Reduction in Composable Kernel (#82)

* Initial adding of generic reduction

* Initial adding of generic reduction ...

* Updates to make compiling done

* clang-format all files

* clang-format some files again

* Renaming in profiler/include/profile_reduce.hpp

* Updates and make BlockWise cases passed

* Updates and make ThreadWise and MultiBlockTwoCall cases passed

* Remove the support for MUL and NORM1 reduceOp from the profiler and the device instances

* Change to replace the dim0_max_vector_size/dim1_max_vector_size template argument in the device reduce classes

* format

* adding pooling

* added max and average pooling

* comment out cout and kernel timing

* Tiny simplification in profiler/reduce_profiler.cpp

* Add example for reduce_blockwise

* Tiny updates

* Change to pass the ElementWiseOp from device layer to kernel

* Fix the vectorDim and vectorSize in Device layer

* Enable vector load on both dim0 and dim1 for Threadwise method

* Tiny updates

* Change to let the user to pass the preUnaryOp and posUnaryOp

* Make pooling example work

* split device_reduce_instance into two libraries

* Tiny update

* Replace nanPropaOpt enum by boolean propagate_nan

* Simplification in DeviceReduce layer codes

* update build

* Change to clarify the difference between ck::half_t and half_float::half

* Renaming in all the reduction codes

* Add VectorSize as template parameter for device layer

* Add BetaIsZero as kernel template and as AccDataType for alpha

* print

* Small updates for pooling

* Updates for host_generic_reduction for reference

* Update to make AVG pooling pass

* Update to make MAX pooling with indices output pass

* fix

* add OutDst vector store to threadwise reduction and pooling

* tweak

* turn off check_indices that caused build issue

* refactor pooling

* clean up

* turn off check_indices for building issue for php-compiler

* add more tile size for odd C

* tweak conv for odd C

* update script

* clean up elementwise op

* add hack in reduction_operator.hpp to avoid compile error. To fix it, need to use element_wise_op in reduction op

* Add OutVectorSize as device and kernel tunable, also update to Elementwise Operations

* Move reduce operator mapping to host layer file reduction_operator_mapping.hpp from reduction_operator.hpp

* Change to the unary operators

* Move the definitions of unary operations to element_wise_operation.hpp

* re-org files

* Refine in device interfaces and multiblock kernels

* Split the reduction configurations into instances for specific methods

* Update in getTypeString() of device pool2d

* Renaming in host and kernel

* Tiny update in profiler/src/profiler.cpp

* Uncomment in device_operation/CMakeLists.txt to enable the building of all operations

* Make check_indices a templated function to remove some linking issue

* Renaming in the profiler reduce module

* Add support for double Reduction (but disable MultiblockAtomicAdd for double)

* Tiny correction of literal string

* Rename DevicePoolFwd to DevicePool2dFwd

* Split device_reduce_instance_xxx.cpp files according to the data types to speed up compiling

* Add comments for lists of configurations, lists of instances and references of add_reduce_instances_xxx

* Remove un-used header file gridwise_generic_reduction_wrapper_common.hpp

* Renaming and refining in the Reduction codes

* Tiny change in the unary operators

* Renaming symbols and files

* Renaming symbols in the kernels

* Move kernel kernel_set_buffer_value to separate file

* Add IndexDataType template parameter for kernels and use int32_t as index data type in device layer

* Tiny update in the kernels

* Remove definition of sqrtf()/isnan()/abs() for half_t due to some ADL issue

* Simplify a helper function in device layer

* Tiny adjustment in testing data initialization

* Renaming in kernel/device/host

* Add two testing scripts for reduction

* Refine the Unary operators in element_wise_operation.hpp

* Update in the reduce profiler module

* Update to the reduction testing scripts

* reduce compile parallelism

* change CI docker to rocm5.0

* remove unused variables

* fix build

Co-authored-by: Chao Liu <chao.liu2@amd.com>

profiler/src/profiler.cpp

@@ -2,8 +2,7 @@
 #include <numeric>
 #include <initializer_list>
 #include <cstdlib>
-#include <stdlib.h>
-#include <half.hpp>
+#include <cstring>
 
 int profile_gemm(int, char*[]);
 int profile_batched_gemm(int, char*[]);
@@ -15,6 +14,7 @@ int profile_conv_fwd_bias_relu(int, char*[]);
 int profile_conv_fwd_bias_relu_add(int, char*[]);
 int profile_conv_fwd_bias_relu_atomic_add(int, char*[]);
 int profile_conv_bwd_data(int, char*[]);
+int profile_reduce(int, char*[]);
 
 int main(int argc, char* argv[])
 {
@@ -58,6 +58,10 @@ int main(int argc, char* argv[])
     {
         return profile_conv_bwd_data(argc, argv);
     }
+    else if(strcmp(argv[1], "reduce") == 0)
+    {
+        return profile_reduce(argc, argv);
+    }
     else
     {
         // clang-format off
@@ -69,7 +73,8 @@ int main(int argc, char* argv[])
                "                        conv_fwd_bias_relu: ForwardConvolution+Bias+ReLU\n"
                "                        conv_fwd_bias_relu_add: ForwardConvolution+Bias+ReLU+Add\n"
                "                        conv_fwd_bias_relu_atomic_add: ForwardConvolution+Bias+ReLU+AtomicAdd\n"
-               "                        conv_bwd: BackwardConvolution\n");
+               "                        conv_bwd: BackwardConvolution\n"
+               "                        reduce: REDUCE\n");
         // clang-format on
 
         return 0;