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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-cuda/im2col.cu
downloadllmnpc-b333b06772c89d96aacb5490d6a219fba7c09cc6.tar.gz
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Diffstat (limited to 'llama.cpp/ggml/src/ggml-cuda/im2col.cu')
-rw-r--r--llama.cpp/ggml/src/ggml-cuda/im2col.cu264
1 files changed, 264 insertions, 0 deletions
diff --git a/llama.cpp/ggml/src/ggml-cuda/im2col.cu b/llama.cpp/ggml/src/ggml-cuda/im2col.cu
new file mode 100644
index 0000000..56dc054
--- /dev/null
+++ b/llama.cpp/ggml/src/ggml-cuda/im2col.cu
@@ -0,0 +1,264 @@
+#include "im2col.cuh"
+
+#define MAX_GRIDDIM_Z 65535
+
+template <typename T>
+static __global__ void im2col_kernel(
+ const float * x, T * dst,
+ int64_t IC, int64_t IW, int64_t IH, int64_t OH, int64_t OW, int64_t KW, int64_t KH,
+ int64_t IC_IH_IW, int64_t IH_IW, int64_t N_OH, int64_t KH_KW, int64_t IC_KH_KW,
+ int s0, int s1, int p0, int p1, int d0, int d1) {
+ const int64_t i = threadIdx.x + blockIdx.x * blockDim.x;
+ if (i >= IC_KH_KW) {
+ return;
+ }
+
+ const int64_t iic = i / (KH_KW);
+ const int64_t rem = i - iic * KH_KW;
+ const int64_t ikh = rem / KW;
+ const int64_t ikw = rem - ikh * KW;
+
+ const int64_t iow = blockIdx.y;
+ for (int64_t iz = blockIdx.z; iz < N_OH; iz+=MAX_GRIDDIM_Z) {
+ const int64_t in = iz / OH;
+ const int64_t ioh = iz - in * OH;
+
+ const int64_t iiw = iow * s0 + ikw * d0 - p0;
+ const int64_t iih = ioh * s1 + ikh * d1 - p1;
+
+ const int64_t offset_dst =
+ ((in * OH + ioh) * OW + iow) * IC_KH_KW + iic * KH_KW + ikh * KW + ikw;
+
+ if (iih < 0 || iih >= IH || iiw < 0 || iiw >= IW) {
+ dst[offset_dst] = 0.0f;
+ } else {
+ const int64_t offset_src = iic * IC_IH_IW + in * IH_IW;
+ dst[offset_dst] = x[offset_src + iih * IW + iiw];
+ }
+ }
+
+ GGML_UNUSED(IC);
+ GGML_UNUSED(KH);
+}
+
+// im2col: [N, IC, IH, IW] => [N, OH, OW, IC*KH*KW]
+template <typename T>
+static void im2col_cuda(const float * x, T* dst,
+ int64_t IW, int64_t IH, int64_t OW, int64_t OH, int64_t KW, int64_t KH, int64_t IC,
+ int64_t N, int64_t IC_IH_IW, int64_t IH_IW,
+ int s0,int s1,int p0,int p1,int d0,int d1, cudaStream_t stream) {
+ const int64_t IC_KH_KW = IC * KH * KW;
+ const int64_t num_blocks = (IC_KH_KW + CUDA_IM2COL_BLOCK_SIZE - 1) / CUDA_IM2COL_BLOCK_SIZE;
+ const int64_t N_OH = N * OH;
+ const int64_t KH_KW = KW*KH;
+ dim3 block_nums(num_blocks, OW, MIN(N_OH, MAX_GRIDDIM_Z));
+ im2col_kernel<<<block_nums, MIN(IC_KH_KW, CUDA_IM2COL_BLOCK_SIZE) , 0, stream>>>(x, dst, IC, IW, IH, OH, OW, KW, KH,
+ IC_IH_IW, IH_IW, N_OH, KH_KW, IC_KH_KW,
+ s0, s1, p0, p1, d0, d1);
+}
+
+static void im2col_cuda_f16(const float * x, half * dst,
+ int64_t IW, int64_t IH, int64_t OW, int64_t OH, int64_t KW, int64_t KH, int64_t IC,
+ int64_t N, int64_t IC_IH_IW, int64_t IH_IW,
+ int s0,int s1,int p0,int p1,int d0,int d1, cudaStream_t stream) {
+
+ im2col_cuda<half>(x, dst, IW, IH, OW, OH, KW, KH, IC, N, IC_IH_IW, IH_IW, s0, s1, p0, p1, d0, d1, stream);
+}
+
+static void im2col_cuda_f32(const float * x, float * dst,
+ int64_t IW, int64_t IH, int64_t OW, int64_t OH, int64_t KW, int64_t KH, int64_t IC,
+ int64_t N, int64_t IC_IH_IW, int64_t IH_IW,
+ int s0,int s1,int p0,int p1,int d0,int d1, cudaStream_t stream) {
+
+ im2col_cuda<float>(x, dst, IW, IH, OW, OH, KW, KH, IC, N, IC_IH_IW, IH_IW, s0, s1, p0, p1, d0, d1, stream);
+}
+
+void ggml_cuda_op_im2col(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+ const ggml_tensor * src0 = dst->src[0];
+ const ggml_tensor * src1 = dst->src[1];
+ const float * src1_d = (const float *)src1->data;
+ float * dst_d = (float *)dst->data;
+ cudaStream_t stream = ctx.stream();
+
+ GGML_ASSERT(src1->type == GGML_TYPE_F32);
+ GGML_ASSERT( dst->type == GGML_TYPE_F16 || dst->type == GGML_TYPE_F32);
+
+ const int32_t s0 = ((const int32_t*)(dst->op_params))[0];
+ const int32_t s1 = ((const int32_t*)(dst->op_params))[1];
+ const int32_t p0 = ((const int32_t*)(dst->op_params))[2];
+ const int32_t p1 = ((const int32_t*)(dst->op_params))[3];
+ const int32_t d0 = ((const int32_t*)(dst->op_params))[4];
+ const int32_t d1 = ((const int32_t*)(dst->op_params))[5];
+
+ const bool is_2D = ((const int32_t*)(dst->op_params))[6] == 1;
+
+ const int64_t IC = src1->ne[is_2D ? 2 : 1];
+ const int64_t IH = is_2D ? src1->ne[1] : 1;
+ const int64_t IW = src1->ne[0];
+
+ const int64_t KH = is_2D ? src0->ne[1] : 1;
+ const int64_t KW = src0->ne[0];
+
+ const int64_t OH = is_2D ? dst->ne[2] : 1;
+ const int64_t OW = dst->ne[1];
+
+ const int64_t IC_IH_IW = src1->nb[is_2D ? 2 : 1] / 4; // nb is byte offset, src is type float32
+ const int64_t N = src1->ne[is_2D ? 3 : 2];
+ const int64_t IH_IW = src1->nb[is_2D ? 3 : 2] / 4; // nb is byte offset, src is type float32
+
+ if(dst->type == GGML_TYPE_F16) {
+ im2col_cuda_f16(src1_d, (half *) dst_d, IW, IH, OW, OH, KW, KH, IC, N, IC_IH_IW, IH_IW, s0, s1, p0, p1, d0, d1, stream);
+ } else {
+ im2col_cuda_f32(src1_d, (float *) dst_d, IW, IH, OW, OH, KW, KH, IC, N, IC_IH_IW, IH_IW, s0, s1, p0, p1, d0, d1, stream);
+ }
+}
+
+// [N*IC, ID, IH, IW] => [N*OD, OH, OW, IC * KD * KH * KW]
+template <typename T>
+static __global__ void im2col_3d_kernel(
+ const float * src, T * dst,
+ int64_t N, int64_t IC, int64_t ID, int64_t IH, int64_t IW, int64_t OC,
+ int64_t KD, int64_t KH, int64_t KW, int64_t OD, int64_t OH, int64_t OW,
+ int64_t OH_OW, int64_t KD_KH_KW, int64_t ID_IH_IW, int64_t KH_KW, int64_t IH_IW, int64_t IC_ID_IH_IW,
+ int64_t IC_KD_KH_KW, int64_t OW_KD_KH_KW, int64_t OD_OH_OW_IC_KD_KH_KW, int64_t OH_OW_IC_KD_KH_KW,
+ int64_t OW_IC_KD_KH_KW, int64_t N_OD_OH, int64_t OD_OH,
+ int64_t stride_q, int64_t stride_z, int64_t stride_y, int64_t stride_x,
+ int s0, int s1, int s2, int p0, int p1, int p2, int d0, int d1, int d2) {
+ const int64_t i = threadIdx.x + blockIdx.x * blockDim.x;
+ if (i >= IC_KD_KH_KW) {
+ return;
+ }
+ GGML_UNUSED(N); GGML_UNUSED(OC); GGML_UNUSED(OH_OW); GGML_UNUSED(OD); GGML_UNUSED(OW); GGML_UNUSED(KD); GGML_UNUSED(KH);
+ GGML_UNUSED(ID_IH_IW); GGML_UNUSED(IH_IW); GGML_UNUSED(IC_ID_IH_IW); GGML_UNUSED(OW_KD_KH_KW);
+
+ const int64_t iic = i / KD_KH_KW;
+ const int64_t ikd = (i - iic * KD_KH_KW) / KH_KW;
+ const int64_t ikh = (i - iic * KD_KH_KW - ikd * KH_KW) / KW;
+ const int64_t ikw = i % KW;
+
+ const int64_t iow = blockIdx.y;
+ for (int64_t iz = blockIdx.z; iz < N_OD_OH; iz+=MAX_GRIDDIM_Z) {
+ const int64_t in = iz / OD_OH;
+ const int64_t iod = (iz - in*OD_OH) / OH;
+ const int64_t ioh = iz % OH;
+
+ const int64_t iiw = iow * s0 + ikw * d0 - p0;
+ const int64_t iih = ioh * s1 + ikh * d1 - p1;
+ const int64_t iid = iod * s2 + ikd * d2 - p2;
+
+ const int64_t offset_dst = in*OD_OH_OW_IC_KD_KH_KW + iod*OH_OW_IC_KD_KH_KW + ioh*OW_IC_KD_KH_KW + iow*IC_KD_KH_KW + iic*KD_KH_KW + ikd * KH_KW + ikh*KW + ikw;
+
+ if (iih < 0 || iih >= IH || iiw < 0 || iiw >= IW || iid < 0 || iid >= ID) {
+ dst[offset_dst] = 0.0f;
+ } else {
+ const int64_t offset_src = ((in * IC + iic) * stride_q) + (iid * stride_z) + (iih * stride_y) + (iiw * stride_x);
+ dst[offset_dst] = src[offset_src];
+ }
+ }
+}
+
+// [N*IC, ID, IH, IW] => [N*OD, OH, OW, IC * KD * KH * KW]
+template <typename T>
+static void im2col_3d_cuda(const float * src, T* dst,
+ int64_t N, int64_t IC, int64_t ID, int64_t IH, int64_t IW, int64_t OC,
+ int64_t KD, int64_t KH, int64_t KW, int64_t OD, int64_t OH, int64_t OW,
+ int64_t stride_q, int64_t stride_z, int64_t stride_y, int64_t stride_x,
+ int s0, int s1, int s2, int p0, int p1, int p2, int d0, int d1, int d2, cudaStream_t stream) {
+ const int64_t OH_OW = OH*OW;
+ const int64_t KD_KH_KW = KD*KH*KW;
+ const int64_t ID_IH_IW = ID*IH*IW;
+ const int64_t KH_KW = KH*KW;
+ const int64_t IH_IW = IH*IW;
+ const int64_t IC_KD_KH_KW = IC*KD*KH*KW;
+ const int64_t OW_KD_KH_KW = OW*KD*KH*KW;
+ const int64_t N_OD_OH = N*OD*OH;
+ const int64_t OD_OH = OD*OH;
+ const int64_t IC_ID_IH_IW = IC*ID*IH*IW;
+ const int64_t OD_OH_OW_IC_KD_KH_KW = OD*OH*OW*IC*KD*KH*KW;
+ const int64_t OH_OW_IC_KD_KH_KW = OH*OW*IC*KD*KH*KW;
+ const int64_t OW_IC_KD_KH_KW = OW*IC*KD*KH*KW;
+ const int64_t num_blocks = (IC_KD_KH_KW + CUDA_IM2COL_BLOCK_SIZE - 1) / CUDA_IM2COL_BLOCK_SIZE;
+ dim3 block_nums(num_blocks, OW, MIN(N_OD_OH, MAX_GRIDDIM_Z));
+ im2col_3d_kernel<<<block_nums, MIN(IC_KD_KH_KW, CUDA_IM2COL_BLOCK_SIZE) , 0, stream>>>(src, dst, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW,
+ OH_OW, KD_KH_KW, ID_IH_IW, KH_KW, IH_IW, IC_ID_IH_IW,
+ IC_KD_KH_KW, OW_KD_KH_KW, OD_OH_OW_IC_KD_KH_KW,
+ OH_OW_IC_KD_KH_KW, OW_IC_KD_KH_KW, N_OD_OH, OD_OH,
+ stride_q, stride_z, stride_y, stride_x,
+ s0, s1, s2, p0, p1, p2, d0, d1, d2);
+}
+
+static void im2col_3d_cuda_f16(const float * src, half * dst,
+ int64_t N, int64_t IC, int64_t ID, int64_t IH, int64_t IW, int64_t OC,
+ int64_t KD, int64_t KH, int64_t KW, int64_t OD, int64_t OH, int64_t OW,
+ int64_t stride_q, int64_t stride_z, int64_t stride_y, int64_t stride_x,
+ int s0, int s1, int s2, int p0, int p1, int p2, int d0, int d1, int d2, cudaStream_t stream) {
+
+ im2col_3d_cuda<half>(src, dst, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW,
+ stride_q, stride_z, stride_y, stride_x,
+ s0, s1, s2, p0, p1, p2, d0, d1, d2, stream);
+}
+
+static void im2col_3d_cuda_f32(const float * src, float * dst,
+ int64_t N, int64_t IC, int64_t ID, int64_t IH, int64_t IW, int64_t OC,
+ int64_t KD, int64_t KH, int64_t KW, int64_t OD, int64_t OH, int64_t OW,
+ int64_t stride_q, int64_t stride_z, int64_t stride_y, int64_t stride_x,
+ int s0, int s1, int s2, int p0, int p1, int p2, int d0, int d1, int d2, cudaStream_t stream) {
+
+ im2col_3d_cuda<float>(src, dst, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW,
+ stride_q, stride_z, stride_y, stride_x,
+ s0, s1, s2, p0, p1, p2, d0, d1, d2, stream);
+}
+
+void ggml_cuda_op_im2col_3d(ggml_backend_cuda_context & ctx, ggml_tensor * dst) {
+ const ggml_tensor * src0 = dst->src[0];
+ const ggml_tensor * src1 = dst->src[1];
+ const float * src1_d = (const float *)src1->data;
+ float * dst_d = (float *)dst->data;
+ cudaStream_t stream = ctx.stream();
+
+ GGML_ASSERT(src1->type == GGML_TYPE_F32);
+ GGML_ASSERT( dst->type == GGML_TYPE_F16 || dst->type == GGML_TYPE_F32);
+
+ GGML_TENSOR_BINARY_OP_LOCALS
+
+ const int32_t s0 = ((const int32_t *)(dst->op_params))[0];
+ const int32_t s1 = ((const int32_t *)(dst->op_params))[1];
+ const int32_t s2 = ((const int32_t *)(dst->op_params))[2];
+ const int32_t p0 = ((const int32_t *)(dst->op_params))[3];
+ const int32_t p1 = ((const int32_t *)(dst->op_params))[4];
+ const int32_t p2 = ((const int32_t *)(dst->op_params))[5];
+ const int32_t d0 = ((const int32_t *)(dst->op_params))[6];
+ const int32_t d1 = ((const int32_t *)(dst->op_params))[7];
+ const int32_t d2 = ((const int32_t *)(dst->op_params))[8];
+ const int32_t IC = ((const int32_t *)(dst->op_params))[9];
+
+ const int64_t N = ne13 / IC;
+ const int64_t ID = ne12;
+ const int64_t IH = ne11;
+ const int64_t IW = ne10;
+
+ const int64_t OC = ne03 / IC;
+ const int64_t KD = ne02;
+ const int64_t KH = ne01;
+ const int64_t KW = ne00;
+
+ const int64_t OD = ne3 / N;
+ const int64_t OH = ne2;
+ const int64_t OW = ne1;
+
+ const size_t es = ggml_element_size(src1);
+ const int64_t stride_x = src1->nb[0] / es;
+ const int64_t stride_y = src1->nb[1] / es;
+ const int64_t stride_z = src1->nb[2] / es;
+ const int64_t stride_q = src1->nb[3] / es;
+
+ if(dst->type == GGML_TYPE_F16) {
+ im2col_3d_cuda_f16(src1_d, (half *) dst_d, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW,
+ stride_q, stride_z, stride_y, stride_x,
+ s0, s1, s2, p0, p1, p2, d0, d1, d2, stream);
+ } else {
+ im2col_3d_cuda_f32(src1_d, (float *) dst_d, N, IC, ID, IH, IW, OC, KD, KH, KW, OD, OH, OW,
+ stride_q, stride_z, stride_y, stride_x,
+ s0, s1, s2, p0, p1, p2, d0, d1, d2, stream);
+ }
+}