ikawrakow/ik_llama.cpp
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Iwan Kawrakow
2025-03-24 15:22:16 +02:00
parent fb8db62e5a
commit f1bef9046e
1 changed files with 48 additions and 17 deletions
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65
ggml/src/ggml-cuda.cu
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@@ -2659,37 +2659,68 @@ static bool ggml_cuda_up_gate_unary(ggml_backend_cuda_context & ctx, ggml_tensor
bool first = false; //true;
std::vector<mmid_row_mapping> rmapping(ids->ne[1]*n_ids);
std::vector<int> moe_counts(n_as, 0), cum_moe_counts(n_as+1);
for (int64_t i02 = 0; i02 < n_as; i02++) {
int64_t num_src1_rows = 0;
for (int64_t iid1 = 0; iid1 < ids->ne[1]; iid1++) {
for (int64_t id = 0; id < n_ids; id++) {
const int32_t row_id_i = *(const int32_t *) (ids_host.data() + iid1*ids->nb[1] + id*ids->nb[0]);
if (row_id_i >= 0 && row_id_i < n_as) ++moe_counts[row_id_i];
}
}
cum_moe_counts[0] = 0;
for (int i = 0; i < (int)n_as; ++i) {
cum_moe_counts[i+1] = cum_moe_counts[i] + moe_counts[i];
//printf("moe_counts[%2d] = %d, cum = %d\n", i, moe_counts[i], cum_moe_counts[i+1]);
}
for (int64_t iid1 = 0; iid1 < ids->ne[1]; iid1++) {
for (int64_t id = 0; id < n_ids; id++) {
const int32_t row_id_i = *(const int32_t *) (ids_host.data() + iid1*ids->nb[1] + id*ids->nb[0]);
if (row_id_i == i02) {
//if (id >= ne11) printf("Oops: id = %ld, ne11 = %ld\n", id, ne11);
//rmapping[num_src1_rows++] = {(int)(id%ne11), (int)iid1};
rmapping[num_src1_rows++] = {(int)id, (int)iid1};
}
ggml_cuda_pool_alloc<mmid_row_mapping> dev_row_mapping(ctx.pool(), cum_moe_counts[n_as]);
for (int64_t iid1 = 0; iid1 < ids->ne[1]; iid1++) {
for (int64_t id = 0; id < n_ids; id++) {
const int32_t row_id_i = *(const int32_t *) (ids_host.data() + iid1*ids->nb[1] + id*ids->nb[0]);
if (row_id_i >= 0 && row_id_i < n_as) {
rmapping[cum_moe_counts[row_id_i]++] = {(int)id, (int)iid1};
}
}
//printf("i02 = %ld, num_src1_rows = %ld, rmapping.size() = %zu\n", i02, num_src1_rows, rmapping.size());
}
for (int i = 0; i < (int)n_as; ++i) cum_moe_counts[i] -= moe_counts[i];
CUDA_CHECK(cudaMemcpyAsync(dev_row_mapping.get(), rmapping.data(), cum_moe_counts[n_as]*sizeof(mmid_row_mapping), cudaMemcpyHostToDevice, stream));
for (int64_t i02 = 0; i02 < n_as; i02++) {
int64_t num_src1_rows = moe_counts[i02];
//printf("Processing i02 = %d with %d counts\n", (int)i02, (int)num_src1_rows);
//int64_t num_src1_rows = 0;
//for (int64_t iid1 = 0; iid1 < ids->ne[1]; iid1++) {
// for (int64_t id = 0; id < n_ids; id++) {
// const int32_t row_id_i = *(const int32_t *) (ids_host.data() + iid1*ids->nb[1] + id*ids->nb[0]);
// if (row_id_i == i02) {
// //if (id >= ne11) printf("Oops: id = %ld, ne11 = %ld\n", id, ne11);
// //rmapping[num_src1_rows++] = {(int)(id%ne11), (int)iid1};
// rmapping[num_src1_rows++] = {(int)id, (int)iid1};
// }
// }
//}
if (num_src1_rows == 0) continue;
size_t mapping_offset = cum_moe_counts[i02];
ggml_cuda_pool_alloc<mmid_row_mapping> dev_row_mapping(ctx.pool(), num_src1_rows);
CUDA_CHECK(cudaMemcpyAsync(dev_row_mapping.get(), rmapping.data(), num_src1_rows*sizeof(mmid_row_mapping), cudaMemcpyHostToDevice, stream));
CUDA_CHECK(cudaStreamSynchronize(stream));
//ggml_cuda_pool_alloc<mmid_row_mapping> dev_row_mapping(ctx.pool(), num_src1_rows);
//CUDA_CHECK(cudaMemcpyAsync(dev_row_mapping.get(), rmapping.data(), num_src1_rows*sizeof(mmid_row_mapping), cudaMemcpyHostToDevice, stream));
//CUDA_CHECK(cudaStreamSynchronize(stream));
//ggml_cuda_pool_alloc<int> dev_cur_src1_row(ctx.pool(), 1);
//ggml_cuda_pool_alloc<mmid_row_mapping> dev_row_mapping(ctx.pool(), num_src1_rows);
//CUDA_CHECK(cudaMemsetAsync(dev_cur_src1_row.get(), 0, sizeof(int), stream));
{
//printf("Invoking k_copy_src_to_contiguous kernel using offset %zu\n", offset);
dim3 block_dims(std::min((unsigned int)ne10, 768u));
dim3 grid_dims(num_src1_rows);
k_copy_src_to_contiguous<<<grid_dims, block_dims, 0, stream>>>(
src1_original, src1_contiguous.get(), dev_row_mapping.get(), ne10, ne11, nb11, nb12);
src1_original, src1_contiguous.get(), dev_row_mapping.get() + mapping_offset, ne10, ne11, nb11, nb12);
//dim3 block_dims(std::min((unsigned int)ne10, 768u));
//dim3 grid_dims(ids->ne[1], n_ids);
//k_copy_src1_to_contiguous<<<grid_dims, block_dims, 0, stream>>>(
@@ -2754,7 +2785,7 @@ static bool ggml_cuda_up_gate_unary(ggml_backend_cuda_context & ctx, ggml_tensor
dim3 grid_dims(num_src1_rows);
k_copy_dst_from_contiguous<<<grid_dims, block_dims, 0, stream>>>(
(char *)next->data, final_dst_contiguous.get(),
dev_row_mapping.get(),
dev_row_mapping.get() + mapping_offset,
next->ne[0],
next->nb[1], next->nb[2]);
CUDA_CHECK(cudaGetLastError());
@@ -2766,7 +2797,7 @@ static bool ggml_cuda_up_gate_unary(ggml_backend_cuda_context & ctx, ggml_tensor
dim3 grid_dims(num_src1_rows);
k_copy_dst_from_contiguous<<<grid_dims, block_dims, 0, stream>>>(
dst_original, dst_gate_contiguous.get(),
dev_row_mapping.get(),
dev_row_mapping.get() + mapping_offset,
ne0,
nb1, nb2);
CUDA_CHECK(cudaGetLastError());