i avec2 = load(A + lda * (ii + 2) + l);
+ __m256i avec3 = load(A + lda * (ii + 3) + l);
+ for (int64_t j = 0; j < RN; ++j) {
+ __m128 db = _mm_set1_ps(unhalf(B[ldb * (jj + j) + l].d));
+ // Computation of product of delta values for four blocks and replicate it across 256 bit lane
+ __m256 dvec = _mm256_castps128_ps256(_mm_mul_ps(da, db));
+ dvec = _mm256_permute2f128_ps(dvec ,dvec, 0);
+ // Computation of dot product and multiplication with appropriate delta value products
+ Cv[j][0] = madd(_mm256_shuffle_ps(dvec, dvec, 0),
+ updot(_mm256_sign_epi8(avec0, avec0),
+ _mm256_sign_epi8(load(B + ldb * (jj + j) + l), avec0)),
+ Cv[j][0]);
+ Cv[j][1] = madd(_mm256_shuffle_ps(dvec, dvec, 85),
+ updot(_mm256_sign_epi8(avec1, avec1),
+ _mm256_sign_epi8(load(B + ldb * (jj + j) + l), avec1)),
+ Cv[j][1]);
+ Cv[j][2] = madd(_mm256_shuffle_ps(dvec, dvec, 170),
+ updot(_mm256_sign_epi8(avec2, avec2),
+ _mm256_sign_epi8(load(B + ldb * (jj + j) + l), avec2)),
+ Cv[j][2]);
+ Cv[j][3] = madd(_mm256_shuffle_ps(dvec, dvec, 255),
+ updot(_mm256_sign_epi8(avec3, avec3),
+ _mm256_sign_epi8(load(B + ldb * (jj + j) + l), avec3)),
+ Cv[j][3]);
+ }
+ }
+
+ for (int64_t j = 0; j < RN; ++j)
+ for (int64_t i = 0; i < 4; ++i)
+ C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
+ }
+ }
+
+ // Templated functions for gemm of dimensions Mx4
+ template <int RM>
+ NOINLINE void gemmMx4(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int64_t ytiles = (m - m0) / RM;
+ int64_t xtiles = (n - n0) / 4;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ if (end > tiles)
+ end = tiles;
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = m0 + job / xtiles * RM;
+ int64_t jj = n0 + job % xtiles * 4;
+ __m256 Cv[4][RM] = {};
+ for (int64_t l = 0; l < k; ++l) {
+ uint64_t b_delta = ((uint64_t)B[ldb * (jj + 3) + l].d << 48) | ((uint64_t)B[ldb * (jj + 2) + l].d << 32) | ((uint64_t)B[ldb * (jj + 1) + l].d << 16) | (B[ldb * (jj + 0) + l].d);
+ // Convert delta values for four blocks to float values
+ __m128 db = _mm_cvtph_ps(_mm_set_epi64x(0, b_delta));
+ __m256i bvec0 = load(B + ldb * (jj + 0) + l);
+ __m256i bvec1 = load(B + ldb * (jj + 1) + l);
+ __m256i bvec2 = load(B + ldb * (jj + 2) + l);
+ __m256i bvec3 = load(B + ldb * (jj + 3) + l);
+ for (int64_t i = 0; i < RM; ++i) {
+ __m128 da = _mm_set1_ps(unhalf((A[lda * (ii + i) + l].d)));
+ // Computation of product of delta values for four blocks and replicate it across 256 bit lane
+ __m256 dvec = _mm256_castps128_ps256(_mm_mul_ps(da, db));
+ dvec = _mm256_permute2f128_ps(dvec ,dvec, 0);
+ // Computation of dot product and multiplication with appropriate delta value products
+ Cv[0][i] = madd(_mm256_shuffle_ps(dvec, dvec, 0),
+ updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l),
+ load(A + lda * (ii + i) + l)),
+ _mm256_sign_epi8(bvec0, load(A + lda * (ii + i) + l))),
+ Cv[0][i]);
+ Cv[1][i] = madd(_mm256_shuffle_ps(dvec, dvec, 85),
+ updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l),
+ load(A + lda * (ii + i) + l)),
+ _mm256_sign_epi8(bvec1, load(A + lda * (ii + i) + l))),
+ Cv[1][i]);
+ Cv[2][i] = madd(_mm256_shuffle_ps(dvec, dvec, 170),
+ updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l),
+ load(A + lda * (ii + i) + l)),
+ _mm256_sign_epi8(bvec2, load(A + lda * (ii + i) + l))),
+ Cv[2][i]);
+ Cv[3][i] = madd(_mm256_shuffle_ps(dvec, dvec, 255),
+ updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l),
+ load(A + lda * (ii + i) + l)),
+ _mm256_sign_epi8(bvec3, load(A + lda * (ii + i) + l))),
+ Cv[3][i]);
+ }
+ }
+ for (int64_t j = 0; j < 4; ++j)
+ for (int64_t i = 0; i < RM; ++i)
+ C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
+ }
+ }
+#endif
+
+ template <int RM, int RN>
+ NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int64_t ytiles = (m - m0) / RM;
+ int64_t xtiles = (n - n0) / RN;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ if (end > tiles)
+ end = tiles;
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = m0 + job / xtiles * RM;
+ int64_t jj = n0 + job % xtiles * RN;
+ __m256 Cv[RN][RM] = {};
+ for (int64_t l = 0; l < k; ++l)
+ for (int64_t j = 0; j < RN; ++j)
+ for (int64_t i = 0; i < RM; ++i) {
+#if defined(__AVX2__)
+ __m256 udTmp = updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l),
+ load(A + lda * (ii + i) + l)),
+ _mm256_sign_epi8(load(B + ldb * (jj + j) + l),
+ load(A + lda * (ii + i) + l)));
+#else
+ __m128i ali0 = load0(A + lda * (ii + i) + l);
+ __m128i ali1 = load1(A + lda * (ii + i) + l);
+ __m128i blj0 = load0(B + ldb * (jj + j) + l);
+ __m128i blj1 = load1(B + ldb * (jj + j) + l);
+
+ __m128i sepAA0 = _mm_sign_epi8(ali0, ali0);
+ __m128i sepAA1 = _mm_sign_epi8(ali1, ali1);
+ __m128i sepBA0 = _mm_sign_epi8(blj0, ali0);
+ __m128i sepBA1 = _mm_sign_epi8(blj1, ali1);
+
+ // updot
+ const __m128i oneFill = _mm_set1_epi16(1);
+ __m128i mad0 = _mm_maddubs_epi16(sepAA0, sepBA0);
+ __m128i mad1 = _mm_maddubs_epi16(sepAA1, sepBA1);
+ __m256 udTmp = _mm256_cvtepi32_ps(MM256_SET_M128I(_mm_madd_epi16(oneFill, mad1), _mm_madd_epi16(oneFill, mad0)));
+#endif
+ Cv[j][i] = madd(_mm256_set1_ps(unhalf(A[lda * (ii + i) + l].d) *
+ unhalf(B[ldb * (jj + j) + l].d)),
+ udTmp,
+ Cv[j][i]);
+ }
+ for (int64_t j = 0; j < RN; ++j)
+ for (int64_t i = 0; i < RM; ++i)
+ C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
+ }
+ }
+
+ inline __m256i load(const block_q8_0 *b) {
+ return _mm256_loadu_si256((const __m256i *)b->qs);
+ }
+
+ inline __m128i load0(const block_q8_0 *b) {
+ return _mm_loadu_si128((const __m128i *)b->qs);
+ }
+
+ inline __m128i load1(const block_q8_0 *b) {
+ return _mm_loadu_si128(((const __m128i *)b->qs) + 1);
+ }
+
+ inline __m256i load(const block_q4_0 *b) {
+ return _mm256_sub_epi8(denibble(b->qs), _mm256_set1_epi8(8));
+ }
+
+ inline __m128i load0(const block_q4_0 *b) {
+ const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
+ return _mm_sub_epi8(_mm_and_si128(_mm_set1_epi8(15), x), _mm_set1_epi8(8));
+ }
+
+ inline __m128i load1(const block_q4_0 *b) {
+ const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
+ return _mm_sub_epi8(_mm_and_si128(_mm_set1_epi8(15), _mm_srli_epi16(x, 4)), _mm_set1_epi8(8));
+ }
+
+ inline __m256i load(const block_q5_0 *b) {
+ return _mm256_or_si256(denibble(b->qs), bittobyte(b->qh));
+ }
+
+ inline __m128i load0(const block_q5_0* b) {
+ const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
+ uint32_t x32;
+ memcpy(&x32, b->qh, sizeof(uint32_t));
+ __m128i qxl = _mm_and_si128(_mm_set1_epi8(15), x);
+ __m128i bytesl = _mm_cmpeq_epi8(_mm_set1_epi64x(-1),
+ _mm_or_si128(_mm_set1_epi64x(0x7fbfdfeff7fbfdfe),
+ _mm_shuffle_epi8(_mm_set1_epi32(x32),
+ _mm_set_epi64x(0x0101010101010101, 0x0000000000000000))));
+ bytesl = _mm_andnot_si128(bytesl, _mm_set1_epi8((char)0xF0));
+ return _mm_or_si128(qxl, bytesl);
+ }
+
+ inline __m128i load1(const block_q5_0* b) {
+ const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
+ uint32_t x32;
+ memcpy(&x32, b->qh, sizeof(uint32_t));
+ __m128i qxh = _mm_and_si128(_mm_set1_epi8(15), _mm_srli_epi16(x, 4));
+ __m128i bytesh = _mm_cmpeq_epi8(_mm_set1_epi64x(-1),
+ _mm_or_si128(_mm_set1_epi64x(0x7fbfdfeff7fbfdfe),
+ _mm_shuffle_epi8(_mm_set1_epi32(x32),
+ _mm_set_epi64x(0x0303030303030303, 0x0202020202020202))));
+ bytesh = _mm_andnot_si128(bytesh, _mm_set1_epi8((char)0xF0));
+ return _mm_or_si128(qxh, bytesh);
+ }
+
+ inline __m256i load(const block_iq4_nl *b) {
+ return MM256_SET_M128I(load1(b), load0(b));
+ }
+
+ inline __m128i load0(const block_iq4_nl *b) {
+ const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
+ return _mm_shuffle_epi8(iq4nlt, _mm_and_si128(_mm_set1_epi8(15), x));
+ }
+
+ inline __m128i load1(const block_iq4_nl *b) {
+ const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
+ return _mm_shuffle_epi8(iq4nlt, _mm_and_si128(_mm_set1_epi8(15), _mm_srli_epi16(x, 4)));
+ }
+
+ inline __m256 updot(__m256i u, __m256i s) {
+ __m256i res;
+#if defined(__AVX512VNNI__) && defined(__AVX512VL__)
+ res = _mm256_dpbusd_epi32(_mm256_setzero_si256(), u, s);
+#elif defined(__AVXVNNI__)
+ res = _mm256_dpbusd_avx_epi32(_mm256_setzero_si256(), u, s);
+#else
+ res = _mm256_madd_epi16(_mm256_set1_epi16(1), _mm256_maddubs_epi16(u, s));
+#endif
+ return _mm256_cvtepi32_ps(res);
+ }
+
+ static inline __m256i denibble(const uint8_t *p) {
+ __m128i x = _mm_loadu_si128((const __m128i *)p);
+ return _mm256_and_si256(_mm256_set1_epi8(15),
+ _mm256_insertf128_si256(_mm256_castsi128_si256(x),
+ _mm_srli_epi16(x, 4), 1));
+ }
+
+ static inline __m256i bittobyte(const uint8_t *p) {
+ uint32_t x32;
+ memcpy(&x32, p, sizeof(uint32_t));
+ __m256i bytes = _mm256_cmpeq_epi8(_mm256_set1_epi64x(-1),
+ _mm256_or_si256(_mm256_set1_epi64x(0x7fbfdfeff7fbfdfe),
+ _mm256_shuffle_epi8(_mm256_set1_epi32(x32),
+ _mm256_set_epi64x(0x0303030303030303, 0x0202020202020202,
+ 0x0101010101010101, 0x0000000000000000))));
+ return _mm256_andnot_si256(bytes, _mm256_set1_epi8((char)0xF0));
+ }
+
+ const TA *const A;
+ const TB *const B;
+ TC *const C;
+ const int64_t k;
+ const int64_t lda;
+ const int64_t ldb;
+ const int64_t ldc;
+ const int ith;
+ const int nth;
+ __m128i iq4nlt;
+};
+#endif // __AVX__
+
+//PPC Implementation
+#if defined(__MMA__)
+
+#define SAVE_ACC(ACC, ii, jj) \
+ __builtin_mma_disassemble_acc(vec_C, ACC); \
+ for (int I = 0; I < 4; I++) { \
+ for (int J = 0; J < 4; J++) { \
+ *((float*)(C+ii+((jj+J)*ldc)+I)) = *((float*)&vec_C[I]+J); \
+ } \
+ } \
+
+template<typename T>
+struct mma_instr;
+
+template<>
+struct mma_instr<ggml_bf16_t> {
+ static inline void outer_product(acc_t *acc, vec_t a, vec_t b) {
+ __builtin_mma_xvbf16ger2pp(acc, a, b);
+ }
+};
+
+template<>
+struct mma_instr<ggml_fp16_t> {
+ static inline void outer_product(acc_t *acc, vec_t a, vec_t b) {
+ __builtin_mma_xvf16ger2pp(acc, a, b);
+ }
+};
+
+template <typename TA, typename TB, typename TC>
+class tinyBLAS_HP16_PPC {
+ public:
+ tinyBLAS_HP16_PPC(int64_t k,
+ const TA *A, int64_t lda,
+ const TB *B, int64_t ldb,
+ TC *C, int64_t ldc,
+ int ith, int nth)
+ : A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
+ }
+
+ void matmul(int64_t m, int64_t n) {
+ mnpack(0, m, 0, n);
+ }
+
+ private:
+ void vector_permute_store(vec_t *c, int numVec, unsigned char *vecOffset) {
+ vec_t t[8], s[8];
+ vec_t swiz1 = {0, 1, 2, 3, 16, 17, 18, 19, 4, 5, 6, 7, 20, 21, 22, 23};
+ vec_t swiz2 = {8, 9, 10, 11, 24, 25, 26, 27, 12, 13, 14, 15, 28, 29, 30, 31};
+ vec_t swiz3 = {0, 1, 2, 3, 4, 5, 6, 7, 16, 17, 18, 19, 20, 21, 22, 23};
+ vec_t swiz4 = {8, 9, 10, 11, 12, 13, 14, 15, 24, 25, 26, 27, 28, 29, 30, 31};
+
+ if (numVec == 2) {
+ t[0] = vec_perm(c[0], c[1], swiz1);
+ t[1] = vec_perm(c[2], c[3], swiz1);
+ s[0] = vec_perm(t[0], t[1], swiz3);
+ s[1] = vec_perm(t[0], t[1], swiz4);
+ vec_xst(s[0], 0, (vec_t*)vecOffset);
+ vec_xst(s[1], 0, (vec_t*)(vecOffset + 16));
+ } else if (numVec == 4) {
+ t[0] = vec_perm(c[0], c[1], swiz1);
+ t[1] = vec_perm(c[0], c[1], swiz2);
+ t[2] = vec_perm(c[2], c[3], swiz1);
+ t[3] = vec_perm(c[2], c[3], swiz2);
+ s[0] = vec_perm(t[0], t[2], swiz3);
+ s[1] = vec_perm(t[0], t[2], swiz4);
+ s[2] = vec_perm(t[1], t[3], swiz3);
+ s[3] = vec_perm(t[1], t[3], swiz4);
+ for (int i = 0; i < 4; ++i)
+ vec_xst(s[i], 0, (vec_t*)(vecOffset + i * 16));
+ } else if (numVec == 8) {
+ for (int i = 0; i < 4; i += 2) {
+ t[i+0] = vec_perm(c[i+0], c[i+1], swiz1);
+ t[i+1] = vec_perm(c[i+0], c[i+1], swiz2);
+ }
+ for (int i = 4; i < 8; i += 2) {
+ t[i+0] = vec_perm(c[i+0], c[i+1], swiz1);
+ t[i+1] = vec_perm(c[i+0], c[i+1], swiz2);
+ }
+ s[0] = vec_perm(t[0], t[2], swiz3);
+ s[1] = vec_perm(t[0], t[2], swiz4);
+ s[2] = vec_perm(t[1], t[3], swiz3);
+ s[3] = vec_perm(t[1], t[3], swiz4);
+ s[4] = vec_perm(t[4], t[6], swiz3);
+ s[5] = vec_perm(t[4], t[6], swiz4);
+ s[6] = vec_perm(t[5], t[7], swiz3);
+ s[7] = vec_perm(t[5], t[7], swiz4);
+ for (int i = 0; i < 8; ++i)
+ vec_xst(s[i], 0, (vec_t*)(vecOffset + i * 16));
+ }
+ }
+
+ void packNormal(const TA* a, int64_t lda, int rows, int cols, unsigned char* vec) {
+ int64_t i, j;
+ TA *aoffset = NULL;
+ unsigned char *vecOffset = NULL;
+ TA * aoffsets[8];
+ vector unsigned char c_arr[8];
+ aoffset = const_cast<TA*>(a);
+ vecOffset = vec;
+ j = (rows >> 3);
+ if (j > 0) {
+ do {
+ if (cols == 4) {
+ aoffsets[0] = aoffset;
+ for (int it = 1; it < 4; ++it)
+ aoffsets[it] = aoffsets[it-1] + lda;
+ aoffset += 4 * lda;
+ for (int i = 0; i < 4; ++i)
+ c_arr[i] = vec_xl(0, (vector unsigned char*)aoffsets[i]);
+ vector_permute_store(c_arr, 4, vecOffset);
+ for (int i = 0; i<4; i++)
+ aoffsets[i] = aoffsets[i]+lda;
+ vecOffset +=64;
+ }
+ i = (cols >> 3);
+ if (i > 0) {
+ aoffsets[0] = aoffset;
+ for (int it = 1; it < 8; ++it) {
+ aoffsets[it] = aoffsets[it-1] + lda;
+ }
+ aoffset += 8 * lda;
+ do {
+ for (int it = 0; it < 8; ++it)
+ c_arr[it] = vec_xl(0, (vector unsigned char*)aoffsets[it]);
+ vector_permute_store(c_arr, 8, vecOffset);
+ for (int it = 0; it < 8; ++it)
+ aoffsets[it] = aoffsets[it] + 8*lda;
+ vecOffset += 128;
+ i--;
+ } while(i > 0);
+ }
+ j--;
+ } while(j > 0);
+ }
+ if (rows & 4) {
+ aoffsets[0] = aoffset;
+ for (int it = 1; it < 4; ++it)
+ aoffsets[it] = aoffsets[it-1] + lda;
+ aoffset += 4 * lda;
+ if (cols == 4) {
+ for (int it = 0; it < 4; ++it)
+ c_arr[it] = vec_xl(0, (vector unsigned char*)aoffsets[it]);
+ vector_permute_store(c_arr, 2, vecOffset);
+ for (int it = 0; it< 4; it++)
+ aoffsets[it] = aoffsets[it] + lda;
+ vecOffset += 32;
+ }
+ i = (cols >> 3);
+ if (i > 0) {
+ do {
+ for (int it = 0; it < 4; ++it)
+ c_arr[it] = vec_xl(0, (vector unsigned char*)aoffsets[it]);
+ vector_permute_store(c_arr, 4, vecOffset);
+ for (int it = 0; it< 4; it++)
+ aoffsets[it] = aoffsets[it] + 8*lda;
+ vecOffset += 64;
+ i--;
+ } while(i > 0);
+ }
+ }
+ if (rows & 3) {
+ aoffsets[0] = aoffset;
+ for (int it = 1; it < 4; ++it)
+ aoffsets[it] = aoffsets[it-1] + lda;
+ if (cols == 4) {
+ switch(rows) {
+ case 3: c_arr[2] = vec_xl(0, (vector unsigned char*)aoffsets[2]);
+ case 2: c_arr[1] = vec_xl(0, (vector unsigned char*)aoffsets[1]);
+ case 1: c_arr[0] = vec_xl(0, (vector unsigned char*)aoffsets[0]);
+ break;
+ }
+ vector_permute_store(c_arr, 2, vecOffset);
+ for (int it = 0; it< 4; it++)
+ aoffsets[it] = aoffsets[it] + lda;
+ vecOffset += 32;
+ }
+ i = (cols >> 3);
+ if (i > 0) {
+ do {
+ switch(rows) {
+ case 3: c_arr[2] = vec_xl(0, (vector unsigned char*)aoffsets[2]);
+ case 2: c_arr[1] = vec_xl(0, (vector unsigned char*)aoffsets[1]);
+ case 1: c_arr[0] = vec_xl(0, (vector unsigned char*)aoffsets[0]);
+ break;
+ }
+ vector_permute_store(c_arr, 4, vecOffset);
+ for (int it = 0; it <4; it++)
+ aoffsets[it] = aoffsets[it] + 8* lda;
+ vecOffset += 64;
+ i--;
+ } while(i > 0);
+ }
+ }
+ }
+
+ void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int64_t mc, nc, mp, np;
+ int m_rem = MIN(m - m0, 8);
+ int n_rem = MIN(n - n0, 8);
+
+ if (m_rem >= 8 && n_rem >= 8) {
+ mc = 8;
+ nc = 8;
+ gemm<8,8>(m0, m, n0, n);
+ } else if (m_rem >= 4 && n_rem >= 8) {
+ mc = 4;
+ nc = 8;
+ gemm<4,8>(m0, m, n0, n);
+ } else if (m_rem >=8 && n_rem >=4){
+ mc = 8;
+ nc = 4;
+ gemm<8,4>(m0, m, n0, n);
+ } else if ((m_rem < 4) && (n_rem >= 8)) {
+ nc = 8;
+ switch(m_rem) {
+ case 1:
+ mc = 1;
+ gemm_Mx8<1>(m0, m, n0, n);
+ break;
+ case 2:
+ mc = 2;
+ gemm_Mx8<2>(m0, m, n0, n);
+ break;
+ case 3:
+ mc = 3;
+ gemm_Mx8<3>(m0, m, n0, n);
+ break;
+ default:
+ return;
+ }
+ } else if (m_rem >= 4 && n_rem >= 4) {
+ mc = 4;
+ nc = 4;
+ gemm_small<4, 4>(m0, m, n0, n);
+ } else if ((m_rem > 4) && (n_rem < 4)) {
+ mc = 4;
+ switch(n_rem) {
+ case 1:
+ nc = 1;
+ gemm_small<4, 1>(m0, m, n0, n);
+ break;
+ case 2:
+ nc = 2;
+ gemm_small<4, 2>(m0, m, n0, n);
+ break;
+ case 3:
+ nc = 3;
+ gemm_small<4, 3>(m0, m, n0, n);
+ break;
+
+ default:
+ return;
+ }
+ } else {
+ switch((m_rem << 4) | n_rem) {
+ case 0x43:
+ mc = 4;
+ nc = 3;
+ gemm_small<4, 3>(m0, m, n0, n);
+ break;
+ case 0x42:
+ mc = 4;
+ nc = 2;
+ gemm_small<4, 2>(m0, m, n0, n);
+ break;
+ case 0x41:
+ mc = 4;
+ nc = 1;
+ gemm_small<4, 1>(m0, m, n0, n);
+ break;
+ case 0x34:
+ mc = 3;
+ nc = 4;
+ gemm_small<3, 4>(m0, m, n0, n);
+ break;
+ case 0x33:
+ mc = 3;
+ nc = 3;
+ gemm_small<3, 3>(m0, m, n0, n);
+ break;
+ case 0x32:
+ mc = 3;
+ nc = 2;
+ gemm_small<3, 2>(m0, m, n0, n);
+ break;
+ case 0x31:
+ mc = 3;
+ nc = 1;
+ gemm_small<3, 1>(m0, m, n0, n);
+ break;
+ case 0x24:
+ mc = 2;
+ nc = 4;
+ gemm_small<2,4>(m0, m, n0, n);
+ break;
+ case 0x23:
+ mc = 2;
+ nc = 3;
+ gemm_small<2, 3>(m0, m, n0, n);
+ break;
+ case 0x22:
+ mc = 2;
+ nc = 2;
+ gemm_small<2, 2>(m0, m, n0, n);
+ break;
+ case 0x21:
+ mc = 2;
+ nc = 1;
+ gemm_small<2, 1>(m0, m, n0, n);
+ break;
+ case 0x14:
+ mc = 1;
+ nc = 4;
+ gemm_small<1, 4>(m0, m, n0, n);
+ break;
+ case 0x13:
+ mc = 1;
+ nc = 3;
+ gemm_small<1, 3>(m0, m, n0, n);
+ break;
+ case 0x12:
+ mc = 1;
+ nc = 2;
+ gemm_small<1, 2>(m0, m, n0, n);
+ break;
+ case 0x11:
+ mc = 1;
+ nc = 1;
+ gemm_small<1, 1>(m0, m, n0, n);
+ break;
+ default:
+ return;
+ }
+ }
+ mp = m0 + (m - m0) / mc * mc;
+ np = n0 + (n - n0) / nc * nc;
+ mnpack(mp, m, n0, np);
+ mnpack(m0, m, np, n);
+ }
+
+ void KERNEL_4x8(int64_t ii, int64_t jj) {
+ vec_t vec_A[4], vec_B[8] , vec_C[4];
+ acc_t acc_0, acc_1;
+ __builtin_mma_xxsetaccz(&acc_0);
+ __builtin_mma_xxsetaccz(&acc_1);
+ for (int l = 0; l < k; l+=8) {
+ packNormal((A+(ii*lda)+l), lda, 4, 8, (uint8_t*)vec_A);
+ packNormal((B+(jj*ldb)+l), ldb, 8, 8, (uint8_t*)vec_B);
+ for (int x = 0; x < 4; x++) {
+ mma_instr<TA>::outer_product(&acc_0, vec_A[x], vec_B[x]);
+ mma_instr<TA>::outer_product(&acc_1, vec_A[x], vec_B[x+4]);
+ }
+ }
+ SAVE_ACC(&acc_0, ii, jj);
+ SAVE_ACC(&acc_1, ii, jj+4);
+ }
+
+ void KERNEL_8x4(int64_t ii, int64_t jj) {
+ vec_t vec_A[8], vec_B[4] , vec_C[4];
+ acc_t acc_0, acc_1;
+ __builtin_mma_xxsetaccz(&acc_0);
+ __builtin_mma_xxsetaccz(&acc_1);
+ for (int l = 0; l < k; l+=8) {
+ packNormal((A+(ii*lda)+l), lda, 8, 8, (uint8_t*)vec_A);
+ packNormal((B+(jj*ldb)+l), ldb, 8, 4, (uint8_t*)vec_B);
+ for (int x = 0; x < 4; x++) {
+ mma_instr<TA>::outer_product(&acc_0, vec_A[x], vec_B[x]);
+ mma_instr<TA>::outer_product(&acc_1, vec_A[x], vec_B[x+4]);
+ }
+ }
+ SAVE_ACC(&acc_0, ii, jj);
+ SAVE_ACC(&acc_1, ii+4, jj);
+ }
+
+
+ void KERNEL_8x8(int64_t ii, int64_t jj) {
+ vec_t vec_A[8], vec_B[8], vec_C[4];
+ acc_t acc_0, acc_1, acc_2, acc_3;
+ __builtin_mma_xxsetaccz(&acc_0);
+ __builtin_mma_xxsetaccz(&acc_1);
+ __builtin_mma_xxsetaccz(&acc_2);
+ __builtin_mma_xxsetaccz(&acc_3);
+ for (int l = 0; l < k; l+=8) {
+ packNormal(A+(ii*lda)+l, lda, 8, 8, (uint8_t*)vec_A);
+ packNormal(B+(jj*ldb)+l, ldb, 8, 8, (uint8_t*)vec_B);
+ for (int x = 0; x < 4; x++) {
+ mma_instr<TA>::outer_product(&acc_0, vec_A[x], vec_B[x]);
+ mma_instr<TA>::outer_product(&acc_1, vec_A[x], vec_B[x+4]);
+ mma_instr<TA>::outer_product(&acc_2, vec_A[x+4], vec_B[x]);
+ mma_instr<TA>::outer_product(&acc_3, vec_A[x+4], vec_B[x+4]);
+ }
+ }
+
+ SAVE_ACC(&acc_0, ii, jj);
+ SAVE_ACC(&acc_1, ii, jj+4);
+ SAVE_ACC(&acc_2, ii+4, jj);
+ SAVE_ACC(&acc_3, ii+4, jj+4);
+ }
+
+ template<int RM, int RN>
+ void gemm_small(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int64_t ytiles = (m - m0) / RM;
+ int64_t xtiles = (n - n0) / RN;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ if (end > tiles)
+ end = tiles;
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = m0 + job / xtiles * RM;
+ int64_t jj = n0 + job % xtiles * RN;
+ vec_t vec_C[4];
+ acc_t acc_0;
+ __builtin_mma_xxsetaccz(&acc_0);
+ vec_t vec_A[2], vec_B[2];
+ for (int l=0; l<k; l+=4) {
+ packNormal(A+(ii*lda)+l, lda, RM, 4, (uint8_t*)vec_A);
+ packNormal(B+(jj*ldb)+l, ldb, RN, 4, (uint8_t*)vec_B);
+ for (int x = 0; x<2; x++) {
+ mma_instr<TA>::outer_product(&acc_0, vec_A[x], vec_B[x]);
+ }
+ }
+ __builtin_mma_disassemble_acc(vec_C, &acc_0);
+ for (int I = 0; I < RM; I++) {
+ for (int J = 0; J < RN; J++) {
+ *((TC*)(C+ii+((jj+J)*ldc)+I)) = *((TC*)&vec_C[I]+J);
+ }
+ }
+ }
+ }
+
+ template<int RM>
+ void gemm_Mx8(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int RN = 8;
+ int64_t ytiles = (m - m0) / RM;
+ int64_t xtiles = (n - n0) / RN;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ if (end > tiles)
+ end = tiles;
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = m0 + job / xtiles * RM;
+ int64_t jj = n0 + job % xtiles * RN;
+ vec_t vec_C[4];
+ acc_t acc_0, acc_1;
+ __builtin_mma_xxsetaccz(&acc_0);
+ __builtin_mma_xxsetaccz(&acc_1);
+ vec_t vec_A[4], vec_B[8];
+ for (int l=0; l<k; l+=8) {
+ packNormal(A+(ii*lda)+l, lda, RM, 8, (uint8_t*)vec_A);
+ packNormal(B+(jj*ldb)+l, ldb, RN, 8, (uint8_t*)vec_B);
+ for (int x = 0; x<4; x++) {
+ mma_instr<TA>::outer_product(&acc_0, vec_A[x], vec_B[x]);
+ mma_instr<TA>::outer_product(&acc_1, vec_A[x], vec_B[x+4]);
+ }
+ }
+ __builtin_mma_disassemble_acc(vec_C, &acc_0);
+ for (int I = 0; I < RM; I++) {
+ for (int J = 0; J < 4; J++) {
+ *((TC*)(C+ii+((jj+J)*ldc)+I)) = *((TC*)&vec_C[I]+J);
+ }
+ }
+ __builtin_mma_disassemble_acc(vec_C, &acc_1);
+ for (int I = 0; I < RM; I++) {
+ for (int J = 0; J < 4; J++) {
+ *((TC*)(C+ii+((jj+4+J)*ldc)+I)) = *((TC*)&vec_C[I]+J);
+ }
+ }
+ }
+ }
+
+ template<int RM, int RN>
+ inline void kernel(int64_t ii, int64_t jj) {
+ if constexpr(RM == 4 && RN == 8) {
+ KERNEL_4x8(ii,jj);
+ } else if constexpr(RM == 8 && RN == 8) {
+ KERNEL_8x8(ii,jj);
+ } else if constexpr(RM == 8 && RN == 4) {
+ KERNEL_8x4(ii,jj);
+ } else {
+ assert(false && "RN/RM values not supported");
+ }
+ }
+
+ template <int RM, int RN>
+ NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int64_t ytiles = (m - m0) / RM;
+ int64_t xtiles = (n - n0) / RN;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ if (end > tiles)
+ end = tiles;
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = m0 + job / xtiles * RM;
+ int64_t jj = n0 + job % xtiles * RN;
+ kernel<RM, RN>(ii, jj);
+ }
+ }
+
+ const TA *const A;
+ const TB *const B;
+ TC *C;
+ const int64_t k;
+ const int64_t lda;
+ const int64_t ldb;
+ const int64_t ldc;
+ const int ith;
+ const int nth;
+};
+
+ template <typename TA>
+ tinyBLAS_Q0_PPC<TA>::tinyBLAS_Q0_PPC(int64_t k,
+ const TA *A, int64_t lda,
+ const block_q8_0 *B, int64_t ldb,
+ float *C, int64_t ldc,
+ int ith, int nth)
+ : A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
+ kc = 64;
+ }
+
+ template<typename TA>
+ void tinyBLAS_Q0_PPC<TA>::matmul(int64_t m, int64_t n) {
+ int mc = 64; int nc = 64;
+ if (n % 8 == 0 && n < nc) {
+ nc = n;
+ mc = 32 ;
+ kc = 32;
+ }
+ const bool is_aligned = ((m & (mc - 1)) == 0) & ((n & (nc - 1)) == 0) & ((k & (kc - 1)) == 0);
+ if (is_aligned) {
+ this->matmul_tiled_q0(m, n, mc, nc, kc);
+ } else {
+ mnpack(0, m, 0, n);
+ }
+ }
+
+ template<typename TA>
+ template<int size>
+ void tinyBLAS_Q0_PPC<TA>::packNormalInt4(const TA* a, int64_t lda, int rows, int cols, int8_t* vec, std::array<int, size>& comparray) {
+ int64_t i, j;
+ TA *aoffset = NULL;
+ int8_t *vecOffset = NULL;
+ TA *aoffset1 = NULL, *aoffset2 = NULL, *aoffset3 = NULL, *aoffset4 = NULL;
+ TA *aoffset5 = NULL, *aoffset6 = NULL, *aoffset7 = NULL, *aoffset8 = NULL;
+ vector signed char c1[2] = {0}, c2[2] = {0}, c3[2] = {0}, c4[2] = {0};
+ vector signed char c5[2] = {0}, c6[2] = {0}, c7[2] = {0}, c8[2] = {0};
+ aoffset = const_cast<TA*>(a);
+ vecOffset = vec;
+ j = (rows >> 3);
+ if (j > 0) {
+ do {
+ aoffset1 = aoffset;
+ aoffset2 = aoffset1 + lda;
+ aoffset3 = aoffset2 + lda;
+ aoffset4 = aoffset3 + lda;
+ aoffset5 = aoffset4 + lda;
+ aoffset6 = aoffset5 + lda;
+ aoffset7 = aoffset6 + lda;
+ aoffset8 = aoffset7 + lda;
+ aoffset += 8 * lda;
+ i = (cols >> 2);
+ if (i > 0) {
+ do {
+ c1[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset1->qs));
+ c2[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset2->qs));
+ c3[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset3->qs));
+ c4[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset4->qs));
+ c5[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset5->qs));
+ c6[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset6->qs));
+ c7[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset7->qs));
+ c8[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset8->qs));
+
+ process_q4_elements(c1, &comparray[0]);
+ process_q4_elements(c2, &comparray[1]);
+ process_q4_elements(c3, &comparray[2]);
+ process_q4_elements(c4, &comparray[3]);
+ process_q4_elements(c5, &comparray[4]);
+ process_q4_elements(c6, &comparray[5]);
+ process_q4_elements(c7, &comparray[6]);
+ process_q4_elements(c8, &comparray[7]);
+ vector_permute_store<int8_t, vector signed char>(c1[0], c2[0], c3[0], c4[0], vecOffset, false);
+ vector_permute_store<int8_t, vector signed char>(c1[1], c2[1], c3[1], c4[1], vecOffset+64, false);
+ vector_permute_store<int8_t, vector signed char>(c5[0], c6[0], c7[0], c8[0], vecOffset+128, false);
+ vector_permute_store<int8_t, vector signed char>(c5[1], c6[1], c7[1], c8[1], vecOffset+192, false);
+ aoffset1 += lda;
+ aoffset2 += lda;
+ aoffset3 += lda;
+ aoffset4 += lda;
+ aoffset5 += lda;
+ aoffset6 += lda;
+ aoffset7 += lda;
+ aoffset8 += lda;
+ vecOffset += 256;
+ i--;
+ } while (i > 0);
+ }
+ j--;
+ } while (j > 0);
+ }
+
+ if (rows & 4) {
+ aoffset1 = aoffset;
+ aoffset2 = aoffset1 + lda;
+ aoffset3 = aoffset2 + lda;
+ aoffset4 = aoffset3 + lda;
+ aoffset += 4 * lda;
+ i = (cols >> 2);
+ if (i > 0) {
+ do {
+ c1[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset1->qs));
+ c2[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset2->qs));
+ c3[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset3->qs));
+ c4[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset4->qs));
+
+ process_q4_elements(c1, &comparray[0]);
+ process_q4_elements(c2, &comparray[1]);
+ process_q4_elements(c3, &comparray[2]);
+ process_q4_elements(c4, &comparray[3]);
+ vector_permute_store<int8_t, vector signed char>(c1[0], c2[0], c3[0], c4[0], vecOffset, false);
+ vector_permute_store<int8_t, vector signed char>(c1[1], c2[1], c3[1], c4[1], vecOffset+64, false);
+ aoffset1 += lda;
+ aoffset2 += lda;
+ aoffset3 += lda;
+ aoffset4 += lda;
+ vecOffset += 128;
+ i--;
+ } while (i > 0);
+ }
+ }
+
+ if (rows & 3) {
+ aoffset1 = aoffset;
+ aoffset2 = aoffset1 + lda;
+ aoffset3 = aoffset2 + lda;
+ i = (cols >> 2);
+ if (i > 0) {
+ do {
+ switch(rows) {
+ case 3: c3[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset3->qs));
+ case 2: c2[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset2->qs));
+ case 1: c1[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset1->qs));
+ break;
+ }
+ process_q4_elements(c1, &comparray[0]);
+ process_q4_elements(c2, &comparray[1]);
+ process_q4_elements(c3, &comparray[2]);
+ process_q4_elements(c4, &comparray[3]);
+ vector_permute_store<int8_t, vector signed char>(c1[0], c2[0], c3[0], c4[0], vecOffset, false);
+ vector_permute_store<int8_t, vector signed char>(c1[1], c2[1], c3[1], c4[1], vecOffset+64, false);
+ aoffset1 += lda;
+ aoffset2 += lda;
+ aoffset3 += lda;
+ vecOffset += 128;
+ i--;
+ } while(i > 0);
+ }
+ }
+ }
+
+ template<typename TA>
+ template<typename VA, typename VB>
+ void tinyBLAS_Q0_PPC<TA>::packNormal(const block_q8_0* a, int64_t lda, int rows, int cols, VA* vec, bool flip) {
+ int64_t i, j;
+ block_q8_0 *aoffset = NULL;
+ VA *vecOffset = NULL;
+ block_q8_0* aoffsets[8];
+ __vector_pair arr[8];
+ VB c[8][2] = {0};
+ VB c1[8] = {0}; VB c2[8] = {0};
+ aoffset = const_cast<block_q8_0*>(a);
+ vecOffset = vec;
+ j = (rows >> 3);
+ if (j > 0) {
+ do {
+ aoffsets[0] = aoffset;
+ for (int it = 1; it < 8; it++)
+ aoffsets[it] = aoffsets[it-1] + lda;
+ aoffset += 8 * lda;
+
+ i = (cols >> 3);
+ if (i > 0) {
+ do {
+ for (int it = 0; it < 8; it++) {
+ arr[it] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[it]->qs);
+ __builtin_vsx_disassemble_pair(c[it], &arr[it]);
+ c1[it] = c[it][0];
+ c2[it] = c[it][1];
+ }
+ vector_permute_store<VA, VB>(c1[0], c1[1], c1[2], c1[3], vecOffset, flip);
+ vector_permute_store<VA, VB>(c2[0], c2[1], c2[2], c2[3], vecOffset+64, flip);
+ vector_permute_store<VA, VB>(c1[4], c1[5], c1[6], c1[7], vecOffset+128, flip);
+ vector_permute_store<VA, VB>(c2[4], c2[5], c2[6], c2[7], vecOffset+192, flip);
+ for (int it = 0; it < 8; it++)
+ aoffsets[it] += lda;
+ vecOffset += 256;
+ i--;
+ } while(i > 0);
+ }
+ j--;
+ } while(j > 0);
+ }
+ if (rows & 4) {
+ aoffsets[0] = aoffset;
+ for (int it = 1; it < 4; it++ )
+ aoffsets[it] = aoffsets[it-1] + lda;
+ aoffset += 4 * lda;
+ i = (cols >> 3);
+ if (i > 0) {
+ do {
+ for (int it = 0; it < 4; it++) {
+ arr[it] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[it]->qs);
+ __builtin_vsx_disassemble_pair(c[it], &arr[it]);
+ c1[it] = c[it][0];
+ c2[it] = c[it][1];
+ }
+ vector_permute_store<VA, VB>(c1[0], c1[1], c1[2], c1[3], vecOffset, flip);
+ vector_permute_store<VA, VB>(c2[0], c2[1], c2[2], c2[3], vecOffset+64, flip);
+ for (int it = 0; it < 4; it++) {
+ aoffsets[it] += lda;
+ }
+ vecOffset += 128;
+ i--;
+ } while(i > 0);
+ }
+ }
+
+ if (rows & 3) {
+ aoffsets[0] = aoffset;
+ for (int it = 1; it < 3; it++ )
+ aoffsets[it] = aoffsets[it-1] + lda;
+ i = (cols >> 3);
+ if (i > 0) {
+ do {
+ switch(rows) {
+ case 3: arr[2] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[2]->qs);
+ __builtin_vsx_disassemble_pair(c[2], &arr[2]);
+ c1[2] = c[2][0]; c2[2] = c[2][1];
+ case 2: arr[1] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[1]->qs);
+ __builtin_vsx_disassemble_pair(c[1], &arr[1]);
+ c1[1] = c[1][0]; c2[1] = c[1][1];
+ case 1: arr[0] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[0]->qs);
+ __builtin_vsx_disassemble_pair(c[0], &arr[0]);
+ c1[0] = c[0][0]; c2[0] = c[0][1];
+ break;
+ }
+ vector_permute_store<VA, VB>(c1[0], c1[1], c1[2], c1[3], vecOffset, flip);
+ vector_permute_store<VA, VB>(c2[0], c2[1], c2[2], c2[3], vecOffset+64, flip);
+ for (int it = 0; it < 3; it++)
+ aoffsets[it] += lda;
+ vecOffset += 128;
+ i--;
+ } while(i > 0);
+ }
+ }
+ }
+
+ template<typename TA>
+ void tinyBLAS_Q0_PPC<TA>::mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int m_rem = MIN(m - m0, 16);
+ int n_rem = MIN(n - n0, 16);
+
+ int mc = 0, nc = 0;
+
+ if (m_rem >= 8 && n_rem >= 8) {
+ mc = 8;
+ nc = 8;
+ gemm<8, 8>(m0, m, n0, n);
+ } else if (m_rem >= 4 && n_rem >= 8) {
+ mc = 4;
+ nc = 8;
+ gemm<4, 8>(m0, m, n0, n);
+ } else if (m_rem >= 8 && n_rem >= 4) {
+ mc = 8;
+ nc = 4;
+ gemm<8, 4>(m0, m, n0, n);
+ } else if (m_rem >= 4 && n_rem >= 4) {
+ mc = 4;
+ nc = 4;
+ gemm_small(m0, m, n0, n, mc, nc);
+ } else {
+ mc = (m_rem >= 4) ? 4 : m_rem;
+ nc = (n_rem >= 4) ? 4 : n_rem;
+ if (mc == 0 || nc == 0)
+ return;
+ gemm_small(m0, m, n0, n, mc, nc);
+ }
+
+ int64_t mp = m0 + ((m - m0) / mc) * mc;
+ int64_t np = n0 + ((n - n0) / nc) * nc;
+ mnpack(mp, m, n0, np);
+ mnpack(m0, m, np, n);
+ }
+
+
+ template<typename TA>
+ void tinyBLAS_Q0_PPC<TA>::KERNEL_4x8(int64_t ii, int64_t jj) {
+ vec_t vec_A[8], vec_B[16] = {0};
+ acc_t acc_0, acc_1;
+ std::array<int, 4> comparray {};
+ vector float fin_res[8] = {0};
+ vector float vs[8] = {0};
+ bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
+ for (int l = 0; l < k; l++) {
+ __builtin_mma_xxsetaccz(&acc_0);
+ __builtin_mma_xxsetaccz(&acc_1);
+ if (std::is_same_v<TA, block_q4_0>) {
+ packNormalInt4<4>((A+(ii*lda)+l), lda, 4, 4, (int8_t*)vec_A, comparray);
+ } else {
+ packNormal<int8_t, vector signed char>((const block_q8_0*)(A+(ii*lda)+l), lda, 4, 8, (int8_t*)vec_A, false);
+ }
+ packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, 8, 8, (uint8_t*)vec_B, true);
+ for(int x = 0; x < 8; x++) {
+ __builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
+ __builtin_mma_xvi8ger4pp(&acc_1, vec_A[x], vec_B[x+8]);
+ }
+ for (int I = 0; I<4; I++) {
+ for (int J = 0; J<4; J++) {
+ *((float*)&vs[I]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J)*ldb)+l)->d));
+ *((float*)&vs[I+4]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J+4)*ldb)+l)->d));
+ }
+ }
+ if (!isAblock_q4) {
+ auto aoffset = A+(ii*lda)+l;
+ for (int i = 0; i < 4; i++) {
+ comparray[i] = 0;
+ int ca = 0;
+ auto *at = aoffset->qs;
+ for (int j = 0; j < 32; j++)
+ ca += (int)*at++;
+ comparray[i] = ca;
+ aoffset += lda;
+ }
+ }
+ compute(&acc_0, 0, 0, comparray, vs, fin_res);
+ compute(&acc_1, 0, 4, comparray, vs, fin_res);
+ }
+ save_res(ii, jj, 0, fin_res);
+ save_res(ii, jj+4, 4, fin_res);
+ }
+
+ template<typename TA>
+ void tinyBLAS_Q0_PPC<TA>::KERNEL_8x4(int64_t ii, int64_t jj) {
+ vec_t vec_A[16], vec_B[8] = {0};
+ acc_t acc_0, acc_1;
+ std::array<int, 8> comparray {};
+ vector float fin_res[8] = {0};
+ vector float vs[8] = {0};
+ bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
+ for (int l = 0; l < k; l++) {
+ __builtin_mma_xxsetaccz(&acc_0);
+ __builtin_mma_xxsetaccz(&acc_1);
+ if (std::is_same_v<TA, block_q4_0>) {
+ packNormalInt4<8>((A+(ii*lda)+l), lda, 8, 4, (int8_t*)vec_A, comparray);
+ } else {
+ packNormal<int8_t, vector signed char>((const block_q8_0*)(A+(ii*lda)+l), lda, 8, 8, (int8_t*)vec_A, false);
+ }
+ packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, 4, 8, (uint8_t*)vec_B, true);
+ for(int x = 0; x < 8; x++) {
+ __builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
+ __builtin_mma_xvi8ger4pp(&acc_1, vec_A[x+8], vec_B[x]);
+ }
+ for (int I = 0; I<8; I++) {
+ for (int J = 0; J<4; J++) {
+ *((float*)&vs[I]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J)*ldb)+l)->d));
+ }
+ }
+ if (!isAblock_q4) {
+ auto aoffset = A+(ii*lda)+l;
+ for (int i = 0; i < 8; i++) {
+ comparray[i] = 0;
+ int ca = 0;
+ auto *at = aoffset->qs;
+ for (int j = 0; j < 32; j++)
+ ca += (int)*at++;
+ comparray[i] = ca;
+ aoffset += lda;
+ }
+ }
+ compute(&acc_0, 0, 0, comparray, vs, fin_res);
+ compute(&acc_1, 4, 4, comparray, vs, fin_res);
+ }
+ save_res(ii, jj, 0, fin_res);
+ save_res(ii+4, jj, 4, fin_res);
+ }
+
+ template<typename TA>
+ void tinyBLAS_Q0_PPC<TA>::KERNEL_8x8(int64_t ii, int64_t jj) {
+ vec_t vec_A[16], vec_B[16] = {0};
+ acc_t acc_0, acc_1, acc_2, acc_3;
+ acc_t acc_4, acc_5, acc_6, acc_7;
+ std::array<int, 8> comparray {};
+ vector float fin_res[16] = {0};
+ vector float vs[16] = {0};
+ bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
+ for (int l = 0; l < k; l++) {
+ __builtin_mma_xxsetaccz(&acc_0);
+ __builtin_mma_xxsetaccz(&acc_1);
+ __builtin_mma_xxsetaccz(&acc_2);
+ __builtin_mma_xxsetaccz(&acc_3);
+ if (std::is_same_v<TA, block_q4_0>) {
+ packNormalInt4<8>((A+(ii*lda)+l), lda, 8, 4, (int8_t*)vec_A, comparray);
+ } else {
+ packNormal<int8_t, vector signed char>((const block_q8_0*)(A+(ii*lda)+l), lda, 8, 8, (int8_t*)vec_A, false);
+ }
+ packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, 8, 8, (uint8_t*)vec_B, true);
+ for(int x = 0; x < 8; x++) {
+ __builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
+ __builtin_mma_xvi8ger4pp(&acc_1, vec_A[x+8], vec_B[x]);
+ __builtin_mma_xvi8ger4pp(&acc_2, vec_A[x], vec_B[x+8]);
+ __builtin_mma_xvi8ger4pp(&acc_3, vec_A[x+8], vec_B[x+8]);
+ }
+ for (int I = 0; I<8; I++) {
+ for (int J = 0; J<4; J++) {
+ *((float*)&vs[I]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J)*ldb)+l)->d));
+ *((float*)&vs[I+8]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J+4)*ldb)+l)->d));
+ }
+ }
+ if (!isAblock_q4) {
+ auto aoffset = A+(ii*lda)+l;
+ for (int i = 0; i < 8; i++) {
+ comparray[i] = 0;
+ int ca = 0;
+ auto *at = aoffset->qs;
+ for (int j = 0; j < 32; j++)
+ ca += (int)*at++;
+ comparray[i] = ca;
+ aoffset += lda;
+ }
+ }
+ compute(&acc_0, 0, 0, comparray, vs, fin_res);
+ compute(&acc_1, 4, 4, comparray, vs, fin_res);
+ compute(&acc_2, 0, 8, comparray, vs, fin_res);
+ compute(&acc_3, 4, 12, comparray, vs, fin_res);
+ }
+ save_res(ii, jj, 0, fin_res);
+ save_res(ii+4, jj, 4, fin_res);
+ save_res(ii, jj+4, 8, fin_res);
+ save_res(ii+4, jj+4, 12, fin_res);
+ }
+
+ template<typename TA>
+ void tinyBLAS_Q0_PPC<TA>::gemm_small(int64_t m0, int64_t m, int64_t n0, int64_t n, int RM, int RN) {
+ int64_t ytiles = (m - m0) / RM;
+ int64_t xtiles = (n - n0) / RN;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ vec_t vec_A[8] = {0}, vec_B[8] = {0};
+ vector signed int vec_C[4];
+ acc_t acc_0;
+ bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
+
+ if (end > tiles)
+ end = tiles;
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = m0 + job / xtiles * RM;
+ int64_t jj = n0 + job % xtiles * RN;
+ std::array<int, 4> comparray{};
+ vector float res[4] = {0};
+ vector float fin_res[4] = {0};
+ vector float vs[4] = {0};
+ vector float CA[4] = {0};
+ __builtin_prefetch((A+(ii*lda)+0)->qs, 0, 1); // prefetch first value
+ __builtin_prefetch((B+(jj*ldb)+0)->qs, 0, 1); // prefetch first value
+ for (int l = 0; l < k; l++) {
+ __builtin_prefetch((A+(ii*lda)+(l+1))->qs, 0, 1); // prefetch one loop ahead
+ __builtin_prefetch((B+(jj*ldb)+(l+1))->qs, 0, 1); // prefetch one loop ahead
+ __builtin_mma_xxsetaccz(&acc_0);
+ if (isAblock_q4) {
+ packNormalInt4<4>((A+(ii*lda)+l), lda, RM, 4, (int8_t*)vec_A, comparray);
+ } else {
+ packNormal<int8_t, vector signed char>((const block_q8_0*)(A+(ii*lda)+l), lda, RM, 8, (int8_t*)vec_A, false);
+ }
+ packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, RN, 8, (uint8_t*)vec_B, true);
+ for(int x = 0; x < 8; x+=4) {
+ __builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
+ __builtin_mma_xvi8ger4pp(&acc_0, vec_A[x+1], vec_B[x+1]);
+ __builtin_mma_xvi8ger4pp(&acc_0, vec_A[x+2], vec_B[x+2]);
+ __builtin_mma_xvi8ger4pp(&acc_0, vec_A[x+3], vec_B[x+3]);
+ }
+ for (int I = 0; I<RM; I++) {
+ for (int J = 0; J<RN; J++) {
+ *((float*)&vs[I]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J)*ldb)+l)->d));
+ }
+ }
+ __builtin_mma_disassemble_acc(vec_C, &acc_0);
+ if (!isAblock_q4) {
+ auto aoffset = A+(ii*lda)+l;
+ for (int i = 0; i < RM; i++) {
+ comparray[i] = 0;
+ int ca = 0;
+ auto *at = aoffset->qs;
+ for (int j = 0; j < 32; j++)
+ ca += (int)*at++;
+ comparray[i] = ca;
+ aoffset += lda;
+ }
+ }
+ for (int i = 0; i < RM; i++) {
+ CA[i] = vec_splats((float)(((double)comparray[i]) * -128.0));
+ res[i] = vec_add(vec_ctf(vec_C[i], 0), CA[i]);
+ fin_res[i] = vec_madd(res[i], vs[i], fin_res[i]);
+ }
+ }
+ save_res(ii, jj, 0, fin_res, RM, RN);
+ }
+ }
+
+ template<typename TA>
+ template <int RM, int RN>
+ NOINLINE void tinyBLAS_Q0_PPC<TA>::gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int64_t ytiles = (m - m0) / RM;
+ int64_t xtiles = (n - n0) / RN;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ if (end > tiles)
+ end = tiles;
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = m0 + job / xtiles * RM;
+ int64_t jj = n0 + job % xtiles * RN;
+ this->kernel<RM, RN>(ii, jj);
+ }
+ }
+
+template class tinyBLAS_Q0_PPC<block_q4_0>;
+template class tinyBLAS_Q0_PPC<block_q8_0>;
+
+class tinyBLAS_PPC {
+ public:
+ tinyBLAS_PPC(int64_t k,
+ const float * A, int64_t lda,
+ const float * B, int64_t ldb,
+ float * C, int64_t ldc,
+ int ith, int nth)
+ : A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
+ }
+
+ void matmul(int64_t m, int64_t n) {
+ int64_t mc = 256; int64_t nc = 256; int64_t kc = 256;
+ if (m % mc == 0 && n % nc == 0 && k % kc == 0) {
+ matmul_tiled(m, n, mc, nc, kc);
+ } else {
+ mnpack(0, m, 0, n);
+ }
+ }
+
+ private:
+
+ inline void save_acc(acc_t * ACC, int64_t ii, int64_t jj) {
+ vec_t vec_C[4];
+ __builtin_mma_disassemble_acc(vec_C, ACC);
+ for (int I = 0; I < 4; I++) {
+ for (int J = 0; J < 4; J++) {
+ *((float *)(C+ii+((jj+J)*ldc)+I)) = *((float *)&vec_C[I]+J);
+ }
+ }
+ }
+
+ inline void add_save_acc(acc_t * ACC, int64_t ii, int64_t jj) {
+ vec_t vec_C[4];
+ __builtin_mma_disassemble_acc(vec_C, ACC);
+ for (int I = 0; I < 4; I++) {
+ for (int J = 0; J < 4; J++) {
+ float * c_ptr = (float *)(C+ii+((jj+J)*ldc)+I);
+ *c_ptr += *((float *)&vec_C[I]+J);
+ }
+ }
+ }
+
+ inline void vector_permute_store_4(vector float * src, float * vecOffset) {
+ vector float t1, t2, t3, t4, t5, t6, t7, t8;
+ t1 = vec_mergeh(src[0], src[1]);
+ t2 = vec_mergeh(src[2], src[3]);
+ t3 = vec_mergel(src[0], src[1]);
+ t4 = vec_mergel(src[2], src[3]);
+
+ t5 = vec_xxpermdi(t1, t2, 0);
+ t6 = vec_xxpermdi(t1, t2, 3);
+ t7 = vec_xxpermdi(t3, t4, 0);
+ t8 = vec_xxpermdi(t3, t4, 3);
+
+ vec_xst(t5, 0, vecOffset);
+ vec_xst(t6, 0, vecOffset + 4);
+ vec_xst(t7, 0, vecOffset + 8);
+ vec_xst(t8, 0, vecOffset + 12);
+ }
+
+ inline void vector_permute_store_8(vector float * src, float * vecOffset) {
+ vector float t1, t2, t3, t4, t5, t6, t7, t8;
+ t1 = vec_mergeh(src[0], src[1]);
+ t2 = vec_mergeh(src[2], src[3]);
+ t3 = vec_mergeh(src[4], src[5]);
+ t4 = vec_mergeh(src[6], src[7]);
+
+ t5 = vec_xxpermdi(t1, t2, 0);
+ t6 = vec_xxpermdi(t3, t4, 0);
+ t7 = vec_xxpermdi(t1, t2, 3);
+ t8 = vec_xxpermdi(t3, t4, 3);
+
+ vec_xst(t5, 0, vecOffset);
+ vec_xst(t6, 0, vecOffset + 4);
+ vec_xst(t7, 0, vecOffset + 8);
+ vec_xst(t8, 0, vecOffset + 12);
+
+ t1 = vec_mergel(src[0], src[1]);
+ t2 = vec_mergel(src[2], src[3]);
+ t3 = vec_mergel(src[4], src[5]);
+ t4 = vec_mergel(src[6], src[7]);
+
+ t5 = vec_xxpermdi(t1, t2, 0);
+ t6 = vec_xxpermdi(t3, t4, 0);
+ t7 = vec_xxpermdi(t1, t2, 3);
+ t8 = vec_xxpermdi(t3, t4, 3);
+
+ vec_xst(t5, 0, vecOffset + 16);
+ vec_xst(t6, 0, vecOffset + 20);
+ vec_xst(t7, 0, vecOffset + 24);
+ vec_xst(t8, 0, vecOffset + 28);
+ }
+
+ void packTranspose(const float * a, int64_t lda, int rows, int cols, float * vec) {
+ int64_t i, j;
+ float * aoffsets[8];
+ float * aoffset = NULL, * boffset = NULL;
+ __vector_pair arr[8];
+ vector float c[8][2] = {0};
+ vector float c1[8] = {0};
+ vector float c2[8] = {0};
+ aoffset = const_cast<float *>(a);
+ boffset = vec;
+ j = (rows >> 3);
+ if (j > 0) {
+ do {
+ aoffsets[0] = aoffset;
+ for (int it = 1; it < 8; it++)
+ aoffsets[it] = aoffsets[it-1] + lda;
+ aoffset += 8 * lda;
+ i = (cols >> 3);
+ if (i > 0) {
+ do {
+ for (int it = 0; it < 8; it++) {
+ arr[it] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[it]);
+ __builtin_vsx_disassemble_pair(c[it], &arr[it]);
+ c1[it] = c[it][0];
+ c2[it] = c[it][1];
+ }
+
+ vector_permute_store_8(c1, boffset);
+ vector_permute_store_8(c2, boffset + 32);
+ boffset += 64;
+ i--;
+ if (i > 0) {
+ for (int it = 0; it < 8; it++) {
+ aoffsets[it] = aoffsets[it] + 8;
+ }
+ }
+ } while(i > 0);
+ }
+ if (cols & 4) {
+ for (int it = 0; it < 8 ; it++)
+ c1[it] = vec_xl(0, aoffsets[it]);
+ vector_permute_store_8(c1, boffset);
+ }
+ j--;
+ } while(j > 0);
+ }
+
+ if (rows & 4) {
+ aoffsets[0] = aoffset;
+ for (int it = 1; it < 4; it++)
+ aoffsets[it] = aoffsets[it-1] + lda;
+ aoffset += 4 * lda;
+ i = (cols >> 3);
+ if (i > 0) {
+ do {
+ for (int it = 0; it < 4; it++) {
+ arr[it] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[it]);
+ __builtin_vsx_disassemble_pair(c[it], &arr[it]);
+ c1[it] = c[it][0];
+ c2[it] = c[it][1];
+ }
+ vector_permute_store_4(c1, boffset);
+ vector_permute_store_4(c2, boffset + 16);
+ for (int it = 0; it < 4; it++)
+ aoffsets[it] += 8 * lda;
+ boffset += 32;
+ i--;
+ } while(i > 0);
+ }
+
+ if (cols & 4) {
+ for (int it = 0; it < 4; it++)
+ c1[it] = vec_xl(0, aoffsets[it]);
+ vector_permute_store_4(c1, boffset);
+ }
+ }
+ if (rows & 3) {
+ aoffsets[0] = aoffset;
+ for (int it = 1; it < 3; it++)
+ aoffsets[it] = aoffsets[it-1] + lda;
+ if (cols & 4) {
+ for (int it = 0; it < 3; it++)
+ c1[it] = vec_xl(0, aoffsets[it]);
+ vector_permute_store_4(c1, boffset);
+ }
+ }
+ }
+
+ void KERNEL_4x4(int64_t ii, int64_t jj) {
+ vec_t vec_A[4], vec_B[4], vec_C[4];
+ acc_t acc_0;
+ __builtin_mma_xxsetaccz(&acc_0);
+ for (int l = 0; l < k; l += 4) {
+ packTranspose(A + (ii * lda) + l, lda, 4, 4, (float *)vec_A);
+ packTranspose(B + (jj * ldb) + l, ldb, 4, 4, (float *)vec_B);
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[0], vec_B[0]);
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[1], vec_B[1]);
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[2], vec_B[2]);
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[3], vec_B[3]);
+ }
+ save_acc(&acc_0, ii, jj);
+ }
+
+ void KERNEL_4x8(int64_t ii, int64_t jj) {
+ vec_t vec_A[4], vec_B[8], vec_C[4];
+ acc_t acc_0, acc_1;
+ __builtin_mma_xxsetaccz(&acc_0);
+ __builtin_mma_xxsetaccz(&acc_1);
+ for (int64_t l = 0; l < k; l += 4) {
+ packTranspose(A + (ii * lda) + l, lda, 4, 4, (float *)vec_A);
+ packTranspose(B + (jj * ldb) + l, ldb, 8, 4, (float *)vec_B);
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[0], (vec_t)vec_B[0]);
+ __builtin_mma_xvf32gerpp(&acc_1, vec_A[0], (vec_t)vec_B[1]);
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[1], (vec_t)vec_B[2]);
+ __builtin_mma_xvf32gerpp(&acc_1, vec_A[1], (vec_t)vec_B[3]);
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[2], (vec_t)vec_B[4]);
+ __builtin_mma_xvf32gerpp(&acc_1, vec_A[2], (vec_t)vec_B[5]);
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[3], (vec_t)vec_B[6]);
+ __builtin_mma_xvf32gerpp(&acc_1, vec_A[3], (vec_t)vec_B[7]);
+ }
+ save_acc(&acc_0, ii, jj);
+ save_acc(&acc_1, ii, jj + 4);
+ }
+
+ void KERNEL_8x4(int64_t ii, int64_t jj) {
+ vec_t vec_A[8], vec_B[4], vec_C[4];
+ acc_t acc_0, acc_1;
+ __builtin_mma_xxsetaccz(&acc_0);
+ __builtin_mma_xxsetaccz(&acc_1);
+ for (int64_t l = 0; l < k; l += 4) {
+ packTranspose(A + (ii * lda) + l, lda, 8, 4, (float *)vec_A);
+ packTranspose(B + (jj * ldb) + l, ldb, 4, 4, (float *)vec_B);
+ __builtin_mma_xvf32gerpp(&acc_0, (vec_t)vec_A[0], vec_B[0]);
+ __builtin_mma_xvf32gerpp(&acc_1, (vec_t)vec_A[1], vec_B[0]);
+ __builtin_mma_xvf32gerpp(&acc_0, (vec_t)vec_A[2], vec_B[1]);
+ __builtin_mma_xvf32gerpp(&acc_1, (vec_t)vec_A[3], vec_B[1]);
+ __builtin_mma_xvf32gerpp(&acc_0, (vec_t)vec_A[4], vec_B[2]);
+ __builtin_mma_xvf32gerpp(&acc_1, (vec_t)vec_A[5], vec_B[2]);
+ __builtin_mma_xvf32gerpp(&acc_0, (vec_t)vec_A[6], vec_B[3]);
+ __builtin_mma_xvf32gerpp(&acc_1, (vec_t)vec_A[7], vec_B[3]);
+ }
+ save_acc(&acc_0, ii, jj);
+ save_acc(&acc_1, ii + 4, jj);
+ }
+
+ void KERNEL_8x8(int64_t ii, int64_t jj) {
+ vec_t vec_A[16], vec_B[16], vec_C[4];
+ acc_t acc_0, acc_1, acc_2, acc_3;
+ __builtin_mma_xxsetaccz(&acc_0);
+ __builtin_mma_xxsetaccz(&acc_1);
+ __builtin_mma_xxsetaccz(&acc_2);
+ __builtin_mma_xxsetaccz(&acc_3);
+ for (int l = 0; l < k; l+=8) {
+ packTranspose(A + (ii * lda) + l, lda, 8, 8, (float *)vec_A);
+ packTranspose(B + (jj * ldb) + l, ldb, 8, 8, (float *)vec_B);
+ for(int x = 0; x < 16; x+=2) {
+ __builtin_mma_xvf32gerpp(&acc_0, (vec_t)vec_A[x], vec_B[x]);
+ __builtin_mma_xvf32gerpp(&acc_1, (vec_t)vec_A[x], vec_B[x + 1]);
+ __builtin_mma_xvf32gerpp(&acc_2, (vec_t)vec_A[x + 1], vec_B[x]);
+ __builtin_mma_xvf32gerpp(&acc_3, (vec_t)vec_A[x + 1], vec_B[x + 1]);
+ }
+ }
+ save_acc(&acc_0, ii, jj);
+ save_acc(&acc_1, ii, jj + 4);
+ save_acc(&acc_2, ii + 4, jj);
+ save_acc(&acc_3, ii + 4, jj + 4);
+ }
+
+ inline void MMA_16x8(vec_t * vec_A0, vec_t * vec_A1, vec_t * vec_B, acc_t * acc) {
+ for (int x = 0; x < 16; x += 2) {
+ __builtin_mma_xvf32gerpp(&acc[0], vec_A0[x + 0], vec_B[x]);
+ __builtin_mma_xvf32gerpp(&acc[1], vec_A0[x + 0], vec_B[x + 1]);
+ __builtin_mma_xvf32gerpp(&acc[2], vec_A0[x + 1], vec_B[x]);
+ __builtin_mma_xvf32gerpp(&acc[3], vec_A0[x + 1], vec_B[x + 1]);
+ __builtin_mma_xvf32gerpp(&acc[4], vec_A1[x + 0], vec_B[x]);
+ __builtin_mma_xvf32gerpp(&acc[5], vec_A1[x + 0], vec_B[x + 1]);
+ __builtin_mma_xvf32gerpp(&acc[6], vec_A1[x + 1], vec_B[x]);
+ __builtin_mma_xvf32gerpp(&acc[7], vec_A1[x + 1], vec_B[x + 1]);
+ }
+ }
+
+ void KERNEL(int64_t ii, int64_t jj, int64_t mc, int64_t nc, int64_t kc, vec_t * vec_A, vec_t * vec_B, int64_t kk) {
+ for (int64_t i = 0; i < mc; i += 16) {
+ int A_base_addr = (mc / 8) * (i / 8) * 16;
+ for (int64_t j = 0; j < nc; j += 8) {
+ int B_base_addr = (nc / 8) * (j / 8) * 16;
+ acc_t acc[8];
+ vec_t A0_block[16]; vec_t A1_block[16];
+ for (int x = 0; x < 8; x++)
+ __builtin_mma_xxsetaccz(&acc[x]);
+ for (int64_t l = 0; l < kc; l += 8) {
+ int A0_block_idx = A_base_addr + (l / 8) * 16;
+ int A1_block_idx = A0_block_idx + (mc / 8) * 16;
+ int B_block_idx = B_base_addr + (l / 8) * 16;
+ vec_t* A0_block = &vec_A[A0_block_idx];
+ vec_t* A1_block = &vec_A[A1_block_idx];
+ vec_t* B_block = &vec_B[B_block_idx];
+ MMA_16x8(A0_block, A1_block, B_block, acc);
+ }
+ if (kk == 0) {
+ save_acc(&acc[0], ii + i, jj + j);
+ save_acc(&acc[1], ii + i, jj + j + 4);
+ save_acc(&acc[2], ii + i + 4, jj + j);
+ save_acc(&acc[3], ii + i + 4, jj + j + 4);
+ save_acc(&acc[4], ii + i + 8, jj + j);
+ save_acc(&acc[5], ii + i + 8, jj + j + 4);
+ save_acc(&acc[6], ii + i + 12, jj + j);
+ save_acc(&acc[7], ii + i + 12, jj + j + 4);
+ } else {
+ add_save_acc(&acc[0], ii + i, jj + j);
+ add_save_acc(&acc[1], ii + i, jj + j + 4);
+ add_save_acc(&acc[2], ii + i + 4, jj + j);
+ add_save_acc(&acc[3], ii + i + 4, jj + j + 4);
+ add_save_acc(&acc[4], ii + i + 8, jj + j);
+ add_save_acc(&acc[5], ii + i + 8, jj + j + 4);
+ add_save_acc(&acc[6], ii + i + 12, jj + j);
+ add_save_acc(&acc[7], ii + i + 12, jj + j + 4);
+ }
+ }
+ }
+ }
+
+ void matmul_tiled(int64_t m , int64_t n, int64_t mc, int64_t nc, int64_t kc) {
+ int64_t ytiles = m / mc;
+ int64_t xtiles = n / nc;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ if (end > tiles) {
+ end = tiles;
+ }
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = (job / xtiles) * mc;
+ int64_t jj = (job % xtiles) * nc;
+ for (int64_t kk = 0; kk < k; kk += kc) {
+ vec_t A_pack[kc * mc / 4];
+ vec_t B_pack[kc * nc / 4];
+ packTranspose(A + (ii * lda) + kk, lda, kc, mc, (float *)A_pack);
+ packTranspose(B + (jj * ldb) + kk, ldb, kc, nc, (float *)B_pack);
+ KERNEL(ii, jj, mc, nc, kc, A_pack, B_pack, kk);
+ }
+ }
+ }
+
+ void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int m_rem = MIN(m - m0, 8);
+ int n_rem = MIN(n - n0, 8);
+ int mc = 0, nc = 0;
+ if (m_rem >= 8 && n_rem >= 8) {
+ mc = 8;
+ nc = 8;
+ gemm<8, 8>(m0, m, n0, n);
+ } else if (m_rem >= 4 && n_rem >= 8) {
+ mc = 4;
+ nc = 8;
+ gemm<4, 8>(m0, m, n0, n);
+ } else if (m_rem >= 8 && n_rem >= 4) {
+ mc = 8;
+ nc = 4;
+ gemm<8, 4>(m0, m, n0, n);
+ } else if (m_rem >= 4 && n_rem >= 4) {
+ mc = 4;
+ nc = 4;
+ gemm<4, 4>(m0, m, n0, n);
+ } else {
+ mc = (m_rem >= 4) ? 4 : m_rem;
+ nc = (n_rem >= 4) ? 4 : n_rem;
+ if (mc == 0 || nc == 0)
+ return;
+ gemm_small(m0, m, n0, n, mc, nc);
+ }
+ int64_t mp = m0 + ((m - m0) / mc) * mc;
+ int64_t np = n0 + ((n - n0) / nc) * nc;
+ mnpack(mp, m, n0, np);
+ mnpack(m0, m, np, n);
+ }
+
+ void gemm_small(int64_t m0, int64_t m, int64_t n0, int64_t n, int RM, int RN) {
+ int64_t ytiles = (m - m0) / RM;
+ int64_t xtiles = (n - n0) / RN;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ if (end > tiles)
+ end = tiles;
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = m0 + job / xtiles * RM;
+ int64_t jj = n0 + job % xtiles * RN;
+ vec_t vec_C[4];
+ acc_t acc_0;
+ __builtin_mma_xxsetaccz(&acc_0);
+ vec_t vec_A[4] = {0}, vec_B[4] = {0};
+ for (int l = 0; l < k; l += 4) {
+ /* 'GEMV Forwarding' concept is used in first two conditional loops.
+ * when one of the matrix has a single row/column, the elements are
+ * broadcasted, instead of using packing routine to prepack the
+ * matrix elements.
+ */
+ if (RM == 1) {
+ float * a = const_cast<float *>(A + (ii) * lda + l);
+ packTranspose(B + (jj * ldb) + l, ldb, RN, 4, (float *)vec_B);
+ vec_A[0] = (vec_t)vec_xl(0,a);
+ vec_A[1] = (vec_t)vec_splats(*((float *)&vec_A+1));
+ vec_A[2] = (vec_t)vec_splats(*((float *)&vec_A+2));
+ vec_A[3] = (vec_t)vec_splats(*((float *)&vec_A+3));
+ } else if (RN == 1) {
+ packTranspose(A + (ii * lda) + l, lda, RM, 4, (float *)vec_A);
+ float * b = const_cast<float *>(B + (jj) * ldb + l);
+ vec_B[0] = (vec_t)vec_xl(0,b);
+ vec_B[1] = (vec_t)vec_splats(*((float *)&vec_B+1));
+ vec_B[2] = (vec_t)vec_splats(*((float *)&vec_B+2));
+ vec_B[3] = (vec_t)vec_splats(*((float *)&vec_B+3));
+ } else {
+ packTranspose(A + (ii * lda) + l, lda, RM, 4, (float *)vec_A);
+ packTranspose(B + (jj * ldb) + l, ldb, RN, 4, (float *)vec_B);
+ }
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[0], vec_B[0]);
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[1], vec_B[1]);
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[2], vec_B[2]);
+ __builtin_mma_xvf32gerpp(&acc_0, vec_A[3], vec_B[3]);
+ }
+ __builtin_mma_disassemble_acc(vec_C, &acc_0);
+ for (int I = 0; I < RM; I++) {
+ for (int J = 0; J < RN; J++) {
+ *((float *)(C+ii+((jj+J)*ldc)+I)) = *((float *)&vec_C[I]+J);
+ }
+ }
+ }
+ }
+
+ template<int RM, int RN>
+ inline void kernel(int64_t ii, int64_t jj) {
+ if constexpr(RM == 4 && RN == 4) {
+ KERNEL_4x4(ii, jj);
+ } else if constexpr(RM == 4 && RN == 8) {
+ KERNEL_4x8(ii, jj);
+ } else if constexpr(RM == 8 && RN == 4) {
+ KERNEL_8x4(ii, jj);
+ } else if constexpr(RM == 8 && RN == 8) {
+ KERNEL_8x8(ii, jj);
+ } else {
+ static_assert(false, "RN/RM values not supported");
+ }
+ }
+
+ template <int RM, int RN>
+ NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
+ int64_t ytiles = (m - m0) / RM;
+ int64_t xtiles = (n - n0) / RN;
+ int64_t tiles = xtiles * ytiles;
+ int64_t duty = (tiles + nth - 1) / nth;
+ int64_t start = duty * ith;
+ int64_t end = start + duty;
+ if (end > tiles)
+ end = tiles;
+ for (int64_t job = start; job < end; ++job) {
+ int64_t ii = m0 + job / xtiles * RM;
+ int64_t jj = n0 + job % xtiles * RN;
+ kernel<RM, RN>(ii, jj);
+ }
+ }
+
+ const float * const A;
+ const float * const B;
+ float * C;
+ const int64_t k;
+ const int64_t lda;
+ const int64_t ldb;
+ const int64_t ldc;
+ const int ith;
+ const int nth;
+};
+#endif
+} // namespace
+
+/**
+ * Performs optimized matrix multiplication on CPU.
+ *
+ * This subroutine may compute C = Aᵀ * B with column major ordering.
+ * Despite its name, this isn't a generalized implementation. Work is
+ * only performed when a handwritten kernel is written and available.
+ * Otherwise the caller should fall back to a general matmul routine.
+ *
+ * For example, for single-threaded single-precision GEMM you can say
+ *
+ * llamafile_sgemm(m, n, k, A, lda, B, ldb, C, ldc,
+ * 0, 1,
+ * GGML_TYPE_F32, GGML_TYPE_F32, GGML_TYPE_F32);
+ *
+ * @param m is rows in `A` and `C`
+ * @param n is cols in `B` and `C`
+ * @param k is cols in `A` and rows in `B`
+ * @param A is first input matrix (always transposed)
+ * @param lda is row stride of `A`
+ * @param B is second input matrix (never transposed)
+ * @param ldb is row stride of `B`
+ * @param C is input/output array of output matrices
+ * @param ldc is row stride of `C`
+ * @param ith is thread id (must be less than `nth`)
+ * @param nth is number of threads (must be greater than zero)
+ * @param Atype is GGML data type of `A`
+ * @param Btype is GGML data type of `B`
+ * @param Ctype is GGML data type of `C`
+ * @return true if this function was able to service the matmul request
+ */
+bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64_t n, int64_t k,
+ const void *A, int64_t lda, const void *B, int64_t ldb, void *C,
+ int64_t ldc, int Atype, int Btype, int Ctype) {
+
+ assert(m >= 0);
+ assert(n >= 0);
+ assert(k >= 0);
+ assert(lda >= k);
+ assert(ldb >= k);
+ assert(ldc >= m);
+ assert(params->nth > 0);
+ assert(params->ith < params->nth);
+
+ // only enable sgemm for prompt processing
+#if !defined(__MMA__)
+ if (n < 2)
+ return false;
+#endif
+
+ if (Ctype != GGML_TYPE_F32)
+ return false;
+
+ switch (Atype) {
+
+ case GGML_TYPE_F32: {
+ if (Btype != GGML_TYPE_F32)
+ return false;
+#if defined(__AVX512F__)
+ tinyBLAS<16, __m512, __m512, float, float, float> tb{ params,
+ k, (const float *)A, lda,
+ (const float *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+#elif defined(__AVX__) || defined(__AVX2__)
+ tinyBLAS<8, __m256, __m256, float, float, float> tb{ params,
+ k, (const float *)A, lda,
+ (const float *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+#elif defined(__ARM_NEON)
+ if (n < 4)
+ return false;
+ tinyBLAS<4, float32x4_t, float32x4_t, float, float, float> tb{ params,
+ k, (const float *)A, lda,
+ (const float *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+#elif defined(__VXE__) || defined(__VXE2__)
+ if (n < 4)
+ return false;
+ tinyBLAS<4, float32x4_t, float32x4_t, float, float, float> tb{ params,
+ k, (const float *)A, lda,
+ (const float *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+#elif defined(__MMA__)
+ if (k % 8)
+ return false;
+ tinyBLAS_PPC tb{
+ k, (const float *)A, lda,
+ (const float *)B, ldb,
+ (float *)C, ldc,
+ params->ith, params->nth};
+ tb.matmul(m, n);
+ return true;
+#elif defined(__riscv_zvfh)
+ #if LMUL == 1
+ tinyBLAS_RVV<vfloat32m1_t, vfloat32m1_t, float, float, float> tb{ params,
+ k, (const float *)A, lda,
+ (const float *)B, ldb,
+ (float *)C, ldc};
+ #elif LMUL == 2
+ tinyBLAS_RVV<vfloat32m2_t, vfloat32m2_t, float, float, float> tb{ params,
+ k, (const float *)A, lda,
+ (const float *)B, ldb,
+ (float *)C, ldc};
+ #else // LMUL = 4
+ tinyBLAS_RVV<vfloat32m4_t, vfloat32m4_t, float, float, float> tb{ params,
+ k, (const float *)A, lda,
+ (const float *)B, ldb,
+ (float *)C, ldc};
+ #endif
+ return tb.matmul(m, n);
+#else
+ return false;
+#endif
+ }
+
+ case GGML_TYPE_BF16: {
+#if defined(__AVX512BF16__)
+ if (Btype == GGML_TYPE_BF16) {
+ tinyBLAS<32, __m512, __m512bh, ggml_bf16_t, ggml_bf16_t, float> tb{ params, k,
+ (const ggml_bf16_t *)A, lda,
+ (const ggml_bf16_t *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+ }
+#elif defined(__AVX512F__)
+ if (Btype == GGML_TYPE_BF16) {
+ tinyBLAS<16, __m512, __m512, ggml_bf16_t, ggml_bf16_t, float> tb{ params, k,
+ (const ggml_bf16_t *)A, lda,
+ (const ggml_bf16_t *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+ }
+#elif defined(__AVX2__)
+ if (Btype == GGML_TYPE_BF16) {
+ tinyBLAS<8, __m256, __m256, ggml_bf16_t, ggml_bf16_t, float> tb{ params, k,
+ (const ggml_bf16_t *)A, lda,
+ (const ggml_bf16_t *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+ }
+#elif defined(__MMA__)
+ if (k % 8) {
+ return false;
+ }
+
+ if (Btype == GGML_TYPE_BF16) {
+ tinyBLAS_HP16_PPC<ggml_bf16_t, ggml_bf16_t, float> tb{ k,
+ (const ggml_bf16_t *)A, lda,
+ (const ggml_bf16_t *)B, ldb,
+ (float *)C, ldc,
+ params->ith, params->nth };
+
+ tb.matmul(m, n);
+ return true;
+ }
+#elif defined(__riscv_zvfbfwma)
+ #if LMUL == 1
+ tinyBLAS_RVV<vfloat32m1_t, vbfloat16mf2_t, ggml_bf16_t, ggml_bf16_t, float> tb{ params,
+ k, (const ggml_bf16_t *)A, lda,
+ (const ggml_bf16_t *)B, ldb,
+ (float *)C, ldc};
+ #elif LMUL == 2
+ tinyBLAS_RVV<vfloat32m2_t, vbfloat16m1_t, ggml_bf16_t, ggml_bf16_t, float> tb{ params,
+ k, (const ggml_bf16_t *)A, lda,
+ (const ggml_bf16_t *)B, ldb,
+ (float *)C, ldc};
+ #else // LMUL = 4
+ tinyBLAS_RVV<vfloat32m4_t, vbfloat16m2_t, ggml_bf16_t, ggml_bf16_t, float> tb{ params,
+ k, (const ggml_bf16_t *)A, lda,
+ (const ggml_bf16_t *)B, ldb,
+ (float *)C, ldc};
+ #endif
+ return tb.matmul(m, n);
+#endif
+ return false;
+ }
+
+ case GGML_TYPE_F16: {
+#if defined(__AVX512F__)
+ if (Btype == GGML_TYPE_F16) {
+ tinyBLAS<16, __m512, __m512, ggml_fp16_t, ggml_fp16_t, float> tb{ params, k,
+ (const ggml_fp16_t *)A, lda,
+ (const ggml_fp16_t *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+ }
+#elif (defined(__AVX__) || defined(__AVX2__)) && defined(__F16C__)
+ if (Btype == GGML_TYPE_F16) {
+ tinyBLAS<8, __m256, __m256, ggml_fp16_t, ggml_fp16_t, float> tb{ params, k,
+ (const ggml_fp16_t *)A, lda,
+ (const ggml_fp16_t *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+ }
+#elif defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && !defined(_MSC_VER)
+ if (n < 8)
+ return false;
+ if (Btype == GGML_TYPE_F16) {
+ tinyBLAS<8, float16x8_t, float16x8_t, ggml_fp16_t, ggml_fp16_t, float> tb{ params,
+ k, (const ggml_fp16_t *)A, lda,
+ (const ggml_fp16_t *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+ }
+#elif defined(__ARM_NEON) && !defined(_MSC_VER)
+ if (Btype == GGML_TYPE_F32) {
+ tinyBLAS<4, float32x4_t, float32x4_t, ggml_fp16_t, float, float> tb{ params,
+ k, (const ggml_fp16_t *)A, lda,
+ (const float *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+ }
+#elif defined(__VXE__) || defined(__VXE2__)
+ if (n < 4)
+ return false;
+ if (Btype == GGML_TYPE_F16) {
+ tinyBLAS<4, float32x4_t, float32x4_t, ggml_fp16_t, ggml_fp16_t, float> tb{ params,
+ k, (const ggml_fp16_t *)A, lda,
+ (const ggml_fp16_t *)B, ldb,
+ (float *)C, ldc};
+ return tb.matmul(m, n);
+ }
+#elif defined(__riscv_zvfh)
+ if (Btype == GGML_TYPE_F16) {
+ #if LMUL == 1
+ tinyBLAS_RVV<vfloat32m1_t, vfloat16mf2_t, ggml_fp16_t, ggml_fp16_t, float> tb{ params,
+ k, (const ggml_fp16_t *)A, lda,
+ (const ggml_fp16_t *)B, ldb,
+ (float *)C, ldc};
+ #elif LMUL == 2
+ tinyBLAS_RVV<vfloat32m2_t, vfloat16m1_t, ggml_fp16_t, ggml_fp16_t, float> tb{ params,
+ k, (const ggml_fp16_t *)A, lda,
+ (const ggml_fp16_t *)B, ldb,
+ (float *)C, ldc};
+ #else // LMUL = 4
+ tinyBLAS_RVV<vfloat32m4_t, vfloat16m2_t, ggml_fp16_t, ggml_fp16_t, float> tb{ params,
+ k, (const ggml_fp16_t *)A, lda,
+ (const ggml_fp16_t *)B, ldb,
+ (float *)C, ldc};
+ #endif
+ return tb.matmul(m, n);
+ }
+#elif defined(__MMA__)
+ if (k % 8) {
+ return false;
+ }
+
+ if (Btype == GGML_TYPE_F16) {
+ tinyBLAS_HP16_PPC<ggml_fp16_t, ggml_fp16_t, float> tb{ k,
+ (const ggml_fp16_t *)A, lda,
+ (const ggml_fp16_t *)B, ldb,
+ (float *)C, ldc,
+ params->ith, params->nth };
+
+ tb.matmul(m, n);
+ return true;
+ }
+#endif
+ return false;
+ }
+
+ case GGML_TYPE_Q8_0: {
+ if (Btype != GGML_TYPE_Q8_0)
+ return false;
+#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__)
+ tinyBLAS_Q0_AVX<block_q8_0, block_q8_0, float> tb{
+ k, (const block_q8_0 *)A, lda,
+ (const block_q8_0 *)B, ldb,
+ (float *)C, ldc,
+ params->ith, params->nth};
+ tb.matmul(m, n);
+ return true;
+#elif defined(__ARM_FEATURE_DOTPROD)
+ tinyBLAS_Q0_ARM<block_q8_0> tb{
+ k, (const block_q8_0 *)A, lda,
+ (const block_q8_0 *)B, ldb,
+ (float *)C, ldc,
+ params->ith, params->nth};
+ tb.matmul(m, n);
+ return true;
+#elif defined(__MMA__)
+ //TO-DO: Remove this condition once gemv forwarding is enabled.
+ if (n < 8 && n != 4)
+ return false;
+ if (m < 8 && m != 4)
+ return false;
+ tinyBLAS_Q0_PPC<block_q8_0> tb{
+ k, (const block_q8_0 *)A, lda,
+ (const block_q8_0 *)B, ldb,
+ (float *)C, ldc,
+ params->ith, params->nth};
+ tb.matmul(m, n);
+ return true;
+#else
+ return false;
+#endif
+ }
+
+ case GGML_TYPE_Q4_0: {
+ if (Btype != GGML_TYPE_Q8_0)
+ return false;
+#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__)
+ tinyBLAS_Q0_AVX<block_q4_0, block_q8_0, float> tb{
+ k, (const block_q4_0 *)A, lda,
+ (const block_q8_0 *)B, ldb,
+ (float *)C, ldc,
+ params->ith, params->nth};
+ tb.matmul(m, n);
+ return true;
+#elif defined(__ARM_FEATURE_DOTPROD)
+ tinyBLAS_Q0_ARM<block_q4_0> tb{
+ k, (const block_q4_0 *)A, lda,
+ (const block_q8_0 *)B, ldb,
+ (float *)C, ldc,
+ params->ith, params->nth};
+ tb.matmul(m, n);
+ return true;
+#elif defined(__MMA__)
+ //TO-DO: Remove this condition once gemv forwarding is enabled.
+ if (n < 8 && n != 4)
+ return false;
+ if (m < 8 && m != 4)
+ return false;
+ tinyBLAS_Q0_PPC<block_q4_0> tb{
+ k, (const block_q4_0 *)A, lda,
+ (const block_q8_0 *)B, ldb,
+ (float *)C, ldc,
+ params->ith, params->nth};
+ tb.matmul(m, n);
+ return true;
+#else
+ return false;
+#endif
+ }
+
+ case GGML_TYPE_Q5_0: {
+ if (Btype != GGML_TYPE_Q8_0)
+ return false;
+#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__)
+ tinyBLAS_Q0_AVX<block_q5_0, block_q8_0, float> tb{
+ k, (const block_q5_0 *)A, lda,
+ (const block_q8_0 *)B, ldb,
+ (float *)C, ldc,
+ params->ith, params->nth};
+ tb.matmul(m, n);
+ return true;
+#else
+ return false;
+#endif
+ }
+
+ case GGML_TYPE_IQ4_NL: {
+ if (Btype != GGML_TYPE_Q8_0)
+ return false;
+#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__)
+ tinyBLAS_Q0_AVX<block_iq4_nl, block_q8_0, float> tb{
+ k, (const block_iq4_nl *)A, lda,
+ (const block_q8_0 *)B, ldb,
+ (float *)C, ldc,
+ params->ith, params->nth};
+ tb.matmul(m, n);
+ return true;
+#else
+ return false;
+#endif
+ }
+
+ default:
+ return false;
+ }
+
+ (void)params;
+ (void)m;
+ (void)n;
+ (void)k;
+ (void)A;
+ (void)lda;
+ (void)B;
+ (void)ldb;
+ (void)C;
+ (void)ldc;
+ (void)Atype;
+ (void)Btype;
+ (void)Ctype;
+}
generated by cgit v1.2.3 (git 2.46.0) at 2026-04-29 13:31:32 +0000