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ggml-cuda : fix f16 mul mat #3961

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Merged
merged 2 commits into from
Nov 5, 2023
Merged

ggml-cuda : fix f16 mul mat #3961

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d4d45c7
ggml-cuda : fix f16 mul mat
slaren Nov 5, 2023
8bcdb88
silence common.cpp warning (bonus)
slaren Nov 5, 2023
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2 changes: 1 addition & 1 deletion common/common.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -101,8 +101,8 @@ void process_escapes(std::string& input) {
input[output_idx++] = char(val);
break;
}
// Intentionally fall through to default.
}
// fall through
default: input[output_idx++] = '\\';
input[output_idx++] = input[input_idx]; break;
}
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8 changes: 5 additions & 3 deletions ggml-cuda.cu
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Expand Up @@ -7414,6 +7414,8 @@ static void ggml_cuda_mul_mat(const ggml_tensor * src0, const ggml_tensor * src1
(src1->backend == GGML_BACKEND_GPU) &&
( dst->backend == GGML_BACKEND_GPU);

const bool split = src0->backend == GGML_BACKEND_GPU_SPLIT;

int64_t min_compute_capability = INT_MAX;
for (int64_t id = 0; id < g_device_count; ++id) {
if (min_compute_capability > g_compute_capabilities[id] && g_tensor_split[id] < (id + 1 < g_device_count ? g_tensor_split[id + 1] : 1.0f)) {
Expand All @@ -7435,13 +7437,13 @@ static void ggml_cuda_mul_mat(const ggml_tensor * src0, const ggml_tensor * src1
//printf("src0 is contiguous %d, transposed %d, type = %s, name = %s\n", ggml_is_contiguous(src0), ggml_is_transposed(src0), ggml_type_name(src0->type), src0->name);
//printf("src1 is contiguous %d, transposed %d, type = %s, name = %s\n", ggml_is_contiguous(src1), ggml_is_transposed(src1), ggml_type_name(src1->type), src1->name);

if (all_on_device && !use_tensor_cores && src0->type == GGML_TYPE_F16 && ggml_is_permuted(src0) && ggml_is_permuted(src1) && src1->ne[1] == 1) {
if (!split && all_on_device && !use_tensor_cores && src0->type == GGML_TYPE_F16 && ggml_is_permuted(src0) && ggml_is_permuted(src1) && src1->ne[1] == 1) {
// KQ single-batch
ggml_cuda_mul_mat_vec_p021(src0, src1, dst);
} else if (all_on_device && !use_tensor_cores && src0->type == GGML_TYPE_F16 && !ggml_is_contiguous(src0) && !ggml_is_transposed(src1) && src1->ne[1] == 1) {
} else if (!split && all_on_device && !use_tensor_cores && src0->type == GGML_TYPE_F16 && !ggml_is_contiguous(src0) && !ggml_is_transposed(src1) && src1->ne[1] == 1) {
// KQV single-batch
ggml_cuda_mul_mat_vec_nc(src0, src1, dst);
} else if (all_on_device && use_tensor_cores && src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F32 && !ggml_is_transposed(src0) && !ggml_is_transposed(src1)) {
} else if (!split && all_on_device && use_tensor_cores && src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F32 && !ggml_is_transposed(src0) && !ggml_is_transposed(src1)) {
// KQ + KQV multi-batch
ggml_cuda_mul_mat_mat_batched_cublas(src0, src1, dst);
} else if (src0->type == GGML_TYPE_F32) {
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