diff options
| author | Mitja Felicijan <mitja.felicijan@gmail.com> | 2026-02-12 20:57:17 +0100 |
|---|---|---|
| committer | Mitja Felicijan <mitja.felicijan@gmail.com> | 2026-02-12 20:57:17 +0100 |
| commit | b333b06772c89d96aacb5490d6a219fba7c09cc6 (patch) | |
| tree | 211df60083a5946baa2ed61d33d8121b7e251b06 /llama.cpp/ggml/src/ggml-cuda/convert.cu | |
| download | llmnpc-b333b06772c89d96aacb5490d6a219fba7c09cc6.tar.gz | |
Engage!
Diffstat (limited to 'llama.cpp/ggml/src/ggml-cuda/convert.cu')
| -rw-r--r-- | llama.cpp/ggml/src/ggml-cuda/convert.cu | 825 |
1 files changed, 825 insertions, 0 deletions
diff --git a/llama.cpp/ggml/src/ggml-cuda/convert.cu b/llama.cpp/ggml/src/ggml-cuda/convert.cu new file mode 100644 index 0000000..ba3d4ee --- /dev/null +++ b/llama.cpp/ggml/src/ggml-cuda/convert.cu @@ -0,0 +1,825 @@ +#include "convert.cuh" +#include "dequantize.cuh" + +#include <cstdint> + +#define CUDA_Q8_0_NE_ALIGN 2048 + +template <int qk, int qr, dequantize_kernel_t dequantize_kernel, typename dst_t> +static __global__ void dequantize_block(const void * __restrict__ vx, dst_t * __restrict__ y, + const int64_t ne00, const int64_t ne01, const int64_t ne02, + const int64_t s01, const int64_t s02, const int64_t s03) { + const int64_t i00 = 2 * (int64_t(blockDim.x)*blockIdx.x + threadIdx.x); + + if (i00 >= ne00) { + return; + } + + const int64_t i01 = blockIdx.y; + const int64_t i02 = blockIdx.z % ne02; + const int64_t i03 = blockIdx.z / ne02; + + const int64_t ibx0 = i03*s03 + i02*s02 + i01*s01; + + const int64_t ib = ibx0 + i00/qk; // block index + const int64_t iqs = (i00%qk)/qr; // quant index + const int64_t iybs = i00 - i00%qk; // y block start index + const int64_t y_offset = qr == 1 ? 1 : qk/2; + + // dequantize + float2 v; + dequantize_kernel(vx, ib, iqs, v); + + const int64_t iy0 = ((i03*ne02 + i02)*ne01 + i01)*ne00 + iybs + iqs; + y[iy0 + 0] = ggml_cuda_cast<dst_t>(v.x); + y[iy0 + y_offset] = ggml_cuda_cast<dst_t>(v.y); +} + +template <bool need_check> +static __global__ void dequantize_block_q8_0_f16(const void * __restrict__ vx, half * __restrict__ y, const int64_t k) { +#if __CUDA_ARCH__ >= GGML_CUDA_CC_PASCAL + constexpr int nint = CUDA_Q8_0_NE_ALIGN/sizeof(int) + WARP_SIZE; + + const int64_t i0 = CUDA_Q8_0_NE_ALIGN*blockIdx.x; + const int * x0 = ((int *) vx) + blockIdx.x * nint; + half2 * y2 = (half2 *) (y + i0); + + __shared__ int vals[nint]; + +#pragma unroll + for (int ix0 = 0; ix0 < nint; ix0 += WARP_SIZE) { + if (need_check && i0*sizeof(block_q8_0)/QK8_0 + sizeof(int)*(ix0 + threadIdx.x) >= k*sizeof(block_q8_0)/QK8_0) { + break; + } + + const int ix = ix0 + threadIdx.x; + vals[ix] = x0[ix]; + } + + __syncthreads(); + +#pragma unroll + for (int iy = 0; iy < CUDA_Q8_0_NE_ALIGN; iy += 2*WARP_SIZE) { + if (need_check && i0 + iy + 2*threadIdx.x >= k) { + return; + } + + const half * b0 = ((const half *) vals) + (sizeof(block_q8_0)/sizeof(half)) * ((iy + 2*threadIdx.x)/QK8_0); + const half d = *b0; + const char2 qs = ((const char2 *) (b0 + 1))[threadIdx.x % (QK8_0/2)]; + + y2[iy/2 + threadIdx.x] = __hmul2(make_half2(qs.x, qs.y), __half2half2(d)); + } +#else + GGML_UNUSED_VARS(vx, y, k); + NO_DEVICE_CODE; +#endif // __CUDA_ARCH__ >= GGML_CUDA_CC_PASCAL +} + +template<typename dst_t> +static __global__ void dequantize_block_q4_0(const void * __restrict__ vx, dst_t * __restrict__ yy, int nb32) { + + const int64_t i = blockIdx.x; + + // assume 32 threads + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; + const int64_t ir = tid%8; + const int64_t ib = 8*i + ir; + if (ib >= nb32) { + return; + } + + dst_t * y = yy + 256*i + 32*ir + 4*il; + + const block_q4_0 * x = (const block_q4_0 *)vx + ib; + const float d = __half2float(x->d); + const float dm = -8*d; + + const uint8_t * q = x->qs + 4*il; + + for (int l = 0; l < 4; ++l) { + y[l+ 0] = d * (q[l] & 0xF) + dm; + y[l+16] = d * (q[l] >> 4) + dm; + } +} + +template<typename dst_t> +static __global__ void dequantize_block_q4_1(const void * __restrict__ vx, dst_t * __restrict__ yy, int nb32) { + + const int64_t i = blockIdx.x; + + // assume 32 threads + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; + const int64_t ir = tid%8; + const int64_t ib = 8*i + ir; + if (ib >= nb32) { + return; + } + + dst_t * y = yy + 256*i + 32*ir + 4*il; + + const block_q4_1 * x = (const block_q4_1 *)vx + ib; + const float2 d = __half22float2(x->dm); + + const uint8_t * q = x->qs + 4*il; + + for (int l = 0; l < 4; ++l) { + y[l+ 0] = d.x * (q[l] & 0xF) + d.y; + y[l+16] = d.x * (q[l] >> 4) + d.y; + } +} + +//================================== k-quants + +template<typename dst_t> +static __global__ void dequantize_block_q2_K(const void * __restrict__ vx, dst_t * __restrict__ yy) { + + const int64_t i = blockIdx.x; + const block_q2_K * x = (const block_q2_K *) vx; + + const int64_t tid = threadIdx.x; + const int64_t n = tid/32; + const int64_t l = tid - 32*n; + const int64_t is = 8*n + l/16; + + const uint8_t q = x[i].qs[32*n + l]; + dst_t * y = yy + i*QK_K + 128*n; + + float dall = __low2half(x[i].dm); + float dmin = __high2half(x[i].dm); + y[l+ 0] = dall * (x[i].scales[is+0] & 0xF) * ((q >> 0) & 3) - dmin * (x[i].scales[is+0] >> 4); + y[l+32] = dall * (x[i].scales[is+2] & 0xF) * ((q >> 2) & 3) - dmin * (x[i].scales[is+2] >> 4); + y[l+64] = dall * (x[i].scales[is+4] & 0xF) * ((q >> 4) & 3) - dmin * (x[i].scales[is+4] >> 4); + y[l+96] = dall * (x[i].scales[is+6] & 0xF) * ((q >> 6) & 3) - dmin * (x[i].scales[is+6] >> 4); +} + +template<typename dst_t> +static __global__ void dequantize_block_q3_K(const void * __restrict__ vx, dst_t * __restrict__ yy) { + + const int64_t i = blockIdx.x; + const block_q3_K * x = (const block_q3_K *) vx; + + const int64_t r = threadIdx.x/4; + const int64_t tid = r/2; + const int64_t is0 = r%2; + const int64_t l0 = 16*is0 + 4*(threadIdx.x%4); + const int64_t n = tid / 4; + const int64_t j = tid - 4*n; + + uint8_t m = 1 << (4*n + j); + int64_t is = 8*n + 2*j + is0; + int shift = 2*j; + + int8_t us = is < 4 ? (x[i].scales[is-0] & 0xF) | (((x[i].scales[is+8] >> 0) & 3) << 4) : + is < 8 ? (x[i].scales[is-0] & 0xF) | (((x[i].scales[is+4] >> 2) & 3) << 4) : + is < 12 ? (x[i].scales[is-8] >> 4) | (((x[i].scales[is+0] >> 4) & 3) << 4) : + (x[i].scales[is-8] >> 4) | (((x[i].scales[is-4] >> 6) & 3) << 4); + float d_all = x[i].d; + float dl = d_all * (us - 32); + + dst_t * y = yy + i*QK_K + 128*n + 32*j; + const uint8_t * q = x[i].qs + 32*n; + const uint8_t * hm = x[i].hmask; + + for (int l = l0; l < l0+4; ++l) y[l] = dl * ((int8_t)((q[l] >> shift) & 3) - ((hm[l] & m) ? 0 : 4)); +} + +static inline __device__ void get_scale_min_k4(int j, const uint8_t * q, uint8_t & d, uint8_t & m) { + if (j < 4) { + d = q[j] & 63; m = q[j + 4] & 63; + } else { + d = (q[j+4] & 0xF) | ((q[j-4] >> 6) << 4); + m = (q[j+4] >> 4) | ((q[j-0] >> 6) << 4); + } +} + +template<typename dst_t> +static __global__ void dequantize_block_q4_K(const void * __restrict__ vx, dst_t * __restrict__ yy) { + const block_q4_K * x = (const block_q4_K *) vx; + + const int64_t i = blockIdx.x; + + // assume 32 threads + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; + const int64_t ir = tid%8; + const int64_t is = 2*il; + const int64_t n = 4; + + dst_t * y = yy + i*QK_K + 64*il + n*ir; + + const float dall = __low2half(x[i].dm); + const float dmin = __high2half(x[i].dm); + + const uint8_t * q = x[i].qs + 32*il + n*ir; + + uint8_t sc, m; + get_scale_min_k4(is + 0, x[i].scales, sc, m); + const float d1 = dall * sc; const float m1 = dmin * m; + get_scale_min_k4(is + 1, x[i].scales, sc, m); + const float d2 = dall * sc; const float m2 = dmin * m; + for (int l = 0; l < n; ++l) { + y[l + 0] = d1 * (q[l] & 0xF) - m1; + y[l +32] = d2 * (q[l] >> 4) - m2; + } +} + +template<typename dst_t> +static __global__ void dequantize_block_q5_K(const void * __restrict__ vx, dst_t * __restrict__ yy) { + const block_q5_K * x = (const block_q5_K *) vx; + + const int64_t i = blockIdx.x; + + // assume 64 threads - this is very slightly better than the one below + const int64_t tid = threadIdx.x; + const int64_t il = tid/16; // il is in 0...3 + const int64_t ir = tid%16; // ir is in 0...15 + const int64_t is = 2*il; // is is in 0...6 + + dst_t * y = yy + i*QK_K + 64*il + 2*ir; + + const float dall = __low2half(x[i].dm); + const float dmin = __high2half(x[i].dm); + + const uint8_t * ql = x[i].qs + 32*il + 2*ir; + const uint8_t * qh = x[i].qh + 2*ir; + + uint8_t sc, m; + get_scale_min_k4(is + 0, x[i].scales, sc, m); + const float d1 = dall * sc; const float m1 = dmin * m; + get_scale_min_k4(is + 1, x[i].scales, sc, m); + const float d2 = dall * sc; const float m2 = dmin * m; + + uint8_t hm = 1 << (2*il); + y[ 0] = d1 * ((ql[ 0] & 0xF) + (qh[ 0] & hm ? 16 : 0)) - m1; + y[ 1] = d1 * ((ql[ 1] & 0xF) + (qh[ 1] & hm ? 16 : 0)) - m1; + hm <<= 1; + y[32] = d2 * ((ql[ 0] >> 4) + (qh[ 0] & hm ? 16 : 0)) - m2; + y[33] = d2 * ((ql[ 1] >> 4) + (qh[ 1] & hm ? 16 : 0)) - m2; +} + +template<typename dst_t> +static __global__ void dequantize_block_q6_K(const void * __restrict__ vx, dst_t * __restrict__ yy) { + const block_q6_K * x = (const block_q6_K *) vx; + + const int64_t i = blockIdx.x; + + // assume 64 threads - this is very slightly better than the one below + const int64_t tid = threadIdx.x; + const int64_t ip = tid/32; // ip is 0 or 1 + const int64_t il = tid - 32*ip; // 0...32 + const int64_t is = 8*ip + il/16; + + dst_t * y = yy + i*QK_K + 128*ip + il; + + const float d = x[i].d; + + const uint8_t * ql = x[i].ql + 64*ip + il; + const uint8_t qh = x[i].qh[32*ip + il]; + const int8_t * sc = x[i].scales + is; + + y[ 0] = d * sc[0] * ((int8_t)((ql[ 0] & 0xF) | (((qh >> 0) & 3) << 4)) - 32); + y[32] = d * sc[2] * ((int8_t)((ql[32] & 0xF) | (((qh >> 2) & 3) << 4)) - 32); + y[64] = d * sc[4] * ((int8_t)((ql[ 0] >> 4) | (((qh >> 4) & 3) << 4)) - 32); + y[96] = d * sc[6] * ((int8_t)((ql[32] >> 4) | (((qh >> 6) & 3) << 4)) - 32); +} + +template<typename dst_t> +static __global__ void dequantize_block_iq2_xxs(const void * __restrict__ vx, dst_t * __restrict__ yy) { + + const int64_t i = blockIdx.x; + const block_iq2_xxs * x = (const block_iq2_xxs *) vx; + + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; // 0...3 + const int64_t ib = tid%8; // 0...7 + dst_t * y = yy + i*QK_K + 32*ib + 8*il; + const uint16_t * q2 = x[i].qs + 4*ib; + const uint8_t * aux8 = (const uint8_t *)q2; + const uint8_t * grid = (const uint8_t *)(iq2xxs_grid + aux8[il]); + const uint32_t aux32 = q2[2] | (q2[3] << 16); + const float d = (float)x[i].d * (0.5f + (aux32 >> 28)) * 0.25f; + const uint8_t signs = ksigns_iq2xs[(aux32 >> 7*il) & 127]; + for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f); +} + +template<typename dst_t> +static __global__ void dequantize_block_iq2_xs(const void * __restrict__ vx, dst_t * __restrict__ yy) { + + const int64_t i = blockIdx.x; + const block_iq2_xs * x = (const block_iq2_xs *) vx; + + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; // 0...3 + const int64_t ib = tid%8; // 0...7 + dst_t * y = yy + i*QK_K + 32*ib + 8*il; + const uint16_t * q2 = x[i].qs + 4*ib; + const uint8_t * grid = (const uint8_t *)(iq2xs_grid + (q2[il] & 511)); + const float d = (float)x[i].d * (0.5f + ((x[i].scales[ib] >> 4*(il/2)) & 0xf)) * 0.25f; + const uint8_t signs = ksigns_iq2xs[q2[il] >> 9]; + for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f); +} + +template<typename dst_t> +static __global__ void dequantize_block_iq2_s(const void * __restrict__ vx, dst_t * __restrict__ yy) { + + const int64_t i = blockIdx.x; + const block_iq2_s * x = (const block_iq2_s *) vx; + + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; // 0...3 + const int64_t ib = tid%8; // 0...7 + dst_t * y = yy + i*QK_K + 32*ib + 8*il; + const uint8_t * grid = (const uint8_t *)(iq2s_grid + (x[i].qs[4*ib+il] | ((x[i].qh[ib] << (8-2*il)) & 0x300))); + const float d = (float)x[i].d * (0.5f + ((x[i].scales[ib] >> 4*(il/2)) & 0xf)) * 0.25f; + const uint8_t signs = x[i].qs[QK_K/8+4*ib+il]; + for (int j = 0; j < 8; ++j) y[j] = d * grid[j] * (signs & kmask_iq2xs[j] ? -1.f : 1.f); +} + +template<typename dst_t> +static __global__ void dequantize_block_iq3_xxs(const void * __restrict__ vx, dst_t * __restrict__ yy) { + + const int64_t i = blockIdx.x; + const block_iq3_xxs * x = (const block_iq3_xxs *) vx; + + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; // 0...3 + const int64_t ib = tid%8; // 0...7 + dst_t * y = yy + i*QK_K + 32*ib + 8*il; + const uint8_t * q3 = x[i].qs + 8*ib; + const uint16_t * gas = (const uint16_t *)(x[i].qs + QK_K/4) + 2*ib; + const uint8_t * grid1 = (const uint8_t *)(iq3xxs_grid + q3[2*il+0]); + const uint8_t * grid2 = (const uint8_t *)(iq3xxs_grid + q3[2*il+1]); + const uint32_t aux32 = gas[0] | (gas[1] << 16); + const float d = (float)x[i].d * (0.5f + (aux32 >> 28)) * 0.5f; + const uint8_t signs = ksigns_iq2xs[(aux32 >> 7*il) & 127]; + for (int j = 0; j < 4; ++j) { + y[j+0] = d * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f); + y[j+4] = d * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f); + } +} + +template<typename dst_t> +static __global__ void dequantize_block_iq3_s(const void * __restrict__ vx, dst_t * __restrict__ yy) { + + const int64_t i = blockIdx.x; + const block_iq3_s * x = (const block_iq3_s *) vx; + + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; // 0...3 + const int64_t ib = tid%8; // 0...7 + dst_t * y = yy + i*QK_K + 32*ib + 8*il; + const uint8_t * qs = x[i].qs + 8*ib; + const uint8_t * grid1 = (const uint8_t *)(iq3s_grid + (qs[2*il+0] | ((x[i].qh[ib] << (8-2*il)) & 256))); + const uint8_t * grid2 = (const uint8_t *)(iq3s_grid + (qs[2*il+1] | ((x[i].qh[ib] << (7-2*il)) & 256))); + const float d = (float)x[i].d * (1 + 2*((x[i].scales[ib/2] >> 4*(ib%2)) & 0xf)); + const uint8_t signs = x[i].signs[4*ib + il]; + for (int j = 0; j < 4; ++j) { + y[j+0] = d * grid1[j] * (signs & kmask_iq2xs[j+0] ? -1.f : 1.f); + y[j+4] = d * grid2[j] * (signs & kmask_iq2xs[j+4] ? -1.f : 1.f); + } +} + +template<typename dst_t> +static __global__ void dequantize_block_iq1_s(const void * __restrict__ vx, dst_t * __restrict__ yy) { + + const int64_t i = blockIdx.x; + const block_iq1_s * x = (const block_iq1_s *) vx; + + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; // 0...3 + const int64_t ib = tid%8; // 0...7 + dst_t * y = yy + i*QK_K + 32*ib + 8*il; + const float delta = x[i].qh[ib] & 0x8000 ? -1 - IQ1S_DELTA : -1 + IQ1S_DELTA; + const float d = (float)x[i].d * (2*((x[i].qh[ib] >> 12) & 7) + 1); + uint32_t grid32[2]; const int8_t * q = (const int8_t *)grid32; + grid32[0] = iq1s_grid_gpu[x[i].qs[4*ib+il] | (((x[i].qh[ib] >> 3*il) & 7) << 8)]; + grid32[1] = (grid32[0] >> 4) & 0x0f0f0f0f; + grid32[0] &= 0x0f0f0f0f; + for (int j = 0; j < 8; ++j) { + y[j] = d * (q[j] + delta); + } +} + +template<typename dst_t> +static __global__ void dequantize_block_iq1_m(const void * __restrict__ vx, dst_t * __restrict__ yy) { + + const int64_t i = blockIdx.x; + const block_iq1_m * x = (const block_iq1_m *) vx; + + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; // 0...3 + const int64_t ib = tid%8; // 0...7 + dst_t * y = yy + i*QK_K + 32*ib + 8*il; + const uint16_t * sc = (const uint16_t *)x[i].scales; + iq1m_scale_t scale; + scale.u16 = (sc[0] >> 12) | ((sc[1] >> 8) & 0x00f0) | ((sc[2] >> 4) & 0x0f00) | (sc[3] & 0xf000); + const int64_t ib16 = 2*ib + il/2; // sc[ib16/4] >> 3*(ib16%4) -> sc[ib/2] >> 3*((2*ib+il/2)%4); + const float d = (float)scale.f16 * (2*((sc[ib16/4] >> 3*(ib16%4)) & 0x7) + 1); + const float delta = x[i].qh[2*ib+il/2] & (0x08 << 4*(il%2)) ? -1 - IQ1M_DELTA : -1 + IQ1M_DELTA; + uint32_t grid32[2]; const int8_t * q = (const int8_t *)grid32; + grid32[0] = iq1s_grid_gpu[x[i].qs[4*ib+il] | (((x[i].qh[2*ib+il/2] >> 4*(il%2)) & 7) << 8)]; + grid32[1] = (grid32[0] >> 4) & 0x0f0f0f0f; + grid32[0] &= 0x0f0f0f0f; + for (int j = 0; j < 8; ++j) { + y[j] = d * (q[j] + delta); + } +} + +template<typename dst_t> +static __global__ void dequantize_block_iq4_nl(const void * __restrict__ vx, dst_t * __restrict__ yy) { + + const int64_t i = blockIdx.x; + const block_iq4_nl * x = (const block_iq4_nl *) vx + i*(QK_K/QK4_NL); + + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; // 0...3 + const int64_t ib = tid%8; // 0...7 + dst_t * y = yy + i*QK_K + 32*ib + 4*il; + const uint8_t * q4 = x[ib].qs + 4*il; + const float d = (float)x[ib].d; + for (int j = 0; j < 4; ++j) { + y[j+ 0] = d * kvalues_iq4nl[q4[j] & 0xf]; + y[j+16] = d * kvalues_iq4nl[q4[j] >> 4]; + } +} + +template<typename dst_t> +static __global__ void dequantize_block_iq4_xs(const void * __restrict__ vx, dst_t * __restrict__ yy) { + const int64_t i = blockIdx.x; + const block_iq4_xs * x = (const block_iq4_xs *)vx; + + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; // 0...3 + const int64_t ib = tid%8; // 0...7 + dst_t * y = yy + i*QK_K + 32*ib + 4*il; + const uint8_t * q4 = x[i].qs + 16*ib + 4*il; + const float d = (float)x[i].d * ((((x[i].scales_l[ib/2] >> 4*(ib%2)) & 0xf) | (((x[i].scales_h >> 2*ib) & 3) << 4)) - 32); + for (int j = 0; j < 4; ++j) { + y[j+ 0] = d * kvalues_iq4nl[q4[j] & 0xf]; + y[j+16] = d * kvalues_iq4nl[q4[j] >> 4]; + } +} + +template<typename dst_t> +static __global__ void dequantize_block_mxfp4(const void * __restrict__ vx, dst_t * __restrict__ yy) { + + const int64_t i = blockIdx.x; + const block_mxfp4 * x = (const block_mxfp4 *) vx + i*(QK_K/QK_MXFP4); + + const int64_t tid = threadIdx.x; + const int64_t il = tid/8; // 0...3 + const int64_t ib = tid%8; // 0...7 + dst_t * y = yy + i*QK_K + 32*ib + 4*il; + const uint8_t * q4 = x[ib].qs + 4*il; + const float d = ggml_cuda_e8m0_to_fp32(x[ib].e); + for (int j = 0; j < 4; ++j) { + y[j+ 0] = d * kvalues_mxfp4[q4[j] & 0xf]*0.5f; + y[j+16] = d * kvalues_mxfp4[q4[j] >> 4]*0.5f; + } +} + +template <int qk, int qr, dequantize_kernel_t dequantize_kernel, typename dst_t> +static void dequantize_block_cuda(const void * vx, dst_t * y, + const int64_t ne00, const int64_t ne01, const int64_t ne02, const int64_t ne03, + const int64_t s01, const int64_t s02, const int64_t s03, cudaStream_t stream) { + const dim3 num_blocks((ne00 + 2*CUDA_DEQUANTIZE_BLOCK_SIZE - 1) / (2*CUDA_DEQUANTIZE_BLOCK_SIZE), ne01, ne02*ne03); + dequantize_block<qk, qr, dequantize_kernel><<<num_blocks, CUDA_DEQUANTIZE_BLOCK_SIZE, 0, stream>>> + (vx, y, ne00, ne01, ne02, s01, s02, s03); +} + +template <int qk, int qr, dequantize_kernel_t dequantize_kernel, typename dst_t> +static void dequantize_block_cont_cuda(const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t k, cudaStream_t stream) { + dequantize_block_cuda<qk, qr, dequantize_kernel, dst_t>(vx, y, k, 1, 1, 1, k/qk, k/qk, k/qk, stream); +} + +static void dequantize_block_q8_0_f16_cuda(const void * __restrict__ vx, half * __restrict__ y, const int64_t k, cudaStream_t stream) { + const int num_blocks = (k + CUDA_Q8_0_NE_ALIGN - 1) / CUDA_Q8_0_NE_ALIGN; + if (k % CUDA_Q8_0_NE_ALIGN == 0) { + const bool need_check = false; + dequantize_block_q8_0_f16<need_check><<<num_blocks, WARP_SIZE, 0, stream>>>(vx, y, k); + } else { + const bool need_check = true; + dequantize_block_q8_0_f16<need_check><<<num_blocks, WARP_SIZE, 0, stream>>>(vx, y, k); + } +} + +template<typename dst_t> +static void dequantize_row_q2_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_q2_K<<<nb, 64, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_q3_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_q3_K<<<nb, 64, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_q4_0_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb32 = k / 32; + const int nb = (k + 255) / 256; + dequantize_block_q4_0<<<nb, 32, 0, stream>>>(vx, y, nb32); +} + +template<typename dst_t> +static void dequantize_row_q4_1_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb32 = k / 32; + const int nb = (k + 255) / 256; + dequantize_block_q4_1<<<nb, 32, 0, stream>>>(vx, y, nb32); +} + +template<typename dst_t> +static void dequantize_row_q4_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_q4_K<<<nb, 32, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_q5_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_q5_K<<<nb, 64, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_q6_K_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_q6_K<<<nb, 64, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_iq2_xxs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_iq2_xxs<<<nb, 32, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_iq2_xs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_iq2_xs<<<nb, 32, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_iq2_s_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_iq2_s<<<nb, 32, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_iq3_xxs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_iq3_xxs<<<nb, 32, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_iq3_s_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_iq3_s<<<nb, 32, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_iq1_s_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_iq1_s<<<nb, 32, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_iq4_nl_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = (k + QK_K - 1) / QK_K; + dequantize_block_iq4_nl<<<nb, 32, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_iq1_m_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = k / QK_K; + dequantize_block_iq1_m<<<nb, 32, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_iq4_xs_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = (k + QK_K - 1) / QK_K; + dequantize_block_iq4_xs<<<nb, 32, 0, stream>>>(vx, y); +} + +template<typename dst_t> +static void dequantize_row_mxfp4_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + const int nb = (k + QK_K - 1) / QK_K; + dequantize_block_mxfp4<<<nb, 32, 0, stream>>>(vx, y); +} + +template <typename src_t, typename dst_t> +static __global__ void convert_unary( + const void * __restrict__ vx, dst_t * __restrict__ y, const int64_t ne00, const int64_t ne01, const int64_t ne02, + const int64_t s01, const int64_t s02, const int64_t s03) { + const int64_t i00 = (int64_t)blockDim.x*blockIdx.x + threadIdx.x; + + if (i00 >= ne00) { + return; + } + + const int64_t i01 = blockIdx.y; + const int64_t i02 = blockIdx.z % ne02; + const int64_t i03 = blockIdx.z / ne02; + + const src_t * x = (const src_t *) vx; + + const int64_t ix = i03*s03 + i02*s02 + i01*s01 + i00; + const int64_t iy = ((i03*ne02 + i02)*ne01 + i01)*ne00 + i00; + y[iy] = ggml_cuda_cast<dst_t>(x[ix]); +} + +template <typename src_t, typename dst_t> +static void convert_unary_cuda(const void * vx, dst_t * y, + const int64_t ne00, const int64_t ne01, const int64_t ne02, const int64_t ne03, + const int64_t s01, const int64_t s02, const int64_t s03, cudaStream_t stream) { + const dim3 num_blocks((ne00 + CUDA_DEQUANTIZE_BLOCK_SIZE - 1) / CUDA_DEQUANTIZE_BLOCK_SIZE, ne01, ne02*ne03); + convert_unary<src_t><<<num_blocks, CUDA_DEQUANTIZE_BLOCK_SIZE, 0, stream>>> + (vx, y, ne00, ne01, ne02, s01, s02, s03); +} + +template <typename src_t, typename dst_t> +static void convert_unary_cont_cuda(const void * vx, dst_t * y, const int64_t k, cudaStream_t stream) { + convert_unary_cuda<src_t>(vx, y, k, 1, 1, 1, k, k, k, stream); +} + +to_bf16_cuda_t ggml_get_to_bf16_cuda(ggml_type type) { + switch (type) { + case GGML_TYPE_F32: + return convert_unary_cont_cuda<float>; + case GGML_TYPE_F16: + return convert_unary_cont_cuda<half>; + default: + return nullptr; + } +} + +to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type) { + switch (type) { + case GGML_TYPE_Q4_0: + return dequantize_row_q4_0_cuda; + case GGML_TYPE_Q4_1: + return dequantize_row_q4_1_cuda; + case GGML_TYPE_Q5_0: + return dequantize_block_cont_cuda<QK5_0, QR5_0, dequantize_q5_0>; + case GGML_TYPE_Q5_1: + return dequantize_block_cont_cuda<QK5_1, QR5_1, dequantize_q5_1>; + case GGML_TYPE_Q8_0: + if (fp16_available(ggml_cuda_info().devices[ggml_cuda_get_device()].cc)) { + return dequantize_block_q8_0_f16_cuda; + } + return dequantize_block_cont_cuda<QK8_0, QR8_0, dequantize_q8_0>; + case GGML_TYPE_Q2_K: + return dequantize_row_q2_K_cuda; + case GGML_TYPE_Q3_K: + return dequantize_row_q3_K_cuda; + case GGML_TYPE_Q4_K: + return dequantize_row_q4_K_cuda; + case GGML_TYPE_Q5_K: + return dequantize_row_q5_K_cuda; + case GGML_TYPE_Q6_K: + return dequantize_row_q6_K_cuda; + case GGML_TYPE_IQ2_XXS: + return dequantize_row_iq2_xxs_cuda; + case GGML_TYPE_IQ2_XS: + return dequantize_row_iq2_xs_cuda; + case GGML_TYPE_IQ2_S: + return dequantize_row_iq2_s_cuda; + case GGML_TYPE_IQ3_XXS: + return dequantize_row_iq3_xxs_cuda; + case GGML_TYPE_IQ1_S: + return dequantize_row_iq1_s_cuda; + case GGML_TYPE_IQ1_M: + return dequantize_row_iq1_m_cuda; + case GGML_TYPE_IQ4_NL: + return dequantize_row_iq4_nl_cuda; + case GGML_TYPE_IQ4_XS: + return dequantize_row_iq4_xs_cuda; + case GGML_TYPE_IQ3_S: + return dequantize_row_iq3_s_cuda; + case GGML_TYPE_MXFP4: + return dequantize_row_mxfp4_cuda; + case GGML_TYPE_F32: + return convert_unary_cont_cuda<float>; + case GGML_TYPE_BF16: + return convert_unary_cont_cuda<nv_bfloat16>; + default: + return nullptr; + } +} + +to_fp32_cuda_t ggml_get_to_fp32_cuda(ggml_type type) { + switch (type) { + case GGML_TYPE_Q4_0: + return dequantize_row_q4_0_cuda; + case GGML_TYPE_Q4_1: + return dequantize_row_q4_1_cuda; + case GGML_TYPE_Q5_0: + return dequantize_block_cont_cuda<QK5_0, QR5_0, dequantize_q5_0>; + case GGML_TYPE_Q5_1: + return dequantize_block_cont_cuda<QK5_1, QR5_1, dequantize_q5_1>; + case GGML_TYPE_Q8_0: + return dequantize_block_cont_cuda<QK8_0, QR8_0, dequantize_q8_0>; + case GGML_TYPE_Q2_K: + return dequantize_row_q2_K_cuda; + case GGML_TYPE_Q3_K: + return dequantize_row_q3_K_cuda; + case GGML_TYPE_Q4_K: + return dequantize_row_q4_K_cuda; + case GGML_TYPE_Q5_K: + return dequantize_row_q5_K_cuda; + case GGML_TYPE_Q6_K: + return dequantize_row_q6_K_cuda; + case GGML_TYPE_IQ2_XXS: + return dequantize_row_iq2_xxs_cuda; + case GGML_TYPE_IQ2_XS: + return dequantize_row_iq2_xs_cuda; + case GGML_TYPE_IQ2_S: + return dequantize_row_iq2_s_cuda; + case GGML_TYPE_IQ3_XXS: + return dequantize_row_iq3_xxs_cuda; + case GGML_TYPE_IQ1_S: + return dequantize_row_iq1_s_cuda; + case GGML_TYPE_IQ1_M: + return dequantize_row_iq1_m_cuda; + case GGML_TYPE_IQ4_NL: + return dequantize_row_iq4_nl_cuda; + case GGML_TYPE_IQ4_XS: + return dequantize_row_iq4_xs_cuda; + case GGML_TYPE_IQ3_S: + return dequantize_row_iq3_s_cuda; + case GGML_TYPE_MXFP4: + return dequantize_row_mxfp4_cuda; + case GGML_TYPE_F16: + return convert_unary_cont_cuda<half>; + case GGML_TYPE_BF16: + return convert_unary_cont_cuda<nv_bfloat16>; + default: + return nullptr; + } +} + +to_fp16_nc_cuda_t ggml_get_to_fp16_nc_cuda(ggml_type type) { + switch (type) { + case GGML_TYPE_F32: + return convert_unary_cuda<float>; + case GGML_TYPE_Q4_0: + return dequantize_block_cuda<QK4_0, QR4_0, dequantize_q4_0>; + case GGML_TYPE_Q4_1: + return dequantize_block_cuda<QK4_1, QR4_1, dequantize_q4_1>; + case GGML_TYPE_Q5_0: + return dequantize_block_cuda<QK5_0, QR5_0, dequantize_q5_0>; + case GGML_TYPE_Q5_1: + return dequantize_block_cuda<QK5_1, QR5_1, dequantize_q5_1>; + case GGML_TYPE_Q8_0: + return dequantize_block_cuda<QK8_0, QR8_0, dequantize_q8_0>; + case GGML_TYPE_BF16: + return convert_unary_cuda<nv_bfloat16>; + default: + return nullptr; + } +} + +to_bf16_nc_cuda_t ggml_get_to_bf16_nc_cuda(ggml_type type) { + switch (type) { + case GGML_TYPE_F32: + return convert_unary_cuda<float, nv_bfloat16>; + case GGML_TYPE_Q4_0: + return dequantize_block_cuda<QK4_0, QR4_0, dequantize_q4_0>; + case GGML_TYPE_Q4_1: + return dequantize_block_cuda<QK4_1, QR4_1, dequantize_q4_1>; + case GGML_TYPE_Q5_0: + return dequantize_block_cuda<QK5_0, QR5_0, dequantize_q5_0>; + case GGML_TYPE_Q5_1: + return dequantize_block_cuda<QK5_1, QR5_1, dequantize_q5_1>; + case GGML_TYPE_Q8_0: + return dequantize_block_cuda<QK8_0, QR8_0, dequantize_q8_0>; + case GGML_TYPE_F16: + return convert_unary_cuda<half, nv_bfloat16>; + default: + return nullptr; + } +} + +to_fp32_nc_cuda_t ggml_get_to_fp32_nc_cuda(ggml_type type) { + switch (type) { + case GGML_TYPE_F16: + return convert_unary_cuda<half, float>; + case GGML_TYPE_Q4_0: + return dequantize_block_cuda<QK4_0, QR4_0, dequantize_q4_0>; + case GGML_TYPE_Q4_1: + return dequantize_block_cuda<QK4_1, QR4_1, dequantize_q4_1>; + case GGML_TYPE_Q5_0: + return dequantize_block_cuda<QK5_0, QR5_0, dequantize_q5_0>; + case GGML_TYPE_Q5_1: + return dequantize_block_cuda<QK5_1, QR5_1, dequantize_q5_1>; + case GGML_TYPE_Q8_0: + return dequantize_block_cuda<QK8_0, QR8_0, dequantize_q8_0>; + case GGML_TYPE_BF16: + return convert_unary_cuda<nv_bfloat16, float>; + default: + return nullptr; + } +} |
