haraldwolff/llama.cpp
1
0
Fork 0
Code Issues Pull requests Packages Projects Releases Wiki Activity

cuda : add gelu support

Browse source
This commit is contained in:
Georgi Gerganov 2023-07-12 20:26:18 +03:00
parent 4e7464ef88
commit 680e6f9177
1 changed files with 53 additions and 0 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

53
ggml-cuda.cu
View file

@ -212,6 +212,7 @@ static_assert(sizeof(block_q6_K) == sizeof(ggml_fp16_t) + 13*QK_K/16, "wrong q6_
#define CUDA_ADD_BLOCK_SIZE 256
#define CUDA_MUL_BLOCK_SIZE 256
#define CUDA_GELU_BLOCK_SIZE 256
#define CUDA_SILU_BLOCK_SIZE 256
#define CUDA_CPY_BLOCK_SIZE 32
#define CUDA_SCALE_BLOCK_SIZE 256
@ -266,6 +267,20 @@ static __global__ void mul_f32(const float * x, const float * y, float * dst, co
dst[i] = x[i] * y[i%ky];
}
static const float GELU_COEF_A = 0.044715f;
static const float SQRT_2_OVER_PI = 0.79788456080286535587989211986876f;
static __global__ void gelu_f32(const float * x, float * dst, const int k) {
const int i = blockDim.x*blockIdx.x + threadIdx.x;
if (i >= k) {
return;
}
float xi = x[i];
dst[i] = 0.5f*xi*(1.0f + tanhf(SQRT_2_OVER_PI*xi*(1.0f + GELU_COEF_A*xi*xi)));
}
static __global__ void silu_f32(const float * x, float * dst, const int k) {
const int i = blockDim.x*blockIdx.x + threadIdx.x;
@ -1733,6 +1748,11 @@ static void mul_f32_cuda(const float * x, const float * y, float * dst, const in
mul_f32<<<num_blocks, CUDA_MUL_BLOCK_SIZE, 0, stream>>>(x, y, dst, kx, ky);
}
static void gelu_f32_cuda(const float * x, float * dst, const int k, cudaStream_t stream) {
const int num_blocks = (k + CUDA_GELU_BLOCK_SIZE - 1) / CUDA_GELU_BLOCK_SIZE;
gelu_f32<<<num_blocks, CUDA_GELU_BLOCK_SIZE, 0, stream>>>(x, dst, k);
}
static void silu_f32_cuda(const float * x, float * dst, const int k, cudaStream_t stream) {
const int num_blocks = (k + CUDA_SILU_BLOCK_SIZE - 1) / CUDA_SILU_BLOCK_SIZE;
silu_f32<<<num_blocks, CUDA_SILU_BLOCK_SIZE, 0, stream>>>(x, dst, k);
@ -2327,6 +2347,28 @@ inline void ggml_cuda_op_mul(
(void) i02;
}
inline void ggml_cuda_op_gelu(
const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, char * src0_ddq_i,
float * src0_ddf_i, float * src1_ddf_i, float * dst_ddf_i, int64_t i02, int64_t i01_low, int64_t i01_high, int i1,
cudaStream_t & cudaStream_main){
GGML_ASSERT(src0_ddf_i != nullptr);
GGML_ASSERT(dst_ddf_i != nullptr);
const int64_t ne00 = src0->ne[0];
const int64_t i01_diff = i01_high - i01_low;
// compute
gelu_f32_cuda(src0_ddf_i, dst_ddf_i, ne00*i01_diff, cudaStream_main);
(void) src1;
(void) dst;
(void) src0_ddq_i;
(void) src1_ddf_i;
(void) i02;
(void) i1;
}
inline void ggml_cuda_op_silu(
const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, char * src0_ddq_i,
float * src0_ddf_i, float * src1_ddf_i, float * dst_ddf_i, int64_t i02, int64_t i01_low, int64_t i01_high, int i1,
@ -2986,6 +3028,11 @@ void ggml_cuda_mul(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tens
ggml_cuda_op(src0, src1, dst, ggml_cuda_op_mul, true, false); // TODO ggml_cuda_op needs modification for flatten
}
void ggml_cuda_gelu(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
GGML_ASSERT(src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32);
ggml_cuda_op(src0, src1, dst, ggml_cuda_op_gelu, true, true);
}
void ggml_cuda_silu(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
GGML_ASSERT(src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32);
ggml_cuda_op(src0, src1, dst, ggml_cuda_op_silu, true, true);
@ -3382,6 +3429,12 @@ bool ggml_cuda_compute_forward(struct ggml_compute_params * params, struct ggml_
}
func = ggml_cuda_mul;
break;
case GGML_OP_GELU:
if (!any_on_device) {
return false;
}
func = ggml_cuda_gelu;
break;
case GGML_OP_SILU:
if (!any_on_device) {
return false;