Cache for cublaslt descriptor (#50931)

* first commit

* finish base work

* modification for good

* fix for cache setting and gather the algo and desc as one data for cache storage

* fix for cache setting and gather the algo and desc as one data for cache storage

* install pre-commit check

paddle/phi/kernels/autotune/cache_base.h

@@ -60,10 +60,6 @@ size_t GenKey(Args&&... args) {
   return seed;
 }
 
-struct MatmulHashValueType {
-  uint64_t data[8];
-};
-
 struct MatmulCacheKey {
  public:
   MatmulCacheKey() {}
@@ -79,7 +75,7 @@ struct MatmulCacheKey {
                  static_cast<int64_t>(dtype));
   }
   size_t GetKey() const { return key; }
-  size_t GetSubKey(int64_t idx) const { return GenKey(key, idx); }
+  size_t GenSubKey(int64_t idx) const { return GenKey(key, idx); }
 
  private:
   size_t key;
@@ -249,22 +245,22 @@ class MatmulAlgorithmsCache : public AlgorithmsCache<KeyT, AlgorithmT> {
     return ret;
   }
 
-  void SetSubKey(const KeyT& sub_key, const MatmulHashValueType* algo) {
+  void SetSubKey(const KeyT& sub_key, void* algo) {
     std::lock_guard<std::mutex> lock(*(this->cache_mutex_));
-    sub_hash_[sub_key] = *algo;
+    sub_hash_[sub_key] = algo;
   }
 
-  MatmulHashValueType* GetSubKey(const KeyT& sub_key) {
+  void* GetSubKey(const KeyT& sub_key) {
     std::lock_guard<std::mutex> lock(*(this->cache_mutex_));
     PADDLE_ENFORCE_NE(
         sub_hash_.find(sub_key),
         sub_hash_.end(),
         phi::errors::PreconditionNotMet("The key does not exist."));
-    return &(sub_hash_[sub_key]);
+    return sub_hash_[sub_key];
   }
 
  private:
-  std::unordered_map<KeyT, MatmulHashValueType> sub_hash_;
+  std::unordered_map<KeyT, void*> sub_hash_;
 };
 
 }  // namespace autotune

paddle/phi/kernels/funcs/blas/blaslt_impl.cu.h

@@ -26,7 +26,7 @@ limitations under the License. */
 namespace phi {
 namespace funcs {
 
-enum MatmulImplType { kImplWithCublas = 1, kImplWithCublasLt = 2 };
+enum MatmulImplType { kCublas = 1, kCublasLt = 2 };
 
 template <typename T>
 cublasComputeType_t GetCudaComputeType() {
@@ -43,7 +43,35 @@ struct MatmulDescriptor {
   cublasLtMatrixLayout_t x_desc{nullptr};
   cublasLtMatrixLayout_t y_desc{nullptr};
   cublasLtMatrixLayout_t out_desc{nullptr};
+  cublasLtMatmulAlgo_t* algo{nullptr};
+
+  MatmulDescriptor() {}
+  MatmulDescriptor(const MatmulDescriptor& obj) {
+    algo = obj.algo;
+    x_desc = obj.x_desc;
+    y_desc = obj.y_desc;
+    op_desc = obj.op_desc;
+    out_desc = obj.out_desc;
+  }
+
+  ~MatmulDescriptor() {
+    if (!is_cached) {
+      PADDLE_ENFORCE_GPU_SUCCESS(dynload::cublasLtMatmulDescDestroy(op_desc));
+      PADDLE_ENFORCE_GPU_SUCCESS(dynload::cublasLtMatrixLayoutDestroy(y_desc));
+      PADDLE_ENFORCE_GPU_SUCCESS(dynload::cublasLtMatrixLayoutDestroy(x_desc));
+      PADDLE_ENFORCE_GPU_SUCCESS(
+          dynload::cublasLtMatrixLayoutDestroy(out_desc));
+      delete algo;
+
+      op_desc = nullptr;
+      x_desc = nullptr;
+      y_desc = nullptr;
+      out_desc = nullptr;
+      algo = nullptr;
+    }
+  }
 
+  // x_desc, y_desc, op_desc are allocated in heap memory.
   template <typename T>
   void Create(const int M,
               const int N,
@@ -90,6 +118,15 @@ struct MatmulDescriptor {
     }
   }
 
+  cublasLtMatmulAlgo_t* SetAlgo() {
+    algo = new cublasLtMatmulAlgo_t;
+    return algo;
+  }
+
+  void ValidateCache() { is_cached = true; }
+
+ private:
+  bool is_cached{false};
   void CreateMatrixLayout(cublasLtMatrixLayout_t* desc,
                           cudaDataType type,
                           uint64_t rows,
@@ -118,17 +155,73 @@ struct MatmulDescriptor {
         &stride,
         sizeof(stride)));
   }
+};
 
-  void Release() {
-    PADDLE_ENFORCE_GPU_SUCCESS(dynload::cublasLtMatrixLayoutDestroy(y_desc));
-    PADDLE_ENFORCE_GPU_SUCCESS(dynload::cublasLtMatrixLayoutDestroy(x_desc));
-    PADDLE_ENFORCE_GPU_SUCCESS(dynload::cublasLtMatrixLayoutDestroy(out_desc));
-    PADDLE_ENFORCE_GPU_SUCCESS(dynload::cublasLtMatmulDescDestroy(op_desc));
+inline std::string GetDescResultString(std::string prefix,
+                                       const MatmulDescriptor* desc,
+                                       bool has_algo = true) {
+  std::ostringstream out;
+  out << prefix << " \n";
+
+#define GET_DESC_DATA_INFO(src)                      \
+  do {                                               \
+    out << "#data "                                  \
+        << "= [";                                    \
+    int num = sizeof((*src)) / sizeof(src->data[0]); \
+    for (int i = 0; i < num; ++i) {                  \
+      out << src->data[i] << ", ";                   \
+    }                                                \
+    out << "]\n";                                    \
+  } while (0);
+
+  if (has_algo) {
+    GET_DESC_DATA_INFO(desc->algo);
+  }
+  GET_DESC_DATA_INFO(desc->x_desc);
+  GET_DESC_DATA_INFO(desc->y_desc);
+  GET_DESC_DATA_INFO(desc->out_desc);
+  GET_DESC_DATA_INFO(desc->op_desc);
+  return out.str();
+}
 
-    op_desc = nullptr;
-    x_desc = nullptr;
-    y_desc = nullptr;
-    out_desc = nullptr;
+template <typename T>
+struct DescriptorSetter {
+  MatmulDescriptor* desc{nullptr};
+  size_t sub_key{std::numeric_limits<size_t>::min()};
+
+  DescriptorSetter(phi::autotune::MatmulCacheKey* matmul_key,
+                   MatmulDescriptor* desc_ptr,
+                   const int M,
+                   const int N,
+                   const int K,
+                   const bool trans_x,
+                   const bool trans_y,
+                   const int batch_size = 1,
+                   int64_t stride_x = 0,
+                   int64_t stride_y = 0,
+                   int64_t stride_out = 0) {
+    if (matmul_key != nullptr) {
+      sub_key =
+          matmul_key->GenSubKey(static_cast<size_t>(MatmulImplType::kCublasLt));
+    }
+    auto& mamtul_cache = phi::autotune::AutoTuneCache::Instance().GetMatmul();
+    if (mamtul_cache.FindSubKey(sub_key)) {
+      desc =
+          reinterpret_cast<MatmulDescriptor*>(mamtul_cache.GetSubKey(sub_key));
+      VLOG(4) << GetDescResultString("[Heap MatmulDescriptor] ", desc);
+    } else {
+      desc_ptr->Create<T>(M,
+                          N,
+                          K,
+                          trans_x,
+                          trans_y,
+                          batch_size,
+                          stride_x,
+                          stride_y,
+                          stride_out);
+      desc = desc_ptr;
+      VLOG(4) << GetDescResultString("[Stack MatmulDescriptor] ", desc, false);
+    }
   }
 };
 
@@ -148,9 +241,10 @@ struct MatmulWithCublasLt {
                   const bool trans_y,
                   phi::autotune::MatmulCacheKey* matmul_key = nullptr) {
     MatmulDescriptor desc;
-    desc.Create<T>(M, N, K, trans_x, trans_y);
-    RunImpl(ctx, desc, x_data, y_data, out_data, matmul_key);
-    desc.Release();
+    auto setter =
+        DescriptorSetter<T>(matmul_key, &desc, M, N, K, trans_x, trans_y);
+    RunImpl(
+        ctx, setter.desc, x_data, y_data, out_data, setter.sub_key, matmul_key);
   }
 
   static void RunWithBatch(
@@ -169,10 +263,19 @@ struct MatmulWithCublasLt {
       int64_t stride_out,
       phi::autotune::MatmulCacheKey* matmul_key = nullptr) {
     MatmulDescriptor desc;
-    desc.Create<T>(
-        M, N, K, trans_x, trans_y, batch_size, stride_x, stride_y, stride_out);
-    RunImpl(ctx, desc, x_data, y_data, out_data, matmul_key);
-    desc.Release();
+    auto setter = DescriptorSetter<T>(matmul_key,
+                                      &desc,
+                                      M,
+                                      N,
+                                      K,
+                                      trans_x,
+                                      trans_y,
+                                      batch_size,
+                                      stride_x,
+                                      stride_y,
+                                      stride_out);
+    RunImpl(
+        ctx, setter.desc, x_data, y_data, out_data, setter.sub_key, matmul_key);
   }
 
   static void RunWithBatch(
@@ -211,64 +314,56 @@ struct MatmulWithCublasLt {
   }
 
   static void RunImpl(const phi::GPUContext& ctx,
-                      const MatmulDescriptor& desc,
+                      MatmulDescriptor* desc,
                       const T* x_ptr,
                       const T* y_ptr,
                       T* out_ptr,
+                      const size_t sub_key,
                       phi::autotune::MatmulCacheKey* matmul_key = nullptr) {
     MT alpha = static_cast<MT>(1);
     MT beta = static_cast<MT>(0);
 
     cublasLtHandle_t cublaslt_handle = ctx.cublaslt_handle();
-    cublasLtMatmulAlgo_t* best_algo = nullptr;
-
     size_t workspace_size = static_cast<size_t>(4) * 1024 * 1024;
     phi::Allocator::AllocationPtr workspace = GetWorkspace(ctx, workspace_size);
 
     if (matmul_key != nullptr) {
       auto& cache = phi::autotune::AutoTuneCache::Instance().GetMatmul();
-      size_t sub_key = matmul_key->GetSubKey(
-          static_cast<int64_t>(MatmulImplType::kImplWithCublasLt));
-      if (cache.FindSubKey(sub_key)) {
-        best_algo =
-            reinterpret_cast<cublasLtMatmulAlgo_t*>(cache.GetSubKey(sub_key));
-      } else if (phi::autotune::AutoTuneStatus::Instance().UseAutoTune()) {
-        cublasLtMatmulAlgo_t test_algo;
+      if (phi::autotune::AutoTuneStatus::Instance().UseAutoTune() &&
+          (!cache.FindSubKey(sub_key))) {
+        desc->ValidateCache();
         SearchBestAlgo(ctx,
                        cublaslt_handle,
-                       desc.op_desc,
-                       desc.y_desc,
-                       desc.x_desc,
-                       desc.out_desc,
+                       desc,
                        static_cast<void*>(&alpha),
                        static_cast<void*>(&beta),
                        y_ptr,
                        x_ptr,
                        out_ptr,
                        workspace->ptr(),
-                       workspace_size,
-                       &(test_algo));
-        cache.SetSubKey(
-            sub_key,
-            reinterpret_cast<phi::autotune::MatmulHashValueType*>(&test_algo));
-        best_algo = &test_algo;
+                       workspace_size);
+        MatmulDescriptor* best_desc = new MatmulDescriptor(*desc);
+        VLOG(4) << GetDescResultString("[Searched MatmulDescriptor] ",
+                                       best_desc);
+        cache.SetSubKey(sub_key, reinterpret_cast<void*>(best_desc));
       }
     }
 
-    PADDLE_ENFORCE_GPU_SUCCESS(dynload::cublasLtMatmul(
-        cublaslt_handle,
-        desc.op_desc,
+    VLOG(4) << GetDescResultString("[Impl MatmulDescriptor] ", desc);
+    PADDLE_ENFORCE_GPU_SUCCESS(
+        dynload::cublasLtMatmul(cublaslt_handle,
+                                desc->op_desc,
                                 static_cast<void*>(&alpha),
                                 y_ptr,
-        desc.y_desc,
+                                desc->y_desc,
                                 x_ptr,
-        desc.x_desc,
+                                desc->x_desc,
                                 static_cast<void*>(&beta),
                                 out_ptr,
-        desc.out_desc,
+                                desc->out_desc,
                                 out_ptr,
-        desc.out_desc,
-        reinterpret_cast<cublasLtMatmulAlgo_t*>(best_algo),
+                                desc->out_desc,
+                                desc->algo,
                                 workspace->ptr(),
                                 workspace_size,
                                 ctx.stream()));
@@ -276,23 +371,19 @@ struct MatmulWithCublasLt {
 
   static void SearchBestAlgo(const phi::GPUContext& ctx,
                              const cublasLtHandle_t& lt_handle,
-                             const cublasLtMatmulDesc_t& op_desc,
-                             const cublasLtMatrixLayout_t& y_desc,
-                             const cublasLtMatrixLayout_t& x_desc,
-                             const cublasLtMatrixLayout_t& out_desc,
+                             MatmulDescriptor* desc,
                              const void* alpha,
                              const void* beta,
                              const void* y_data,
                              const void* x_data,
                              void* out_data,
                              void* workspace_ptr,
-                             size_t workspace_size,
-                             cublasLtMatmulAlgo_t* best_algo) {
+                             size_t workspace_size) {
+    cublasLtMatmulAlgo_t* best_algo = desc->SetAlgo();
     const auto& stream = ctx.stream();
     int returned_results = 0;
     constexpr int requested_algo_count = 10;
     cublasLtMatmulPreference_t preference;
-
     PADDLE_ENFORCE_GPU_SUCCESS(
         dynload::cublasLtMatmulPreferenceCreate(&preference));
     PADDLE_ENFORCE_GPU_SUCCESS(dynload::cublasLtMatmulPreferenceSetAttribute(
@@ -300,16 +391,15 @@ struct MatmulWithCublasLt {
         CUBLASLT_MATMUL_PREF_MAX_WORKSPACE_BYTES,
         &workspace_size,
         sizeof(workspace_size)));
-
     std::vector<cublasLtMatmulHeuristicResult_t> heuristic_results(
         requested_algo_count);
     PADDLE_ENFORCE_GPU_SUCCESS(
         dynload::cublasLtMatmulAlgoGetHeuristic(lt_handle,
-                                                op_desc,
-                                                y_desc,
-                                                x_desc,
-                                                out_desc,
-                                                out_desc,
+                                                desc->op_desc,
+                                                desc->y_desc,
+                                                desc->x_desc,
+                                                desc->out_desc,
+                                                desc->out_desc,
                                                 preference,
                                                 requested_algo_count,
                                                 heuristic_results.data(),
@@ -317,7 +407,6 @@ struct MatmulWithCublasLt {
     PADDLE_ENFORCE_GT(returned_results,
                       0,
                       phi::errors::Unavailable("No GEMM algorithm avaliable."));
-
     phi::GpuTimer timer;
     int best_algo_idx = -1;
     constexpr int repeats = 6;
@@ -329,17 +418,17 @@ struct MatmulWithCublasLt {
         timer.Start(stream);
         PADDLE_ENFORCE_GPU_SUCCESS(
             dynload::cublasLtMatmul(lt_handle,
-                                    op_desc,
+                                    desc->op_desc,
                                     alpha,
                                     y_data,
-                                    y_desc,
+                                    desc->y_desc,
                                     x_data,
-                                    x_desc,
+                                    desc->x_desc,
                                     beta,
                                     out_data,
-                                    out_desc,
+                                    desc->out_desc,
                                     out_data,
-                                    out_desc,
+                                    desc->out_desc,
                                     &(heuristic_results[algo_idx].algo),
                                     workspace_ptr,
                                     workspace_size,
@@ -360,7 +449,6 @@ struct MatmulWithCublasLt {
       }
     }
     VLOG(4) << "Best_algo_idx in MatmulWithCublaslt is : " << best_algo_idx;
-
     *best_algo = heuristic_results[best_algo_idx].algo;
     PADDLE_ENFORCE_GPU_SUCCESS(
         dynload::cublasLtMatmulPreferenceDestroy(preference));