[CUDA] Initial support for dynamic shared memory (apache#8466)

* send dyn shmem size to runtime

* add dyn shared storage scope

* associate buffer var and its storage scoe in split_host_device

* tried NVPTX but failed with INVALID_PTX error

* test stub

* dynamic shmem reduce working

* log2 issue fixed

* nvptx working

* refactor llvm shmem allocation

* make linkage argument

* support rocm too

* send dyn shmem param to hip runtime

* remove alloc map from split_host_device.cc

* remove attr::storage_scope from split_host_device

* lint fix

* formatting

* update calling convention doc

* minor update to test

* remove log

* remove kDynShared, dyn.shared -> shared.dyn

* support backward compat

* update json/binary reader/writer

* thread_axis_tags -> launch_param_tags

* ThreadAxisConfig -> LaunchParamConfig

* remove use_dynamic_shared_memory from FunctionInfo meta data

* revert change in test_tir_ir_builder.py

* make sure kUseDynamicSharedMemoryTag is the last tag

* remove continue

* update doc string following name change

* more comment update following name change

Co-authored-by: masa <masa@pop-os.localdomain>
Co-authored-by: Masahiro Masuda <masahi@129@gmail.com>

docs/dev/codebase_walkthrough.rst

@@ -183,7 +183,7 @@ The first time you invoke the compiled module with ``fadd(a, b, c)``, ``GetFunct
      auto it = fmap_.find(name);
      const FunctionInfo& info = it->second;
      CUDAWrappedFunc f;
-     f.Init(this, sptr_to_self, name, info.arg_types.size(), info.thread_axis_tags);
+     f.Init(this, sptr_to_self, name, info.arg_types.size(), info.launch_param_tags);
      return PackFuncVoidAddr(f, info.arg_types);
    }
 
@@ -204,7 +204,7 @@ The ``PackedFunc``'s overloaded ``operator()`` will be called, which in turn cal
          fcache_[device_id] = m_->GetFunc(device_id, func_name_);
        }
        CUstream strm = static_cast<CUstream>(CUDAThreadEntry::ThreadLocal()->stream);
-       ThreadWorkLoad wl = thread_axis_cfg_.Extract(args);
+       ThreadWorkLoad wl = launch_param_config_.Extract(args);
        CUresult result = cuLaunchKernel(
            fcache_[device_id],
            wl.grid_dim(0),

include/tvm/tir/function.h

@@ -240,17 +240,26 @@ namespace attr {
  *
  * Call(f,
  *      [arg1, arg2, ..., arg_n,
- *       work_size_1, work_size_2, ... work_size_m])
+ *       work_size_1, work_size_2, ... work_size_m, dyn_shmem_size])
  *
  * Here n = len(arg), m = len(work_size) = len(device_thread_axis).
  *
+ * When kDeviceUseDynSharedMemory is not set, dyn_shmem_size argument is omitted.
+ *
  * The list of device_thread_axis indicates how can be bind the
  * work_size arguments to the corresponding threads.
  *
  * \sa tvm::CallingConv::kDeviceKernelLaunch
  */
 constexpr const char* kDeviceThreadAxis = "tir.device_thread_axis";
 
+/*!
+ * \brief Whether or not use dynamic shared memory.
+ *
+ * Type: Integer
+ */
+constexpr const char* kDeviceUseDynSharedMemory = "tir.device_use_dyn_shared_memory";
+
 /*!
  * \brief Whether to set noalias rule on the function arguments.
  *

src/runtime/cuda/cuda_module.cc

@@ -153,12 +153,12 @@ class CUDAWrappedFunc {
  public:
   // initialize the CUDA function.
   void Init(CUDAModuleNode* m, ObjectPtr<Object> sptr, const std::string& func_name,
-            size_t num_void_args, const std::vector<std::string>& thread_axis_tags) {
+            size_t num_void_args, const std::vector<std::string>& launch_param_tags) {
     m_ = m;
     sptr_ = sptr;
     func_name_ = func_name;
     std::fill(fcache_.begin(), fcache_.end(), nullptr);
-    thread_axis_cfg_.Init(num_void_args, thread_axis_tags);
+    launch_param_config_.Init(num_void_args, launch_param_tags);
   }
   // invoke the function with void arguments
   void operator()(TVMArgs args, TVMRetValue* rv, void** void_args) const {
@@ -168,10 +168,10 @@ class CUDAWrappedFunc {
       fcache_[device_id] = m_->GetFunc(device_id, func_name_);
     }
     CUstream strm = static_cast<CUstream>(CUDAThreadEntry::ThreadLocal()->stream);
-    ThreadWorkLoad wl = thread_axis_cfg_.Extract(args);
+    ThreadWorkLoad wl = launch_param_config_.Extract(args);
     CUresult result = cuLaunchKernel(fcache_[device_id], wl.grid_dim(0), wl.grid_dim(1),
                                      wl.grid_dim(2), wl.block_dim(0), wl.block_dim(1),
-                                     wl.block_dim(2), 0, strm, void_args, nullptr);
+                                     wl.block_dim(2), wl.dyn_shmem_size, strm, void_args, nullptr);
     if (result != CUDA_SUCCESS && result != CUDA_ERROR_DEINITIALIZED) {
       const char* msg;
       cuGetErrorName(result, &msg);
@@ -201,8 +201,8 @@ class CUDAWrappedFunc {
   // Device function cache per device.
   // mark as mutable, to enable lazy initialization
   mutable std::array<CUfunction, kMaxNumGPUs> fcache_;
-  // thread axis configuration
-  ThreadAxisConfig thread_axis_cfg_;
+  // launch parameters configuration
+  LaunchParamConfig launch_param_config_;
 };
 
 class CUDAPrepGlobalBarrier {
@@ -241,7 +241,7 @@ PackedFunc CUDAModuleNode::GetFunction(const std::string& name,
   if (it == fmap_.end()) return PackedFunc();
   const FunctionInfo& info = it->second;
   CUDAWrappedFunc f;
-  f.Init(this, sptr_to_self, name, info.arg_types.size(), info.thread_axis_tags);
+  f.Init(this, sptr_to_self, name, info.arg_types.size(), info.launch_param_tags);
   return PackFuncVoidAddr(f, info.arg_types);
 }
 

src/runtime/file_utils.cc

@@ -43,7 +43,7 @@ void FunctionInfo::Save(dmlc::JSONWriter* writer) const {
   writer->BeginObject();
   writer->WriteObjectKeyValue("name", name);
   writer->WriteObjectKeyValue("arg_types", sarg_types);
-  writer->WriteObjectKeyValue("thread_axis_tags", thread_axis_tags);
+  writer->WriteObjectKeyValue("launch_param_tags", launch_param_tags);
   writer->EndObject();
 }
 
@@ -52,7 +52,9 @@ void FunctionInfo::Load(dmlc::JSONReader* reader) {
   std::vector<std::string> sarg_types;
   helper.DeclareField("name", &name);
   helper.DeclareField("arg_types", &sarg_types);
-  helper.DeclareField("thread_axis_tags", &thread_axis_tags);
+  helper.DeclareOptionalField("launch_param_tags", &launch_param_tags);
+  helper.DeclareOptionalField("thread_axis_tags",
+                              &launch_param_tags);  // for backward compatibility
   helper.ReadAllFields(reader);
   arg_types.resize(sarg_types.size());
   for (size_t i = 0; i < arg_types.size(); ++i) {
@@ -63,13 +65,13 @@ void FunctionInfo::Load(dmlc::JSONReader* reader) {
 void FunctionInfo::Save(dmlc::Stream* writer) const {
   writer->Write(name);
   writer->Write(arg_types);
-  writer->Write(thread_axis_tags);
+  writer->Write(launch_param_tags);
 }
 
 bool FunctionInfo::Load(dmlc::Stream* reader) {
   if (!reader->Read(&name)) return false;
   if (!reader->Read(&arg_types)) return false;
-  if (!reader->Read(&thread_axis_tags)) return false;
+  if (!reader->Read(&launch_param_tags)) return false;
   return true;
 }
 

src/runtime/meta_data.h

@@ -99,11 +99,14 @@ Module MetadataModuleCreate(
     const std::unordered_map<std::string, NDArray>& metadata,
     const std::unordered_map<std::string, std::vector<std::string>>& sym_vars);
 
+/*! \brief A tag to specify whether or not dynamic shared memory is used */
+constexpr const char* kUseDynamicSharedMemoryTag = "tir.use_dyn_shared_memory";
+
 /*! \brief function information needed by device */
 struct FunctionInfo {
   std::string name;
   std::vector<DLDataType> arg_types;
-  std::vector<std::string> thread_axis_tags;
+  std::vector<std::string> launch_param_tags;
 
   void Save(dmlc::JSONWriter* writer) const;
   void Load(dmlc::JSONReader* reader);

src/runtime/metal/metal_module.mm

@@ -178,15 +178,15 @@ void SaveToBinary(dmlc::Stream* stream) final {
   // initialize the METAL function.
   void Init(MetalModuleNode* m, ObjectPtr<Object> sptr, const std::string& func_name,
             size_t num_buffer_args, size_t num_pack_args,
-            const std::vector<std::string>& thread_axis_tags) {
+            const std::vector<std::string>& launch_param_tags) {
     w_ = metal::MetalWorkspace::Global();
     m_ = m;
     sptr_ = sptr;
     func_name_ = func_name;
     num_buffer_args_ = num_buffer_args;
     num_pack_args_ = num_pack_args;
     std::fill(scache_.begin(), scache_.end(), (id<MTLComputePipelineState>)nil);
-    thread_axis_cfg_.Init(num_buffer_args + num_pack_args, thread_axis_tags);
+    launch_param_config_.Init(num_buffer_args + num_pack_args, launch_param_tags);
     metal::MetalThreadEntry* t = metal::MetalThreadEntry::ThreadLocal();
     int dev_id = t->device.device_id;
     scache_[dev_id] = m->GetPipelineState(dev_id, func_name);
@@ -201,7 +201,7 @@ void operator()(TVMArgs args, TVMRetValue* rv, const ArgUnion64* pack_args) cons
       if (scache_[device_id] == nil) {
         scache_[device_id] = m_->GetPipelineState(device_id, func_name_);
       }
-      ThreadWorkLoad wl = thread_axis_cfg_.Extract(args);
+      ThreadWorkLoad wl = launch_param_config_.Extract(args);
       int blockSize = wl.block_dim(0) * wl.block_dim(1) * wl.block_dim(2);
       auto maxTotalThreadsPerThreadgroup = scache_[device_id].maxTotalThreadsPerThreadgroup;
       CHECK_LE(blockSize, maxTotalThreadsPerThreadgroup);
@@ -242,8 +242,8 @@ void operator()(TVMArgs args, TVMRetValue* rv, const ArgUnion64* pack_args) cons
   // Device state cache per device.
   // mark as mutable, to enable lazy initialization
   mutable std::array<id<MTLComputePipelineState>, kMetalMaxNumDevice> scache_;
-  // thread axis configuration
-  ThreadAxisConfig thread_axis_cfg_;
+  // launch parameters configuration
+  LaunchParamConfig launch_param_config_;
 };
 
 PackedFunc MetalModuleNode::GetFunction(const std::string& name,
@@ -261,7 +261,7 @@ void operator()(TVMArgs args, TVMRetValue* rv, const ArgUnion64* pack_args) cons
     MetalWrappedFunc f;
     size_t num_buffer_args = NumBufferArgs(info.arg_types);
     f.Init(this, sptr_to_self, name, num_buffer_args, info.arg_types.size() - num_buffer_args,
-           info.thread_axis_tags);
+           info.launch_param_tags);
     pf = PackFuncNonBufferArg(f, info.arg_types);
   };
   return pf;

src/runtime/opencl/opencl_module.cc

@@ -40,14 +40,14 @@ class OpenCLWrappedFunc {
   // initialize the OpenCL function.
   void Init(OpenCLModuleNode* m, ObjectPtr<Object> sptr, OpenCLModuleNode::KTRefEntry entry,
             std::string func_name, std::vector<size_t> arg_size,
-            const std::vector<std::string>& thread_axis_tags) {
+            const std::vector<std::string>& launch_param_tags) {
     w_ = m->GetGlobalWorkspace();
     m_ = m;
     sptr_ = sptr;
     entry_ = entry;
     func_name_ = func_name;
     arg_size_ = arg_size;
-    thread_axis_cfg_.Init(arg_size.size(), thread_axis_tags);
+    launch_param_config_.Init(arg_size.size(), launch_param_tags);
   }
   // invoke the function with void arguments
   void operator()(TVMArgs args, TVMRetValue* rv, void** void_args) const {
@@ -73,8 +73,8 @@ class OpenCLWrappedFunc {
       OPENCL_CALL(clSetKernelArg(kernel, i, arg_size_[i], arg));
     }
     cl_command_queue queue = w_->GetQueue(t->device);
-    ThreadWorkLoad wl = thread_axis_cfg_.Extract(args);
-    cl_uint work_dim = static_cast<cl_uint>(thread_axis_cfg_.work_dim());
+    ThreadWorkLoad wl = launch_param_config_.Extract(args);
+    cl_uint work_dim = static_cast<cl_uint>(launch_param_config_.work_dim());
     for (cl_uint i = 0; i < work_dim; ++i) {
       wl.work_size[i] *= wl.work_size[i + 3];
     }
@@ -96,8 +96,8 @@ class OpenCLWrappedFunc {
   std::string func_name_;
   // convert code for void argument
   std::vector<size_t> arg_size_;
-  // thread axis config
-  ThreadAxisConfig thread_axis_cfg_;
+  // launch parameters config
+  LaunchParamConfig launch_param_config_;
 };
 
 OpenCLModuleNode::~OpenCLModuleNode() {
@@ -148,7 +148,7 @@ PackedFunc OpenCLModuleNode::GetFunction(const std::string& name,
     }
   }
   // initialize the wrapped func.
-  f.Init(this, sptr_to_self, kid_map_.at(name), name, arg_size, info.thread_axis_tags);
+  f.Init(this, sptr_to_self, kid_map_.at(name), name, arg_size, info.launch_param_tags);
   return PackFuncVoidAddr(f, info.arg_types);
 }
 

src/runtime/rocm/rocm_module.cc

@@ -147,12 +147,12 @@ class ROCMWrappedFunc {
  public:
   // initialize the ROCM function.
   void Init(ROCMModuleNode* m, ObjectPtr<Object> sptr, const std::string& func_name,
-            size_t num_void_args, const std::vector<std::string>& thread_axis_tags) {
+            size_t num_void_args, const std::vector<std::string>& launch_param_tags) {
     m_ = m;
     sptr_ = sptr;
     func_name_ = func_name;
     std::fill(fcache_.begin(), fcache_.end(), nullptr);
-    thread_axis_cfg_.Init(num_void_args, thread_axis_tags);
+    launch_param_config_.Init(num_void_args, launch_param_tags);
   }
   // invoke the function with void arguments
   void operator()(TVMArgs args, TVMRetValue* rv, void* packed_args, size_t packed_nbytes) const {
@@ -164,13 +164,14 @@ class ROCMWrappedFunc {
 
     hipStream_t strm = static_cast<hipStream_t>(ROCMThreadEntry::ThreadLocal()->stream);
 
-    ThreadWorkLoad wl = thread_axis_cfg_.Extract(args);
+    ThreadWorkLoad wl = launch_param_config_.Extract(args);
     void* config[] = {HIP_LAUNCH_PARAM_BUFFER_POINTER, packed_args, HIP_LAUNCH_PARAM_BUFFER_SIZE,
                       &packed_nbytes, HIP_LAUNCH_PARAM_END};
     // HIP supports only extra_args.
-    ROCM_DRIVER_CALL(hipModuleLaunchKernel(
-        fcache_[device_id], wl.grid_dim(0), wl.grid_dim(1), wl.grid_dim(2), wl.block_dim(0),
-        wl.block_dim(1), wl.block_dim(2), 0, strm, nullptr, reinterpret_cast<void**>(&config)));
+    ROCM_DRIVER_CALL(hipModuleLaunchKernel(fcache_[device_id], wl.grid_dim(0), wl.grid_dim(1),
+                                           wl.grid_dim(2), wl.block_dim(0), wl.block_dim(1),
+                                           wl.block_dim(2), wl.dyn_shmem_size, strm, nullptr,
+                                           reinterpret_cast<void**>(&config)));
   }
 
  private:
@@ -183,8 +184,8 @@ class ROCMWrappedFunc {
   // Device function cache per device.
   // mark as mutable, to enable lazy initialization
   mutable std::array<hipFunction_t, kMaxNumGPUs> fcache_;
-  // thread axis configuration
-  ThreadAxisConfig thread_axis_cfg_;
+  // launch parameters configuration
+  LaunchParamConfig launch_param_config_;
 };
 
 PackedFunc ROCMModuleNode::GetFunction(const std::string& name,
@@ -195,7 +196,7 @@ PackedFunc ROCMModuleNode::GetFunction(const std::string& name,
   if (it == fmap_.end()) return PackedFunc();
   const FunctionInfo& info = it->second;
   ROCMWrappedFunc f;
-  f.Init(this, sptr_to_self, name, info.arg_types.size(), info.thread_axis_tags);
+  f.Init(this, sptr_to_self, name, info.arg_types.size(), info.launch_param_tags);
   return PackFuncPackedArg(f, info.arg_types);
 }
 

src/runtime/thread_storage_scope.h

@@ -19,7 +19,7 @@
 
 /*!
  * \file thread_storage_scope.h
- * \brief Extract thread axis configuration from TVMArgs.
+ * \brief Extract launch parameters configuration from TVMArgs.
  */
 #ifndef TVM_RUNTIME_THREAD_STORAGE_SCOPE_H_
 #define TVM_RUNTIME_THREAD_STORAGE_SCOPE_H_
@@ -29,6 +29,8 @@
 #include <string>
 #include <vector>
 
+#include "meta_data.h"
+
 namespace tvm {
 namespace runtime {
 
@@ -182,6 +184,8 @@ struct ThreadScope {
 struct ThreadWorkLoad {
   // array, first three are thread configuration.
   size_t work_size[6];
+  // Dynamic shared memory allocation size in bytes.
+  size_t dyn_shmem_size{0};
   /*!
    * \param i The block dimension.
    * \return i-th block dim
@@ -193,17 +197,23 @@ struct ThreadWorkLoad {
    */
   inline size_t grid_dim(size_t i) const { return work_size[i]; }
 };
-/*! \brief Thread axis configuration */
-class ThreadAxisConfig {
+/*! \brief Launch parameters configuration */
+class LaunchParamConfig {
  public:
-  void Init(size_t base, const std::vector<std::string>& thread_axis_tags) {
+  void Init(size_t base, const std::vector<std::string>& launch_param_tags) {
     base_ = base;
     std::vector<bool> filled(6, false);
-    for (size_t i = 0; i < thread_axis_tags.size(); ++i) {
-      const std::string& tag = thread_axis_tags[i];
-      ThreadScope ts = ThreadScope::Create(tag);
-      arg_index_map_.push_back(ts.rank * 3 + ts.dim_index);
-      filled[ts.rank * 3 + ts.dim_index] = true;
+    for (size_t i = 0; i < launch_param_tags.size(); ++i) {
+      const std::string& tag = launch_param_tags[i];
+      if (tag == kUseDynamicSharedMemoryTag) {
+        ICHECK_EQ(i, launch_param_tags.size() - 1)
+            << "kUseDynamicSharedMemoryTag should be the last tag in launch_param_tags.";
+        use_dyn_shared_memory_ = true;
+      } else {
+        ThreadScope ts = ThreadScope::Create(tag);
+        arg_index_map_.push_back(ts.rank * 3 + ts.dim_index);
+        filled[ts.rank * 3 + ts.dim_index] = true;
+      }
     }
     work_dim_ = 1;
     for (int i = 0; i < 3; ++i) {
@@ -223,6 +233,9 @@ class ThreadAxisConfig {
         w.work_size[arg_index_map_[i]] = size;
       }
     }
+    if (use_dyn_shared_memory_) {
+      w.dyn_shmem_size = static_cast<size_t>(x.values[base_ + arg_index_map_.size()].v_int64);
+    }
     return w;
   }
   // return the work dim
@@ -235,6 +248,8 @@ class ThreadAxisConfig {
   size_t work_dim_;
   /*! \brief The index mapping. */
   std::vector<uint32_t> arg_index_map_;
+  /*! \brief Whether or not use dynamic shared memory. */
+  bool use_dyn_shared_memory_{false};
 };
 
 }  // namespace runtime