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Commit 321c57d0 authored by Tri Dao's avatar Tri Dao
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Set block size of SM75 fwd to 256 if there's no dropout 

This speeds up the fwd by 1.5x.
parent f2d8d410
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Showing with 15 additions and 5 deletions
csrc/flash_attn/fmha_api.cpp
View file @ 321c57d0
...@@ -144,7 +144,7 @@ mha_fwd(const at::Tensor &qkv, // total x num_heads x 3 x head_size, tot ...@@ -144,7 +144,7 @@ mha_fwd(const at::Tensor &qkv, // total x num_heads x 3 x head_size, tot
TORCH_CHECK(head_size == 16 || head_size == 32 || head_size == 64 || head_size == 128); TORCH_CHECK(head_size == 16 || head_size == 32 || head_size == 64 || head_size == 128);
// int base_N = head_size == 16 ? 512 : (head_size == 128 ? 128 : 256); // int base_N = head_size == 16 ? 512 : (head_size == 128 ? 128 : 256);
int base_N = (head_size == 128 || (is_sm75 && head_size == 64)) ? 128 : 256; int base_N = (head_size == 128 || (is_sm75 && head_size == 64 && is_dropout)) ? 128 : 256;
// int base_N = 256; // int base_N = 256;
int seq_len = 512; int seq_len = 512;
if( max_seq_len <= 128 ) { if( max_seq_len <= 128 ) {
......
csrc/flash_attn/src/fmha_fprop_fp16_kernel.sm80.cu
View file @ 321c57d0
...@@ -111,8 +111,13 @@ void run_fmha_fp16_sm80(Launch_params<Fused_multihead_attention_fprop_params> &l ...@@ -111,8 +111,13 @@ void run_fmha_fp16_sm80(Launch_params<Fused_multihead_attention_fprop_params> &l
using Kernel_traits = FMHA_kernel_traits<256, 64, 16, 1, 4, 0x08u>; using Kernel_traits = FMHA_kernel_traits<256, 64, 16, 1, 4, 0x08u>;
run_fmha_fp16_sm80_loop_<Kernel_traits>(launch_params, configure); run_fmha_fp16_sm80_loop_<Kernel_traits>(launch_params, configure);
} else if (dprops->major == 7 && dprops->minor == 5) { } else if (dprops->major == 7 && dprops->minor == 5) {
using Kernel_traits = FMHA_kernel_traits<128, 64, 16, 1, 4, 0x08u>; if (launch_params.is_dropout) { // Need to use the same block size as backward
run_fmha_fp16_sm80_loop_<Kernel_traits>(launch_params, configure); using Kernel_traits = FMHA_kernel_traits<128, 64, 16, 1, 4, 0x08u>;
run_fmha_fp16_sm80_loop_<Kernel_traits>(launch_params, configure);
} else {
using Kernel_traits = FMHA_kernel_traits<256, 64, 16, 1, 4, 0x08u>;
run_fmha_fp16_sm80_loop_<Kernel_traits>(launch_params, configure);
}
} }
} }
} else if (launch_params.params.d == 128) { } else if (launch_params.params.d == 128) {
...@@ -136,8 +141,13 @@ void run_fmha_fp16_sm80(Launch_params<Fused_multihead_attention_fprop_params> &l ...@@ -136,8 +141,13 @@ void run_fmha_fp16_sm80(Launch_params<Fused_multihead_attention_fprop_params> &l
// using Kernel_traits = FMHA_kernel_traits<256, 64, 16, 1, 4, 0x08u>; // using Kernel_traits = FMHA_kernel_traits<256, 64, 16, 1, 4, 0x08u>;
// run_fmha_fp16_sm80_loop_<Kernel_traits>(launch_params, configure); // run_fmha_fp16_sm80_loop_<Kernel_traits>(launch_params, configure);
// } else if (dprops->major == 7 && dprops->minor == 5) { // } else if (dprops->major == 7 && dprops->minor == 5) {
// using Kernel_traits = FMHA_kernel_traits<128, 64, 16, 1, 4, 0x08u>; // if (launch_params.is_dropout) { // Need to use the same block size as backward
// run_fmha_fp16_sm80_loop_<Kernel_traits>(launch_params, configure); // using Kernel_traits = FMHA_kernel_traits<128, 64, 16, 1, 4, 0x08u>;
// run_fmha_fp16_sm80_loop_<Kernel_traits>(launch_params, configure);
// } else {
// using Kernel_traits = FMHA_kernel_traits<256, 64, 16, 1, 4, 0x08u>;
// run_fmha_fp16_sm80_loop_<Kernel_traits>(launch_params, configure);
// }
// } // }
// } // }
// } // }
......
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