optimize w4a8 decoding (PaddlePaddle#3050)

Author: rsmallblue

custom_ops/gpu_ops/cutlass_kernels/w4a8_moe/w4a8_gemm_grouped.h

@@ -223,22 +223,18 @@ class W4A8MoeGemmUniversalBase {
   static Status can_implement(Arguments const &args)
   {
     CUTLASS_TRACE_HOST("W4A8MoeGemmUniversalBase::can_implement()");
-    // printf("--1\n");
     // Initialize static kernel and device properties, if necessary.
     Status result = init_device_props();
-    // printf("--1-2\n");
     if (result != Status::kSuccess) {
       return result;
     }
-    // printf("--2\n");
     dim3 grid = get_grid_shape(args);
     // printf("--grid:%d, %d, %d\n", grid.x, grid.y, grid.z);
     if (!(grid.y <= std::numeric_limits<uint16_t>::max() &&
           grid.z <= std::numeric_limits<uint16_t>::max()))
     {
       return Status::kErrorInvalidProblem;
     }
-    // printf("--3\n");
     return GemmKernel::can_implement(args);
   }
 
@@ -285,18 +281,50 @@ class W4A8MoeGemmUniversalBase {
   }
 
 
+
   /// Returns the maximum number of active thread blocks per multiprocessor
-  static int maximum_active_blocks()
+  static int maximum_active_blocks(int smem_capacity = -1)
   {
     CUTLASS_TRACE_HOST("W4A8MoeGemmUniversalBase::maximum_active_blocks()");
 
-    // Initialize static device properties, if necessary
-    if (init_device_props() != Status::kSuccess) {
+    int smem_size = int(sizeof(typename GemmKernel_::SharedStorage));
+
+    CUTLASS_TRACE_HOST("  smem_size: " << smem_size << " bytes");
+
+    cudaError_t result;
+    if (smem_size > (48 << 10)) {
+      result = cudaFuncSetAttribute(Kernel2<GemmKernel_>,
+                                    cudaFuncAttributeMaxDynamicSharedMemorySize,
+                                    smem_size);
+
+      if (result != cudaSuccess) {
+        // Call cudaGetLastError() to clear the error bit
+        result = cudaGetLastError();
+        CUTLASS_TRACE_HOST(
+          "  cudaFuncSetAttribute() returned error "
+          << cudaGetErrorString(result));
+        return -1;
+      }
+    }
+
+    int max_active_blocks = -1;
+    result = cudaOccupancyMaxActiveBlocksPerMultiprocessor(
+        &max_active_blocks,
+        Kernel2<GemmKernel_>,
+        GemmKernel_::kThreadCount,
+        smem_size);
+
+    if (result != cudaSuccess) {
+      // Call cudaGetLastError() to clear the error bit
+      result = cudaGetLastError();
+      CUTLASS_TRACE_HOST(
+        "  cudaOccupancyMaxActiveBlocksPerMultiprocessor() returned error "
+        << cudaGetErrorString(result));
       return -1;
     }
 
-    CUTLASS_TRACE_HOST("  max_active_blocks: " << sm_occupancy_);
-    return sm_occupancy_;
+    CUTLASS_TRACE_HOST("  max_active_blocks: " << max_active_blocks);
+    return max_active_blocks;
   }
 
 
@@ -341,8 +369,7 @@ class W4A8MoeGemmUniversalBase {
 
     // Configure grid and block dimensions
     dim3 block(GemmKernel::kThreadCount, 1, 1);
-    // dim3 grid = params_.get_grid_dims();
-        dim3 grid(216, 1, 1);
+    dim3 grid(params_.threadblock_count, 1, 1);
 
     // Launch kernel
     CUTLASS_TRACE_HOST("  "

custom_ops/gpu_ops/cutlass_kernels/w4a8_moe/w4a8_moe_gemm_config_search.sh

@@ -21,12 +21,12 @@ rm -rf up_gate_proj_7168_8192.log
 rm -rf down_proj_8192_3584.log
 num_experts=8
 
-for tokens_per_expert in 12
+for tokens_per_expert in 1 2 4 8 16 20 24 28 32 36 48 64 96 128 160 192 224 256 384 512 768 1024 2048 3072 4096 8192
 
 do
 wait
-CUDA_VISIBLE_DEVICES=2 ./w4a8_moe_gemm_test ${num_experts} ${up_gate_proj_n} ${up_gate_proj_k} ${tokens_per_expert} 1 0 >> up_gate_proj_${up_gate_proj_n}_${up_gate_proj_k}.log 2>&1 &
-# CUDA_VISIBLE_DEVICES=3 ./w4a8_moe_gemm_test ${num_experts} ${down_proj_n} ${down_proj_k} ${tokens_per_expert} 1 0 >> down_proj_${down_proj_n}_${down_proj_k}.log 2>&1 &
+CUDA_VISIBLE_DEVICES=2 ./w4a8_moe_gemm_test ${num_experts} ${ffn1_n} ${ffn1_k} ${tokens_per_expert} 0 1 >> ffn1_${ffn1_n}_${ffn1_k}.log 2>&1 &
+CUDA_VISIBLE_DEVICES=3 ./w4a8_moe_gemm_test ${num_experts} ${ffn2_n} ${ffn2_k} ${tokens_per_expert} 0 1 >> ffn2_${ffn2_n}_${ffn2_k}.log 2>&1 &
 done
 wait
 echo "#### finish ####"

custom_ops/gpu_ops/cutlass_kernels/w4a8_moe/w4a8_moe_gemm_test.cu

@@ -996,7 +996,6 @@ int main(int argc, char *argv[]) {
         CutlassTileConfig::CtaShape64x256x64_WarpShape64x64x64,
         CutlassTileConfig::CtaShape32x512x64_WarpShape32x128x64,
         CutlassTileConfig::CtaShape128x128x64_WarpShape128x32x64,
-        CutlassTileConfig::CtaShape32x512x64_WarpShape32x128x64,
     };
     std::vector<SplitKStyle> all_split_k_style{SplitKStyle::NO_SPLIT_K};