CS348Project/llama.cpp
5
0
Fork 0
mirror of https://github.com/ggml-org/llama.cpp.git synced 2025-10-27 08:21:30 +00:00
Code Issues Packages Projects Releases Wiki Activity

CUDA: fix GET_ROWS for large tensors (#15882)

Browse Source
This commit is contained in:
Johannes Gäßler
2025-09-09 08:11:01 +02:00
committed by GitHub
parent c252ce67c4
commit 550cf726e1
2 changed files with 41 additions and 43 deletions
Download Patch File Download Diff File Expand all files Collapse all files

80
ggml/src/ggml-cuda/getrows.cu
View File

@@ -2,39 +2,39 @@
#include "dequantize.cuh" #include "dequantize.cuh"
#include "convert.cuh" #include "convert.cuh"
#define MAX_GRIDDIM_Y 65535
template<int qk, int qr, dequantize_kernel_t dequantize_kernel, typename dst_t> template<int qk, int qr, dequantize_kernel_t dequantize_kernel, typename dst_t>
static __global__ void k_get_rows( static __global__ void k_get_rows(
const void * __restrict__ src0, const int32_t * __restrict__ src1, dst_t * __restrict__ dst, const void * __restrict__ src0, const int32_t * __restrict__ src1, dst_t * __restrict__ dst,
const int64_t ne00, /*const int64_t ne01, const int64_t ne02, const int64_t ne03,*/ const int64_t ne00, /*const int64_t ne01, const int64_t ne02, const int64_t ne03,*/
/*const int64_t ne10, const int64_t ne11,*/ const int64_t ne12, /*const int64_t ne13,*/ /*const int64_t ne10,*/ const int64_t ne11, const int64_t ne12, /*const int64_t ne13,*/
/*const size_t s0,*/ const size_t s1, const size_t s2, const size_t s3, /*const size_t s0,*/ const size_t s1, const size_t s2, const size_t s3,
/*const size_t nb00,*/ const size_t nb01, const size_t nb02, const size_t nb03, /*const size_t nb00,*/ const size_t nb01, const size_t nb02, const size_t nb03,
const size_t s10, const size_t s11, const size_t s12/*, const size_t s13*/) { const size_t s10, const size_t s11, const size_t s12/*, const size_t s13*/) {
for (int64_t i00 = 2*(blockIdx.y*blockDim.x + threadIdx.x); i00 < ne00; i00 += gridDim.y*blockDim.x) { for (int64_t z = blockIdx.z; z < ne11*ne12; z += gridDim.z) {
// The x and y dimensions of the grid are swapped because the maximum allowed grid size for x is higher. for (int64_t i00 = 2*(blockIdx.y*blockDim.x + threadIdx.x); i00 < ne00; i00 += gridDim.y*blockDim.x) {
const int i10 = blockIdx.x; // The x and y dimensions of the grid are swapped because the maximum allowed grid size for x is higher.
const int i11 = blockIdx.z / ne12; const int i10 = blockIdx.x;
const int i12 = blockIdx.z % ne12; const int i11 = z / ne12; // TODO fastdiv
const int i12 = z % ne12;
const int i01 = src1[i10*s10 + i11*s11 + i12*s12]; const int i01 = src1[i10*s10 + i11*s11 + i12*s12];
dst_t * dst_row = dst + i10*s1 + i11*s2 + i12*s3; dst_t * dst_row = dst + i10*s1 + i11*s2 + i12*s3;
const void * src0_row = (const char *) src0 + i01*nb01 + i11*nb02 + i12*nb03; const void * src0_row = (const char *) src0 + i01*nb01 + i11*nb02 + i12*nb03;
const int ib = i00/qk; // block index const int ib = i00/qk; // block index
const int iqs = (i00%qk)/qr; // quant index const int iqs = (i00%qk)/qr; // quant index
const int iybs = i00 - i00%qk; // dst block start index const int iybs = i00 - i00%qk; // dst block start index
const int y_offset = qr == 1 ? 1 : qk/2; const int y_offset = qr == 1 ? 1 : qk/2;
// dequantize // dequantize
float2 v; float2 v;
dequantize_kernel(src0_row, ib, iqs, v); dequantize_kernel(src0_row, ib, iqs, v);
dst_row[iybs + iqs + 0] = ggml_cuda_cast<dst_t>(v.x); dst_row[iybs + iqs + 0] = ggml_cuda_cast<dst_t>(v.x);
dst_row[iybs + iqs + y_offset] = ggml_cuda_cast<dst_t>(v.y); dst_row[iybs + iqs + y_offset] = ggml_cuda_cast<dst_t>(v.y);
}
} }
} }
@@ -42,27 +42,29 @@ template<typename src0_t, typename dst_t>
static __global__ void k_get_rows_float( static __global__ void k_get_rows_float(
const src0_t * __restrict__ src0, const int32_t * __restrict__ src1, dst_t * __restrict__ dst, const src0_t * __restrict__ src0, const int32_t * __restrict__ src1, dst_t * __restrict__ dst,
const int64_t ne00, /*const int64_t ne01, const int64_t ne02, const int64_t ne03,*/ const int64_t ne00, /*const int64_t ne01, const int64_t ne02, const int64_t ne03,*/
/*const int64_t ne10, const int64_t ne11,*/ const int64_t ne12, /*const int64_t ne13,*/ /*const int64_t ne10,*/ const int64_t ne11, const int64_t ne12, /*const int64_t ne13,*/
/*const size_t s0,*/ const size_t s1, const size_t s2, const size_t s3, /*const size_t s0,*/ const size_t s1, const size_t s2, const size_t s3,
/*const size_t nb00,*/ const size_t nb01, const size_t nb02, const size_t nb03, /*const size_t nb00,*/ const size_t nb01, const size_t nb02, const size_t nb03,
const size_t s10, const size_t s11, const size_t s12/*, const size_t s13*/) { const size_t s10, const size_t s11, const size_t s12/*, const size_t s13*/) {
for (int64_t i00 = blockIdx.y*blockDim.x + threadIdx.x; i00 < ne00; i00 += gridDim.y*blockDim.x) { for (int64_t z = blockIdx.z; z < ne11*ne12; z += gridDim.z) {
// The x and y dimensions of the grid are swapped because the maximum allowed grid size for x is higher. for (int64_t i00 = blockIdx.y*blockDim.x + threadIdx.x; i00 < ne00; i00 += gridDim.y*blockDim.x) {
const int i10 = blockIdx.x; // The x and y dimensions of the grid are swapped because the maximum allowed grid size for x is higher.
const int i11 = blockIdx.z / ne12; const int i10 = blockIdx.x;
const int i12 = blockIdx.z % ne12; const int i11 = z / ne12; // TODO fastdiv
const int i12 = z % ne12;
if (i00 >= ne00) { if (i00 >= ne00) {
return; return;
}
const int i01 = src1[i10*s10 + i11*s11 + i12*s12];
dst_t * dst_row = dst + i10*s1 + i11*s2 + i12*s3;
const src0_t * src0_row = (const src0_t *)((const char *) src0 + i01*nb01 + i11*nb02 + i12*nb03);
dst_row[i00] = ggml_cuda_cast<dst_t>(src0_row[i00]);
} }
const int i01 = src1[i10*s10 + i11*s11 + i12*s12];
dst_t * dst_row = dst + i10*s1 + i11*s2 + i12*s3;
const src0_t * src0_row = (const src0_t *)((const char *) src0 + i01*nb01 + i11*nb02 + i12*nb03);
dst_row[i00] = ggml_cuda_cast<dst_t>(src0_row[i00]);
} }
} }
@@ -98,7 +100,7 @@ static void get_rows_cuda_q(
cudaStream_t stream) { cudaStream_t stream) {
const dim3 block_dims(CUDA_GET_ROWS_BLOCK_SIZE, 1, 1); const dim3 block_dims(CUDA_GET_ROWS_BLOCK_SIZE, 1, 1);
const int block_num_y = (ne00 + 2*CUDA_GET_ROWS_BLOCK_SIZE - 1) / (2*CUDA_GET_ROWS_BLOCK_SIZE); const int block_num_y = (ne00 + 2*CUDA_GET_ROWS_BLOCK_SIZE - 1) / (2*CUDA_GET_ROWS_BLOCK_SIZE);
const dim3 block_nums(ne10, MIN(block_num_y, MAX_GRIDDIM_Y), ne11*ne12); const dim3 block_nums(ne10, MIN(block_num_y, UINT16_MAX), MIN(ne11*ne12, UINT16_MAX));
// strides in elements // strides in elements
// const size_t s0 = nb0 / sizeof(dst_t); // const size_t s0 = nb0 / sizeof(dst_t);
@@ -116,7 +118,7 @@ static void get_rows_cuda_q(
k_get_rows<qk, qr, dq><<<block_nums, block_dims, 0, stream>>>( k_get_rows<qk, qr, dq><<<block_nums, block_dims, 0, stream>>>(
src0_d, src1_d, dst_d, src0_d, src1_d, dst_d,
ne00, /*ne01, ne02, ne03,*/ ne00, /*ne01, ne02, ne03,*/
/*ne10, ne11,*/ ne12, /*ne13,*/ /*ne10,*/ ne11, ne12, /*ne13,*/
/* s0,*/ s1, s2, s3, /* s0,*/ s1, s2, s3,
/* nb00,*/ nb01, nb02, nb03, /* nb00,*/ nb01, nb02, nb03,
s10, s11, s12/*, s13*/); s10, s11, s12/*, s13*/);
@@ -131,7 +133,7 @@ static void get_rows_cuda_float(
cudaStream_t stream) { cudaStream_t stream) {
const dim3 block_dims(CUDA_GET_ROWS_BLOCK_SIZE, 1, 1); const dim3 block_dims(CUDA_GET_ROWS_BLOCK_SIZE, 1, 1);
const int block_num_y = (ne00 + CUDA_GET_ROWS_BLOCK_SIZE - 1) / CUDA_GET_ROWS_BLOCK_SIZE; const int block_num_y = (ne00 + CUDA_GET_ROWS_BLOCK_SIZE - 1) / CUDA_GET_ROWS_BLOCK_SIZE;
const dim3 block_nums(ne10, MIN(block_num_y, MAX_GRIDDIM_Y), ne11*ne12); const dim3 block_nums(ne10, MIN(block_num_y, UINT16_MAX), MIN(ne11*ne12, UINT16_MAX));
// strides in elements // strides in elements
// const size_t s0 = nb0 / sizeof(dst_t); // const size_t s0 = nb0 / sizeof(dst_t);
@@ -147,7 +149,7 @@ static void get_rows_cuda_float(
k_get_rows_float<<<block_nums, block_dims, 0, stream>>>( k_get_rows_float<<<block_nums, block_dims, 0, stream>>>(
src0_d, src1_d, dst_d, src0_d, src1_d, dst_d,
ne00, /*ne01, ne02, ne03,*/ ne00, /*ne01, ne02, ne03,*/
/*ne10, ne11,*/ ne12, /*ne13,*/ /*ne10,*/ ne11, ne12, /*ne13,*/
/* s0,*/ s1, s2, s3, /* s0,*/ s1, s2, s3,
/* nb00,*/ nb01, nb02, nb03, /* nb00,*/ nb01, nb02, nb03,
s10, s11, s12/*, s13*/); s10, s11, s12/*, s13*/);

4
ggml/src/ggml-cuda/ggml-cuda.cu
View File

@@ -3393,10 +3393,6 @@ static bool ggml_backend_cuda_device_supports_op(ggml_backend_dev_t dev, const g
return op->type == GGML_TYPE_F32 && op->src[0]->type == GGML_TYPE_F32 && op->src[1]->type == GGML_TYPE_F32; return op->type == GGML_TYPE_F32 && op->src[0]->type == GGML_TYPE_F32 && op->src[1]->type == GGML_TYPE_F32;
case GGML_OP_GET_ROWS: case GGML_OP_GET_ROWS:
{ {
// FIXME: https://github.com/ggml-org/llama.cpp/pull/15868
if (op->src[1]->ne[1]*op->src[1]->ne[2] > 65535) {
return false;
}
switch (op->src[0]->type) { switch (op->src[0]->type) {
case GGML_TYPE_F16: case GGML_TYPE_F16:
case GGML_TYPE_F32: case GGML_TYPE_F32: