Simple parallelism, add -openmp flags and omp parallel for Acc16/32 Unit Test (#14)

Summary:
Pull Request resolved: https://github.com/pytorch/FBGEMM/pull/14

This DIFF triggered a concurrent bug in the unit test.

It is weird that there are no errors for "SpMDMTest", while errors are reported for "NoRequantizeTest".

Update 1:
There might be problems with "memCopy" function. Then I change "Cint32_buffer.data()" to "Cint32_fb.data()" (see my inline comment) so that the accumulation buffer and the output buffer are the same. It appears that we can output the correct result.

I have a discussion with Daya. Now I understand the reason for the failure of this unit test
- For the purpose of this unit test, we should just use the same buffer "Cint32_fb.data()" for the accumulation and output. Not sure why this issue is not found in the original code.
- If the thread number is not 1, and we we use different buffers: "Cint32_buffer" for the accumulation buffer and "Cint32_fb" for the output buffer, then the pointers of "Cint32_buffer.data()" is actually shared by different threads. When doing the accumulation inside "ExecuteKernelU8S8.cc", different threads will just write to the same memory location: Check the code below
    int32_t* C_buffer_row_start = C_buffer_ +
        ((C_buffer_ == reinterpret_cast<int32_t*>(matC_)) ? row_start_A * ldc_
                                                          : 0);
- If the thread number is not 1, and we use the same buffers: "Cint32_fb.data()" for the accumulation and output. According to the above code, different threads will write to different memory locations.

Update 2:
I add a new test case "{1024, 512, 258}" in Acc16 and Acc32 unit tests. "PackedRequantizeAcc16Test" runs well, but "PackedRequantizeTest" is broken.

Update 3:
I change the above code snippet to
    int32_t* C_buffer_row_start = C_buffer_ + row_start_A * ldc_;

Finally we get both Acc16 and Acc32 tests passed. Now different threads will always write to different memory locations.

Update 4:

Jongsoo comments that reusing the first row block of C_buffer_ is mostly to optimize for cache not for memory allocation size (this was making a big difference in xray ocr perf. don't remember exact number). A right thing to do is to have each thread to use different portion of C_buffer_.

So I optimize the above code snippet to

   // If the accumulation buffer C_buffer_ is the same as matC_ (inplace output
    // processing), then each thread use the different parts of output buffer
    // matC_;
    // Otherwise, each thread uses different portions of the accumulation
    // buffer C_buffer_. Note that each thread can use at most MC * n portion of
    // C_buffer_. If the number of threads is 1, the only thread (thread 0) will
    // always reuse the first rowblock of C_buffer_.
    int32_t* C_buffer_row_start = C_buffer_ +
      ((C_buffer_ == reinterpret_cast<int32_t*>(matC_)) ? row_start_A * ldc_
       : std::min(thread_id_ * mbSize_ * ldc_, row_start_A * ldc_));

Note that `thread_id` and `num_threads` is passed as the arguments into `ExecuteKernel`.

Update 5:
Rebase, Also add the parts of D12937408 to remove the dependency.

Reviewed By: jspark1105

Differential Revision: D13001149

fbshipit-source-id: b16c20863dc467de6faaefcaf1134cf1036f8a65

1 files changed, 10 insertions, 0 deletions

diff --git a/CMakeLists.txt b/CMakeLists.txt
index d957bed..9b7a6c8 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -51,6 +51,16 @@ if(NOT COMPILER_SUPPORTS_AVX512)
   message(FATAL_ERROR "A compiler with AVX512 support is required.")
 endif()
 
+#check if compiler supports openmp
+find_package(OpenMP)
+if (OPENMP_FOUND)
+  set (CMAKE_C_FLAGS "${CMAKE_C_FLAGS} ${OpenMP_C_FLAGS}")
+  set (CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${OpenMP_CXX_FLAGS}")
+  set (CMAKE_EXE_LINKER_FLAGS "${CMAKE_EXE_LINKER_FLAGS} ${OpenMP_EXE_LINKER_FLAGS}")
+else()
+  message(WARNING "OpenMP is not supported by the compiler")
+endif()
+
 #All the source files that use avx512 instructions statically
 set(FBGEMM_AVX512_SRCS src/Utils_avx512.cc)