T * tile_xy = (T *) compute_base + threadIdx.y*(tile_A::I * tile_k_padded);
if constexpr (has_ids) {
- __shared__ int has_any;
- if (threadIdx.y == 0) {
- int local_has_any = 0;
- for (int j = threadIdx.x; j < cols_per_block; j += warp_size) {
- int slot = -1;
- for (int k = 0; k < nchannels_dst; ++k) {
- const int idv = ids[j*stride_row_id + k*stride_col_id];
- if (idv == expert_idx) {
- slot = k;
- break;
- }
- }
- if (j < cols_per_block) {
- local_has_any |= (slot >= 0);
- slot_map[j] = slot;
+ int found = 0;
+
+ for (int j0 = 0; j0 < cols_per_block; j0 += nwarps) {
+ const int j = j0 + threadIdx.y;
+ const int32_t * __restrict__ id_row = ids + j*stride_row_id;
+
+ if (threadIdx.x == 0) {
+ slot_map[j] = -1;
+ }
+
+ for (int k = threadIdx.x; k < nchannels_dst; k += warp_size) {
+ int match = id_row[k*stride_col_id] == expert_idx;
+
+ if (match) {
+ slot_map[j] = k;
+ found = 1;
+ break;
}
}
- has_any = warp_reduce_any(local_has_any);
}
- __syncthreads();
- if (has_any == 0) {
+
+ if (!__syncthreads_or(found)) {
return;
}
}
+
for (int col = threadIdx.y*warp_size + threadIdx.x; col < ncols; col += nwarps*warp_size) {
tile_A A[ntA][warp_size / tile_A::J];
#pragma unroll
if constexpr (!has_ids) {
tile_xy[j0*tile_k_padded + threadIdx.x] = j < cols_per_block ? y[j*stride_col_y + col] : 0.0f;
} else {
- float val = 0.0f;
- if (j < cols_per_block) {
- const int slot = slot_map[j];
- if (slot >= 0) {
- val = y[slot*stride_channel_y + j*stride_col_y + col];
- }
- }
- tile_xy[j0*tile_k_padded + threadIdx.x] = val;
+ tile_xy[j0*tile_k_padded + threadIdx.x] = j < cols_per_block ? y[slot_map[j]*stride_channel_y + j*stride_col_y + col] : 0.0f;
}
}
} else if constexpr (std::is_same_v<T, half2> || std::is_same_v<T, nv_bfloat162>) {
const float2 tmp = j < cols_per_block ? y2[j*stride_col_y + col] : make_float2(0.0f, 0.0f);
tile_xy[j0*tile_k_padded + threadIdx.x] = {tmp.x, tmp.y};
} else {
- float2 tmp = make_float2(0.0f, 0.0f);
- if (j < cols_per_block) {
- const int slot = slot_map[j];
- if (slot >= 0) {
- const float2 * y2_slot = (const float2 *)(y + slot*stride_channel_y);
- tmp = y2_slot[j*stride_col_y + col];
- }
- }
+ float2 tmp = j < cols_per_block && slot_map[j] >= 0 ? *(const float2*) &y[slot_map[j]*stride_channel_y + 2*(j*stride_col_y + col)] : make_float2(0.0f, 0.0f);
tile_xy[j0*tile_k_padded + threadIdx.x] = {tmp.x, tmp.y};
}
}
const dim3 & block_nums, const dim3 & block_dims, const int nbytes_shared_total, cudaStream_t stream) {
if (ids) {
mul_mat_f<T, MMF_ROWS_PER_BLOCK, cols_per_block, nwarps, true><<<block_nums, block_dims, nbytes_shared_total, stream>>>
- (x, y, ids, dst, ncols_x, nchannels_dst, stride_row, stride_col_y, stride_col_dst,
+ (x, y, ids, dst, ncols_x, nchannels_dst, stride_row, stride_col_y, stride_col_dst,
stride_col_id, stride_row_id, channel_ratio, stride_channel_x, stride_channel_y, stride_channel_dst,
sample_ratio, stride_sample_x, stride_sample_y, stride_sample_dst);
} else {