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Merge branch 'upstream' into concedo_experimental

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# Conflicts:
#	docs/build.md
#	ggml/src/ggml.c
#	tests/test-backend-ops.cpp
This commit is contained in:
Concedo 2024-08-02 10:44:22 +08:00
commit 804d3520a9
5 changed files with 37 additions and 12 deletions
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20
ggml/src/ggml-cuda.cu
View file

@ -132,7 +132,22 @@ static cudaError_t ggml_cuda_device_malloc(void ** ptr, size_t size, int device)
}
return res;
#else
#if !defined(GGML_USE_HIPBLAS) && !defined(GGML_USE_MUSA)
cudaError_t err;
if (getenv("GGML_CUDA_ENABLE_UNIFIED_MEMORY") != nullptr)
{
err = cudaMallocManaged(ptr, size);
}
else
{
err = cudaMalloc(ptr, size);
}
return err;
#else
return cudaMalloc(ptr, size);
#endif // !defined(GGML_USE_HIPBLAS) && !defined(GGML_USE_MUSA)
#endif
}
@ -1885,10 +1900,9 @@ static void ggml_cuda_mul_mat_batched_cublas(ggml_backend_cuda_context & ctx, co
static void ggml_cuda_mul_mat(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
const bool split = ggml_backend_buffer_is_cuda_split(src0->buffer);
bool use_dequantize_mul_mat_vec = (ggml_is_quantized(src0->type) || src0->type == GGML_TYPE_F16)
bool use_dequantize_mul_mat_vec = ggml_cuda_dmmv_type_supported(src0->type)
&& src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32
&& src0->ne[0] % GGML_CUDA_DMMV_X == 0 && src0->ne[0] >= GGML_CUDA_DMMV_X*2
&& src1->ne[1] == 1;
&& src0->ne[0] % (GGML_CUDA_DMMV_X*2) == 0 && src1->ne[1] == 1;
bool use_mul_mat_vec_q = ggml_is_quantized(src0->type)
&& src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32
&& src1->ne[1] <= MMVQ_MAX_BATCH_SIZE;

21
ggml/src/ggml-cuda/dmmv.cu
View file

@ -500,7 +500,7 @@ static __global__ void dequantize_mul_mat_vec(const void * __restrict__ vx, cons
}
static void dequantize_mul_mat_vec_q4_0_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
GGML_ASSERT(ncols % (GGML_CUDA_DMMV_X*2) == 0);
const int block_num_y = (nrows + GGML_CUDA_MMV_Y - 1) / GGML_CUDA_MMV_Y;
// the number of rows may exceed maximum grid size in the y or z dimensions, use the x dimension instead
const dim3 block_nums(block_num_y, 1, 1);
@ -510,7 +510,7 @@ static void dequantize_mul_mat_vec_q4_0_cuda(const void * vx, const dfloat * y,
}
static void dequantize_mul_mat_vec_q4_1_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
GGML_ASSERT(ncols % (GGML_CUDA_DMMV_X*2) == 0);
const int block_num_y = (nrows + GGML_CUDA_MMV_Y - 1) / GGML_CUDA_MMV_Y;
const dim3 block_nums(block_num_y, 1, 1);
const dim3 block_dims(WARP_SIZE, GGML_CUDA_MMV_Y, 1);
@ -519,7 +519,7 @@ static void dequantize_mul_mat_vec_q4_1_cuda(const void * vx, const dfloat * y,
}
static void dequantize_mul_mat_vec_q5_0_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
GGML_ASSERT(ncols % (GGML_CUDA_DMMV_X*2) == 0);
const int block_num_y = (nrows + GGML_CUDA_MMV_Y - 1) / GGML_CUDA_MMV_Y;
const dim3 block_nums(block_num_y, 1, 1);
const dim3 block_dims(WARP_SIZE, GGML_CUDA_MMV_Y, 1);
@ -528,7 +528,7 @@ static void dequantize_mul_mat_vec_q5_0_cuda(const void * vx, const dfloat * y,
}
static void dequantize_mul_mat_vec_q5_1_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
GGML_ASSERT(ncols % (GGML_CUDA_DMMV_X*2) == 0);
const int block_num_y = (nrows + GGML_CUDA_MMV_Y - 1) / GGML_CUDA_MMV_Y;
const dim3 block_nums(block_num_y, 1, 1);
const dim3 block_dims(WARP_SIZE, GGML_CUDA_MMV_Y, 1);
@ -537,7 +537,7 @@ static void dequantize_mul_mat_vec_q5_1_cuda(const void * vx, const dfloat * y,
}
static void dequantize_mul_mat_vec_q8_0_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
GGML_ASSERT(ncols % (GGML_CUDA_DMMV_X*2) == 0);
const int block_num_y = (nrows + GGML_CUDA_MMV_Y - 1) / GGML_CUDA_MMV_Y;
const dim3 block_nums(block_num_y, 1, 1);
const dim3 block_dims(WARP_SIZE, GGML_CUDA_MMV_Y, 1);
@ -588,7 +588,7 @@ static void dequantize_mul_mat_vec_q6_K_cuda(const void * vx, const float * y, f
}
static void convert_mul_mat_vec_f16_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {
GGML_ASSERT(ncols % GGML_CUDA_DMMV_X == 0);
GGML_ASSERT(ncols % (GGML_CUDA_DMMV_X*2) == 0);
const int block_num_y = (nrows + GGML_CUDA_MMV_Y - 1) / GGML_CUDA_MMV_Y;
const dim3 block_nums(block_num_y, 1, 1);
const dim3 block_dims(WARP_SIZE, GGML_CUDA_MMV_Y, 1);
@ -672,3 +672,12 @@ void ggml_cuda_op_dequantize_mul_mat_vec(
GGML_UNUSED(src1_ncols);
GGML_UNUSED(src1_padded_row_size);
}
bool ggml_cuda_dmmv_type_supported(ggml_type src0_type) {
return src0_type == GGML_TYPE_Q4_0 || src0_type == GGML_TYPE_Q4_1 ||
src0_type == GGML_TYPE_Q5_0 || src0_type == GGML_TYPE_Q5_1 ||
src0_type == GGML_TYPE_Q8_0 || src0_type == GGML_TYPE_Q2_K ||
src0_type == GGML_TYPE_Q3_K || src0_type == GGML_TYPE_Q4_K ||
src0_type == GGML_TYPE_Q5_K || src0_type == GGML_TYPE_Q6_K ||
src0_type == GGML_TYPE_F16;
}

2
ggml/src/ggml-cuda/dmmv.cuh
View file

@ -16,3 +16,5 @@ void ggml_cuda_op_dequantize_mul_mat_vec(
const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, const char * src0_dd_i, const float * src1_ddf_i,
const char * src1_ddq_i, float * dst_dd_i, const int64_t row_low, const int64_t row_high, const int64_t src1_ncols,
const int64_t src1_padded_row_size, cudaStream_t stream);
bool ggml_cuda_dmmv_type_supported(ggml_type src0_type);

2
ggml/src/ggml-sycl/mmvq.cpp
View file

@ -902,7 +902,7 @@ static void mul_mat_vec_iq4_nl_q8_1_sycl(const void *vx, const void *vy,
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
[[intel::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_iq4_nl_q8_1<QK4_NL, QI4_NL, block_iq4_nl, 1>(
mul_mat_vec_q_iq4_nl_q8_1<QK4_NL, QI4_NL, block_iq4_nl, 2>(
vx, vy, dst, ncols, nrows, item_ct1);
});
});

4
ggml/src/ggml.c
View file

@ -185,8 +185,8 @@ static void ggml_print_backtrace_symbols(void) {
fprintf(stderr, "%d: %p %s\n", idx, addr, symbol);
}
}
#elif defined(__linux__)
// #include <execinfo.h>
#elif defined(__linux__) && defined(__GLIBC__)
//#include <execinfo.h>
static void ggml_print_backtrace_symbols(void) {
// void * trace[100];
// int nptrs = backtrace(trace, sizeof(trace)/sizeof(trace[0]));