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

CUDA POOL2D

Browse source
This commit is contained in:
zhangjidong 2024-01-29 10:31:41 +08:00
parent c29a855453
commit ba5592c653
2 changed files with 82 additions and 16 deletions
Download patch file Download diff file Expand all files Collapse all files

82
ggml-cuda.cu
View file

@ -530,6 +530,7 @@ static_assert(sizeof(block_iq2_xs) == sizeof(ggml_fp16_t) + QK_K/8*sizeof(uint16
#define CUDA_PAD_BLOCK_SIZE 256
#define CUDA_ACC_BLOCK_SIZE 256
#define CUDA_IM2COL_BLOCK_SIZE 256
#define CUDA_POOL2D_BLOCK_SIZE 256
#define CUDA_Q8_0_NE_ALIGN 2048
@ -6033,6 +6034,48 @@ static __global__ void im2col_kernel(
}
}
template <typename Ti, typename To>
static __global__ void pool2d_nchw_kernel(
const int ih, const int iw, const int oh, const int ow,
const int kh, const int kw, const int sh, const int sw,
const int ph, const int pw,
const Ti* src, To* dst, const enum ggml_op_pool op) {
int idx = threadIdx.x + blockIdx.x * blockDim.x;
const int I_HW = ih * iw;
const int O_HW = oh * ow;
const int nc = idx / (oh * ow);
const int cur_oh = idx % (oh * ow) / ow;
const int cur_ow = idx % (oh * ow) % ow;
const Ti* i_ptr = src + nc * I_HW;
To* o_ptr = dst + nc * O_HW;
const int start_h = cur_oh * sh - ph;
const int bh = max(0, start_h);
const int eh = min(ih, start_h + kh);
const int start_w = ow * sw - pw;
const int bw = max(0, start_w);
const int ew = min(iw, start_w + kw);
const To scale = 1. / ((eh - bh) * (ew - bw));
To res = 0;
switch(op){
case GGML_OP_POOL_AVG: res = 0; break;
case GGML_OP_POOL_MAX: res = -FLT_MAX; break;
}
for(int i = bh; i < eh; i += 1){
for(int j = bw; j < ew; j += 1){
#if __CUDA_ARCH__ >= 350
Ti cur = __ldg(i_ptr + i * iw + j);
#else
Ti cur = i_ptr[i * iw + j];
#endif
switch(op){
case GGML_OP_POOL_AVG: res += cur * scale; break;
case GGML_OP_POOL_MAX: res = max(res, (To)cur); break;
}
}
}
o_ptr[cur_oh * ow + cur_ow] = res;
}
template<int qk, int qr, dequantize_kernel_t dq>
static void get_rows_cuda(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst,
const void * src0_dd, const int32_t * src1_dd, float * dst_dd, cudaStream_t stream) {
@ -8670,6 +8713,38 @@ static void ggml_cuda_op_alibi(
(void) src1_dd;
}
static void ggml_cuda_op_pool2d(
const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst,
const float * src0_dd, const float * src1_dd, float * dst_dd, cudaStream_t main_stream) {
const int32_t * opts = (const int32_t *)dst->op_params;
enum ggml_op_pool op = static_cast<ggml_op_pool>(opts[0]);
const int k0 = opts[1];
const int k1 = opts[2];
const int s0 = opts[3];
const int s1 = opts[4];
const int p0 = opts[5];
const int p1 = opts[6];
const int64_t IC = src0->ne[2];
const int64_t IH = src0->ne[1];
const int64_t IW = src0->ne[0];
const int64_t N = dst->ne[3];
const int64_t OC = dst->ne[2];
const int64_t OH = dst->ne[1];
const int64_t OW = dst->ne[0];
const int parallel_elements = N * OC * OH * OW;
const int num_blocks = (parallel_elements + CUDA_POOL2D_BLOCK_SIZE - 1) / CUDA_POOL2D_BLOCK_SIZE;
dim3 block_nums(num_blocks);
pool2d_nchw_kernel<<<block_nums, CUDA_IM2COL_BLOCK_SIZE, 0, main_stream>>>(IH, IW, OH, OW, k1, k0, s1, s0, p1, p0, src0_dd, dst_dd, op);
(void) src0;
(void) src0_dd;
}
static void ggml_cuda_op_im2col(
const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst,
const float * src0_dd, const float * src1_dd, float * dst_dd, cudaStream_t main_stream) {
@ -10084,6 +10159,10 @@ static void ggml_cuda_alibi(const ggml_tensor * src0, const ggml_tensor * src1,
ggml_cuda_op_flatten(src0, src1, dst, ggml_cuda_op_alibi);
}
static void ggml_cuda_pool2d(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
ggml_cuda_op_flatten(src0, src1, dst, ggml_cuda_op_pool2d);
}
static void ggml_cuda_im2col(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
ggml_cuda_op_flatten(src0, src1, dst, ggml_cuda_op_im2col);
}
@ -10265,6 +10344,9 @@ GGML_CALL bool ggml_cuda_compute_forward(struct ggml_compute_params * params, st
case GGML_OP_IM2COL:
func = ggml_cuda_im2col;
break;
case GGML_OP_POOL_2D:
func = ggml_cuda_pool2d;
break;
case GGML_OP_SUM_ROWS:
func = ggml_cuda_sum_rows;
break;

16
ggml.c
View file

@ -5580,21 +5580,6 @@ struct ggml_tensor * ggml_pool_2d(
}
struct ggml_tensor * result;
#if defined(GGML_USE_CUBLAS)
if(!(op == GGML_OP_POOL_AVG)) {
GGML_ASSERT(false);
}
const int64_t ne[4] = {k0, k1, 1, a->ne[2]};
struct ggml_tensor * b = ggml_new_tensor(ctx, GGML_TYPE_F16, 4, ne);
struct ggml_tensor * new_a = ggml_reshape_4d(ctx, a, a->ne[0], a->ne[1], 1, a->ne[2] * a->ne[3]);
struct ggml_tensor * im2col = ggml_im2col(ctx, b, new_a,
s0, s1, p0, p1, 1, 1, true, GGML_TYPE_F32); // [N * IC, OH, OW, KH * KW]
result = ggml_sum_rows(ctx, im2col);
result = ggml_scale(ctx, result, 1. / (k0 * k1));
result = ggml_reshape_4d(ctx, result, im2col->ne[1], im2col->ne[2], a->ne[2], a->ne[3]);
#else
const int64_t ne[3] = {
ggml_calc_pool_output_size(a->ne[0], k0, s0, p0),
ggml_calc_pool_output_size(a->ne[1], k1, s1, p1),
@ -5608,7 +5593,6 @@ struct ggml_tensor * ggml_pool_2d(
result->op = GGML_OP_POOL_2D;
result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
result->src[0] = a;
#endif
return result;
}