Reduction for int8 and bfloat16 (#125)

* Use thread cluster descriptor and explicit M_K 2d descriptor to simply Blockwise Reduction

* Change by replacing ReduceDims by NumReduceDims as Device Reduce interface template parameter

* Rename the folder name for the pool2d and reduce examples

* Update to reduction test scripts

* Add Readme for pool2d_fwd and reduce_blockwise examples

* Add support for int8_t reduction (ADD/AVG, MIN/MAX/AMAX)

* Tiny fix in reduce profiler and tiny update in reduce testing scripts

* Tiny fix in testing script profile_reduce_no_index.sh

* Tiny fix in testing script profile_reduce_no_index.sh

* Add support for bfp16 reduction (using bhalf_t = ushort)

* Tiny fix in amd_buffer_addressing.hpp

* Tiny change in script/profile_reduce_with_index.sh

* Use AccDataType for Beta value and use element_wise::PassThrough

* Use type_convert for type converting in host layer reduction

* Renaming and refining in Reduction profiler/device layer/examples

* Renaming and refining in Reduction profiler/device layer/examples

* Renaming all NumReduceDims to NumReduceDim

* Fix the leaked type_convert in ThreadwiseTensorSliceTransfer_v2

* Update to testing scripts to add bf16 support

* added more static_assert

* Remove buggy tunable configurations defined in device_reduce_instance_xxx.hpp

* Add static_assert to give compile-time warning for incorrect thread slice-size/vector-size configurations

* minor change

* Refine and fix (in GetWorkspaceSizeInBytes of MultiBlockPartialReduce) to make int8 completely pass

* Tiny renaming in gridwise_2d_reduction_multiblock_partial_reduce.hpp

* Tiny fix in script/profile_reduce_no_index.sh

* Refine in DeviceReduce layer with regard to using NumInvariantDim/NumReduceDim or InvariantDims/ReduceDims

* Generic renaming in host reduction and DeviceReduce layer

* Add support for 4-d all dimension reduction in the profiler and add_device_reduce_xxx instances

* Use multi-thread and simplification for host Reduction implementation

* Add ctest for reduction

* Update to clarify the using of data init method in produce_reduce/example_reduce/test_reduce/

* Update to the reduce CTest executables to enable default testing behavior when no command argument

* Renaming

Co-authored-by: Jianfeng yan <jfyan008@gmail.com>

example/12_reduce/README.md

@@ -37,7 +37,7 @@ cmake                                                                  \
 ```bash
 # -D <xxx> : input 4-d tensor lengths
 # -v <x> :   verification (0=no, 1=yes)
-#arg1: initialization (0=no init, 1=integer value, 2=decimal value)
+#arg1: initialization (0=no init, 1=single integer value, 2=scope integer value, 3=decimal value)
 #arg2: run kernel # of times (>1)
 ./bin/reduce_blockwise -D 16,64,32,960 -v 1 1 10
 ```

example/12_reduce/reduce_blockwise.cpp

@@ -13,7 +13,7 @@
 #include "device_base.hpp"
 #include "device_reduce_blockwise.hpp"
 #include "host_reduce_util.hpp"
-#include "host_generic_reduction.hpp"
+#include "host_reduction.hpp"
 
 #include "reduction_enums.hpp"
 #include "reduction_operator_mapping.hpp"
@@ -21,13 +21,13 @@
 using namespace ck;
 using namespace ck::tensor_operation::device;
 
-using InDataType  = half_float::half;
-using OutDataType = half_float::half;
+using InDataType  = ck::half_t;
+using OutDataType = ck::half_t;
 using AccDataType = float;
 
-using kInDataType  = ck::half_t;
-using kOutDataType = ck::half_t;
-using kAccDataType = float;
+using HostInDataType  = half_float::half;
+using HostOutDataType = half_float::half;
+using HostAccDataType = float;
 
 constexpr int Rank         = 4;
 constexpr int NumReduceDim = 3;
@@ -43,9 +43,9 @@ using InElementwiseOperation =
 using AccElementwiseOperation =
     typename reduce_unary_operator<AccDataType, ReduceOpId, true, true>::AccElementwiseOperation;
 
-using DeviceReduceInstance = DeviceReduceBlockWise<kInDataType,
-                                                   kAccDataType,
-                                                   kOutDataType,
+using DeviceReduceInstance = DeviceReduceBlockWise<InDataType,
+                                                   AccDataType,
+                                                   OutDataType,
                                                    Rank,
                                                    NumReduceDim,
                                                    ReduceOperation,
@@ -135,6 +135,10 @@ class SimpleAppArgs
         std::cout << "--verify or -v, 1/0 to indicate whether to verify the reduction result by "
                      "comparing with the host-based reduction"
                   << std::endl;
+        std::cout << "Arg1 -- init method (0=no init, 1=single integer value, 2=scope integer "
+                     "value, 3=decimal value)"
+                  << std::endl;
+        std::cout << "Arg2 -- number of repeats to run the kernel" << std::endl;
     };
 
     int processArgs(int argc, char* argv[])
@@ -263,20 +267,21 @@ int main(int argc, char* argv[])
     {
         switch(args.init_method)
         {
-        case 0:
-            in.GenerateTensorValue(GeneratorTensor_1<InDataType>{}, num_thread);
-            if(beta != 0.0f)
-                out_ref.GenerateTensorValue(GeneratorTensor_1<InDataType>{}, num_thread);
-            break;
+        case 0: break;
         case 1:
+            in.GenerateTensorValue(GeneratorTensor_1<InDataType>{1}, num_thread);
+            if(beta != 0.0f)
+                out_ref.GenerateTensorValue(GeneratorTensor_1<InDataType>{1}, num_thread);
+            break;
+        case 2:
             in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5}, num_thread);
             if(beta != 0.0f)
                 out_ref.GenerateTensorValue(GeneratorTensor_2<InDataType>{-5, 5}, num_thread);
             break;
         default:
-            in.GenerateTensorValue(GeneratorTensor_2<InDataType>{1, 5}, num_thread);
+            in.GenerateTensorValue(GeneratorTensor_3<InDataType>{-5.0, 5.0}, num_thread);
             if(beta != 0.0f)
-                out_ref.GenerateTensorValue(GeneratorTensor_2<InDataType>{1, 5}, num_thread);
+                out_ref.GenerateTensorValue(GeneratorTensor_3<InDataType>{-5.0, 5.0}, num_thread);
         }
 
         if(beta != 0.0f)
@@ -293,17 +298,27 @@ int main(int argc, char* argv[])
     if(beta != 0.0f)
         out_dev.ToDevice(out.mData.data());
 
-    size_t indicesSizeInBytes = NeedIndices ? out.mDesc.GetElementSize() * sizeof(int) : 0;
+    size_t indicesSizeInBytes = NeedIndices ? out.mDesc.GetElementSize() * sizeof(int32_t) : 0;
 
     DeviceMem out_indices_dev(indicesSizeInBytes);
 
     if(args.do_verification)
     {
-        ReductionHost<InDataType, AccDataType, OutDataType, ReduceOpId, PropagateNan, NeedIndices>
+        ReductionHost<HostInDataType,
+                      HostAccDataType,
+                      HostOutDataType,
+                      ReduceOpId,
+                      Rank,
+                      NumReduceDim,
+                      PropagateNan,
+                      NeedIndices>
             hostReduce(in.mDesc, out_ref.mDesc, invariantDims, reduceDims);
 
-        hostReduce.Run(
-            alpha, in.mData.data(), beta, out_ref.mData.data(), out_indices_ref.mData.data());
+        hostReduce.Run(alpha,
+                       reinterpret_cast<const HostInDataType*>(in.mData.data()),
+                       beta,
+                       reinterpret_cast<HostOutDataType*>(out_ref.mData.data()),
+                       out_indices_ref.mData.data());
     };
 
     const auto i_inLengths  = to_int_vector(args.inLengths);
@@ -313,7 +328,7 @@ int main(int argc, char* argv[])
 
     auto reduce = DeviceReduceInstance{};
 
-    auto wsSizeInBytes = reduce.GetWorkspaceSizeInBytes(i_inLengths);
+    auto wsSizeInBytes = reduce.GetWorkspaceSizeInBytes(i_inLengths, reduceDims);
 
     DeviceMem ws_dev(wsSizeInBytes);