[fft][1 of 3] build system and helpers to support cuFFT and MKL (#5855)

This is the first of three PRs that #5537 will be split into.

This PR adds mkl headers to included files, and provides helper functions for MKL fft and cuFFT.
In particular, on POSIX, headers are using mkl-include from conda, and on Windows, it is from a new file @yf225 and I made and uploaded to s3.

* add mkl-include to required packages

* include MKL headers; add AT_MKL_ENABLED flag; add a method to query MKL availability

* Add MKL and CUFFT helpers

.jenkins/macos-build-test.sh

@@ -9,7 +9,7 @@ rm -rf $PWD/miniconda3
 bash $PWD/miniconda3.sh -b -p $PWD/miniconda3
 export PATH="$PWD/miniconda3/bin:$PATH"
 source $PWD/miniconda3/bin/activate
-conda install -y numpy pyyaml setuptools cmake cffi ninja
+conda install -y mkl mkl-include numpy pyyaml setuptools cmake cffi ninja
 
 # Build and test PyTorch
 git submodule update --init --recursive

.jenkins/win-build.sh

@@ -32,8 +32,9 @@ cat >ci_scripts/build_pytorch.bat <<EOL
 set PATH=C:\\Program Files\\CMake\\bin;C:\\Program Files\\7-Zip;C:\\curl-7.57.0-win64-mingw\\bin;C:\\Program Files\\Git\\cmd;C:\\Program Files\\Amazon\\AWSCLI;%PATH%
 
 :: Install MKL
-aws s3 cp s3://ossci-windows/mkl.7z mkl.7z --quiet && 7z x -aoa mkl.7z -omkl
+aws s3 cp s3://ossci-windows/mkl_with_headers.7z mkl.7z --quiet && 7z x -aoa mkl.7z -omkl
-set LIB=%cd%\\mkl;%LIB%
+set CMAKE_INCLUDE_PATH=%cd%\\mkl\\include
+set LIB=%cd%\\mkl\\lib;%LIB
 
 :: Install MAGMA
 aws s3 cp s3://ossci-windows/magma_cuda90_release.7z magma_cuda90_release.7z --quiet && 7z x -aoa magma_cuda90_release.7z -omagma_cuda90_release
@@ -47,7 +48,7 @@ IF EXIST C:\\Jenkins\\Miniconda3 ( rd /s /q C:\\Jenkins\\Miniconda3 )
 curl https://repo.continuum.io/miniconda/Miniconda3-latest-Windows-x86_64.exe -O
 .\Miniconda3-latest-Windows-x86_64.exe /InstallationType=JustMe /RegisterPython=0 /S /AddToPath=0 /D=C:\\Jenkins\\Miniconda3
 call C:\\Jenkins\\Miniconda3\\Scripts\\activate.bat C:\\Jenkins\\Miniconda3
-call conda install -y -q numpy mkl cffi pyyaml boto3
+call conda install -y -q numpy cffi pyyaml boto3
 
 :: Install ninja
 pip install ninja

Dockerfile

@@ -14,11 +14,11 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
 
 RUN curl -o ~/miniconda.sh -O  https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh  && \
      chmod +x ~/miniconda.sh && \
-     ~/miniconda.sh -b -p /opt/conda && \     
+     ~/miniconda.sh -b -p /opt/conda && \
      rm ~/miniconda.sh && \
-     /opt/conda/bin/conda install numpy pyyaml scipy ipython mkl && \
+     /opt/conda/bin/conda install numpy pyyaml scipy ipython mkl mkl-include && \
      /opt/conda/bin/conda install -c soumith magma-cuda90 && \
-     /opt/conda/bin/conda clean -ya 
+     /opt/conda/bin/conda clean -ya
 ENV PATH /opt/conda/bin:$PATH
 # This must be done before pip so that requirements.txt is available
 WORKDIR /opt/pytorch

README.md

@@ -171,7 +171,7 @@ On Linux
 export CMAKE_PREFIX_PATH="$(dirname $(which conda))/../" # [anaconda root directory]
 
 # Install basic dependencies
-conda install numpy pyyaml mkl setuptools cmake cffi typing
+conda install numpy pyyaml mkl mkl-include setuptools cmake cffi typing
 
 # Add LAPACK support for the GPU
 conda install -c pytorch magma-cuda80 # or magma-cuda90 if CUDA 9

aten/CMakeLists.txt

@@ -380,10 +380,13 @@ MACRO(Install_Required_Library ln)
 ENDMACRO(Install_Required_Library libname)
 
 FIND_PACKAGE(BLAS)
+SET(AT_MKL_ENABLED 0)
 IF(BLAS_FOUND)
   SET(USE_BLAS 1)
   IF(BLAS_INFO STREQUAL "mkl")
     ADD_DEFINITIONS(-DTH_BLAS_MKL)
+    INCLUDE_DIRECTORIES(${BLAS_INCLUDE_DIR})  # include MKL headers
+    SET(AT_MKL_ENABLED 1)
   ENDIF()
 ENDIF(BLAS_FOUND)
 

aten/src/ATen/CMakeLists.txt

@@ -128,12 +128,14 @@ FILE(GLOB base_cpp RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} "*.cpp")
 FILE(GLOB native_cpp RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} "native/*.cpp")
 FILE(GLOB native_cudnn_cpp RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} "native/cudnn/*.cpp")
 FILE(GLOB native_cuda_cu RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} "native/cuda/*.cu")
+FILE(GLOB native_mkl_cpp RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} "native/mkl/*.cpp")
 
 FILE(GLOB_RECURSE cuda_h
      RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}"
      "cuda/*.cuh" "cuda/*.h" "cudnn/*.cuh" "cudnn/*.h")
 
 FILE(GLOB cudnn_cpp RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} "cudnn/*.cpp")
+FILE(GLOB mkl_cpp RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} "mkl/*.cpp")
 
 FILE(GLOB all_python RELATIVE ${CMAKE_CURRENT_SOURCE_DIR} "*.py")
 
@@ -179,8 +181,7 @@ ADD_CUSTOM_TARGET(aten_files_are_generated
 )
 
 
-SET(all_cpp ${base_cpp} ${native_cpp} ${native_cudnn_cpp} ${generated_cpp} ${ATen_CPU_SRCS} ${cpu_kernel_cpp})
+SET(all_cpp ${base_cpp} ${native_cpp} ${native_cudnn_cpp} ${native_mkl_cpp} ${generated_cpp} ${ATen_CPU_SRCS} ${cpu_kernel_cpp})
-
 
 INCLUDE_DIRECTORIES(${ATen_CPU_INCLUDE})
 IF(NOT NO_CUDA)
@@ -192,6 +193,9 @@ IF(NOT NO_CUDA)
   IF(CUDNN_FOUND)
     SET(all_cpp ${all_cpp} ${cudnn_cpp})
   ENDIF()
+  IF(AT_MKL_ENABLED)
+    SET(all_cpp ${all_cpp} ${mkl_cpp})
+  ENDIF()
 endif()
 
 filter_list(generated_h generated_cpp "\\.h$")
@@ -309,6 +313,7 @@ IF(CUDA_FOUND)
     ${CUDA_cusparse_LIBRARY}
     ${CUDA_curand_LIBRARY})
   CUDA_ADD_CUBLAS_TO_TARGET(ATen)
+  CUDA_ADD_CUFFT_TO_TARGET(ATen)
 
   if(CUDNN_FOUND)
     target_link_libraries(ATen ${CUDNN_LIBRARIES})

aten/src/ATen/Config.h.in

@@ -1,12 +1,13 @@
 #pragma once
 
-// Test these using #if AT_CUDA_ENABLED()(), not #ifdef, so that it's
+// Test these using #if AT_CUDA_ENABLED(), not #ifdef, so that it's
 // obvious if you forgot to include Config.h
 //    c.f. https://stackoverflow.com/questions/33759787/generating-an-error-if-checked-boolean-macro-is-not-defined
 
 #define AT_CUDA_ENABLED() @AT_CUDA_ENABLED@
 #define AT_CUDNN_ENABLED() @AT_CUDNN_ENABLED@
 #define AT_NNPACK_ENABLED() @AT_NNPACK_ENABLED@
+#define AT_MKL_ENABLED() @AT_MKL_ENABLED@
 
 #if !AT_CUDA_ENABLED() && AT_CUDNN_ENABLED()
 #error "Cannot enable CuDNN without CUDA"

aten/src/ATen/Context.cpp

@@ -89,6 +89,14 @@ void Context::setBenchmarkCuDNN(bool b) {
   benchmark_cudnn = b;
 }
 
+bool Context::hasMKL() const {
+#if AT_MKL_ENABLED()
+  return true;
+#else
+  return false;
+#endif
+}
+
 bool Context::hasCUDA() const {
 #if AT_CUDA_ENABLED()
   int count;

aten/src/ATen/Context.h

@@ -43,6 +43,7 @@ public:
       runtime_error("%s backend type not enabled.",toString(p));
     return *generator;
   }
+  bool hasMKL() const;
   bool hasCUDA() const;
   int64_t current_device() const;
   // defined in header so that getType has ability to inline
@@ -103,7 +104,7 @@ static inline void init() {
 }
 
 static inline Type& getType(Backend p, ScalarType s) {
-  return globalContext().getType(p,s);
+  return globalContext().getType(p, s);
 }
 
 static inline Type& CPU(ScalarType s) {
@@ -118,6 +119,10 @@ static inline bool hasCUDA() {
   return globalContext().hasCUDA();
 }
 
+static inline bool hasMKL() {
+  return globalContext().hasMKL();
+}
+
 static inline int64_t current_device() {
   return globalContext().current_device();
 }

aten/src/ATen/mkl/Descriptors.h

@@ -0,0 +1,44 @@
+#pragma once
+
+#include "Exceptions.h"
+#include <mkl_dfti.h>
+#include <ATen/Tensor.h>
+
+namespace at { namespace native {
+
+struct DftiDescriptorDeleter {
+  void operator()(DFTI_DESCRIPTOR* desc) {
+    if (desc != nullptr) {
+      MKL_DFTI_CHECK(DftiFreeDescriptor(&desc));
+    }
+  }
+};
+
+class DftiDescriptor {
+public:
+  void init(DFTI_CONFIG_VALUE precision, DFTI_CONFIG_VALUE signal_type, MKL_LONG signal_ndim, MKL_LONG* sizes) {
+    if (desc_ != nullptr) {
+      throw std::runtime_error("DFTI DESCRIPTOR can only be initialized once");
+    }
+    DFTI_DESCRIPTOR *raw_desc;
+    if (signal_ndim == 1) {
+      MKL_DFTI_CHECK(DftiCreateDescriptor(&raw_desc, precision, signal_type, 1, sizes[0]));
+    } else {
+      MKL_DFTI_CHECK(DftiCreateDescriptor(&raw_desc, precision, signal_type, signal_ndim, sizes));
+    }
+    desc_.reset(raw_desc);
+  }
+
+  DFTI_DESCRIPTOR *get() const {
+    if (desc_ == nullptr) {
+      throw std::runtime_error("DFTI DESCRIPTOR has not been initialized");
+    }
+    return desc_.get();
+  }
+
+private:
+  std::unique_ptr<DFTI_DESCRIPTOR, DftiDescriptorDeleter> desc_;
+};
+
+
+}}  // at::native

aten/src/ATen/mkl/Exceptions.h

@@ -0,0 +1,19 @@
+#pragma once
+
+#include <string>
+#include <stdexcept>
+#include <sstream>
+#include <mkl_dfti.h>
+
+namespace at { namespace native {
+
+static inline void MKL_DFTI_CHECK(MKL_INT status)
+{
+  if (status && !DftiErrorClass(status, DFTI_NO_ERROR)) {
+    std::ostringstream ss;
+    ss << "MKL FFT error: " << DftiErrorMessage(status);
+    throw std::runtime_error(ss.str());
+  }
+}
+
+}}  // namespace at::native

aten/src/ATen/mkl/Limits.h

@@ -0,0 +1,11 @@
+#pragma once
+
+#include <mkl_types.h>
+
+namespace at { namespace native {
+
+  // Since size of MKL_LONG varies on different platforms (linux 64 bit, windows
+  // 32 bit), we need to programmatically calculate the max.
+  static int64_t MKL_LONG_MAX = ((1LL << (sizeof(MKL_LONG) * 8 - 2)) - 1) * 2 + 1;
+
+}}  // namespace

aten/src/ATen/mkl/README.md

@@ -0,0 +1,4 @@
+All files living in this directory are written with the assumption that MKL is available,
+which means that these code are not guarded by `#if AT_MKL_ENABLED()`. Therefore, whenever
+you need to use definitions from here, please guard the `#include<ATen/mkl/*.h>` and
+definition usages with `#if AT_MKL_ENABLED()` macro, e.g. [SpectralOps.cpp](native/mkl/SpectralOps.cpp).

aten/src/ATen/native/cuda/CuFFTUtils.h

@@ -0,0 +1,84 @@
+#pragma once
+
+#include "ATen/ATen.h"
+#include "ATen/Config.h"
+
+#include <string>
+#include <stdexcept>
+#include <sstream>
+#include <cufft.h>
+#include <cufftXt.h>
+
+
+namespace at { namespace native {
+
+static inline std::string _cudaGetErrorEnum(cufftResult error)
+{
+  switch (error)
+  {
+    case CUFFT_SUCCESS:
+      return "CUFFT_SUCCESS";
+    case CUFFT_INVALID_PLAN:
+      return "CUFFT_INVALID_PLAN";
+    case CUFFT_ALLOC_FAILED:
+      return "CUFFT_ALLOC_FAILED";
+    case CUFFT_INVALID_TYPE:
+      return "CUFFT_INVALID_TYPE";
+    case CUFFT_INVALID_VALUE:
+      return "CUFFT_INVALID_VALUE";
+    case CUFFT_INTERNAL_ERROR:
+      return "CUFFT_INTERNAL_ERROR";
+    case CUFFT_EXEC_FAILED:
+      return "CUFFT_EXEC_FAILED";
+    case CUFFT_SETUP_FAILED:
+      return "CUFFT_SETUP_FAILED";
+    case CUFFT_INVALID_SIZE:
+      return "CUFFT_INVALID_SIZE";
+    case CUFFT_UNALIGNED_DATA:
+      return "CUFFT_UNALIGNED_DATA";
+    case CUFFT_INCOMPLETE_PARAMETER_LIST:
+      return "CUFFT_INCOMPLETE_PARAMETER_LIST";
+    case CUFFT_INVALID_DEVICE:
+      return "CUFFT_INVALID_DEVICE";
+    case CUFFT_PARSE_ERROR:
+      return "CUFFT_PARSE_ERROR";
+    case CUFFT_NO_WORKSPACE:
+      return "CUFFT_NO_WORKSPACE";
+    case CUFFT_NOT_IMPLEMENTED:
+      return "CUFFT_NOT_IMPLEMENTED";
+    case CUFFT_LICENSE_ERROR:
+      return "CUFFT_LICENSE_ERROR";
+    case CUFFT_NOT_SUPPORTED:
+      return "CUFFT_NOT_SUPPORTED";
+    default:
+      std::ostringstream ss;
+      ss << "unknown error " << error;
+      return ss.str();
+  }
+}
+
+static inline void CUFFT_CHECK(cufftResult error)
+{
+  if (error != CUFFT_SUCCESS) {
+    std::ostringstream ss;
+    ss << "cuFFT error: " << _cudaGetErrorEnum(error);
+    throw std::runtime_error(ss.str());
+  }
+}
+
+class CufftHandle {
+public:
+  explicit CufftHandle() {
+    CUFFT_CHECK(cufftCreate(&raw_plan));
+  }
+
+  const cufftHandle &get() const { return raw_plan; }
+
+  ~CufftHandle() {
+    CUFFT_CHECK(cufftDestroy(raw_plan));
+  }
+private:
+  cufftHandle raw_plan;
+};
+
+}} // at::native

aten/src/ATen/test/verify_api_visibility.cpp

@@ -8,4 +8,8 @@
 #error "AT_CUDNN_ENABLED should not be visible in public headers"
 #endif
 
+#ifdef AT_MKL_ENABLED
+#error "AT_MKL_ENABLED should not be visible in public headers"
+#endif
+
 auto main() -> int {}

aten/src/TH/cmake/FindLAPACK.cmake

@@ -180,7 +180,7 @@ IF (NOT LAPACK_FOUND AND LAPACK_FIND_REQUIRED)
 ENDIF (NOT LAPACK_FOUND AND LAPACK_FIND_REQUIRED)
 IF(NOT LAPACK_FIND_QUIETLY)
   IF(LAPACK_FOUND)
-    MESSAGE(STATUS "Found a library with LAPACK API. (${LAPACK_INFO})")
+    MESSAGE(STATUS "Found a library with LAPACK API (${LAPACK_INFO}).")
   ELSE(LAPACK_FOUND)
     MESSAGE(STATUS "Cannot find a library with LAPACK API. Not using LAPACK.")
   ENDIF(LAPACK_FOUND)

aten/src/TH/cmake/FindMKL.cmake

@@ -175,7 +175,7 @@ FOREACH(mklrtl ${mklrtls} "")
         IF (NOT MKL_LIBRARIES AND NOT INTEL_MKL_SEQUENTIAL)
           CHECK_ALL_LIBRARIES(MKL_LIBRARIES cblas_sgemm
             "mkl_${mkliface}${mkl64};${mklthread};mkl_core;${mklrtl};pthread;${mkl_m};${mkl_dl}" "")
-        ENDIF (NOT MKL_LIBRARIES AND NOT INTEL_MKL_SEQUENTIAL)          
+        ENDIF (NOT MKL_LIBRARIES AND NOT INTEL_MKL_SEQUENTIAL)
       ENDFOREACH(mklthread)
     ENDFOREACH(mkl64)
   ENDFOREACH(mkliface)
@@ -200,7 +200,7 @@ FOREACH(mklrtl ${mklrtls} "")
         IF (NOT MKL_LIBRARIES)
           CHECK_ALL_LIBRARIES(MKL_LIBRARIES cblas_sgemm
             "mkl_${mkliface}${mkl64};${mklthread};mkl_core;${mklrtl};pthread;${mkl_m};${mkl_dl}" "")
-        ENDIF (NOT MKL_LIBRARIES)          
+        ENDIF (NOT MKL_LIBRARIES)
       ENDFOREACH(mklthread)
     ENDFOREACH(mkl64)
   ENDFOREACH(mkliface)
@@ -211,7 +211,7 @@ IF (NOT MKL_LIBRARIES)
   SET(MKL_VERSION 900)
   CHECK_ALL_LIBRARIES(MKL_LIBRARIES cblas_sgemm
     "mkl;guide;pthread;m" "")
-ENDIF (NOT MKL_LIBRARIES)          
+ENDIF (NOT MKL_LIBRARIES)
 
 # Include files
 IF (MKL_LIBRARIES)
@@ -228,7 +228,7 @@ IF (MKL_LIBRARIES)
         MARK_AS_ADVANCED(MKL_LAPACK_LIBRARIES)
       ENDIF (NOT MKL_LAPACK_LIBRARIES)
       IF (NOT MKL_SCALAPACK_LIBRARIES)
-        FIND_LIBRARY(MKL_SCALAPACK_LIBRARIES NAMES "mkl_scalapack${mkl64}${mkls}") 
+        FIND_LIBRARY(MKL_SCALAPACK_LIBRARIES NAMES "mkl_scalapack${mkl64}${mkls}")
         MARK_AS_ADVANCED(MKL_SCALAPACK_LIBRARIES)
       ENDIF (NOT MKL_SCALAPACK_LIBRARIES)
       IF (NOT MKL_SOLVER_LIBRARIES)
@@ -243,7 +243,7 @@ IF (MKL_LIBRARIES)
   ENDFOREACH(mkl64)
 ENDIF (MKL_LIBRARIES)
 
-# LibIRC: intel compiler always links this; 
+# LibIRC: intel compiler always links this;
 # gcc does not; but mkl kernels sometimes need it.
 IF (MKL_LIBRARIES)
   IF (CMAKE_COMPILER_IS_GNUCC)
@@ -269,7 +269,7 @@ ENDIF (MKL_LIBRARIES)
 
 # Standard termination
 IF(NOT MKL_FOUND AND MKL_FIND_REQUIRED)
-  MESSAGE(FATAL_ERROR "MKL library not found. Please specify library  location")
+  MESSAGE(FATAL_ERROR "MKL library not found. Please specify library location")
 ENDIF(NOT MKL_FOUND AND MKL_FIND_REQUIRED)
 IF(NOT MKL_FIND_QUIETLY)
   IF(MKL_FOUND)

test/common.py

@@ -19,6 +19,7 @@ import torch.cuda
 from torch.autograd import Variable
 from torch._six import string_classes
 import torch.backends.cudnn
+import torch.backends.mkl
 
 
 torch.set_default_tensor_type('torch.DoubleTensor')
@@ -54,6 +55,8 @@ try:
 except ImportError:
     TEST_SCIPY = False
 
+TEST_MKL = torch.backends.mkl.is_available()
+
 
 def skipIfNoLapack(fn):
     @wraps(fn)

torch/backends/mkl/__init__.py

@@ -0,0 +1,6 @@
+import torch
+
+
+def is_available():
+    r"""Returns whether PyTorch is built with MKL support."""
+    return torch._C.has_mkl

torch/csrc/Module.cpp

@@ -505,6 +505,8 @@ static PyObject* initModule() {
   // setting up TH Errors so that they throw C++ exceptions
   at::init();
 
+  ASSERT_TRUE(PyModule_AddObject(module, "has_mkl", at::hasMKL() ? Py_True : Py_False) == 0);
+
   auto& defaultGenerator = at::globalContext().defaultGenerator(at::kCPU);
   THPDefaultGenerator = (THPGenerator*)THPGenerator_NewWithGenerator(
     defaultGenerator);