Merge pull request #165 from BVLC/boost-eigen

MKL/non-MKL Reconciliation

Caffe no longer requires MKL. By default it builds without it, relying on atlas and cblas instead. Set the `USE_MKL` var in your Makefile.config accordingly.

Makefile

@@ -86,27 +86,37 @@ CUDA_LIB_DIR := $(CUDA_DIR)/lib64 $(CUDA_DIR)/lib
 MKL_INCLUDE_DIR := $(MKL_DIR)/include
 MKL_LIB_DIR := $(MKL_DIR)/lib $(MKL_DIR)/lib/intel64
 
-INCLUDE_DIRS += ./src ./include $(CUDA_INCLUDE_DIR) $(MKL_INCLUDE_DIR)
-LIBRARY_DIRS += $(CUDA_LIB_DIR) $(MKL_LIB_DIR)
+INCLUDE_DIRS += ./src ./include $(CUDA_INCLUDE_DIR)
+LIBRARY_DIRS += $(CUDA_LIB_DIR)
 LIBRARIES := cudart cublas curand \
-	mkl_rt \
 	pthread \
-	glog protobuf leveldb \
-	snappy \
+	glog protobuf leveldb snappy \
 	boost_system \
 	hdf5_hl hdf5 \
 	opencv_core opencv_highgui opencv_imgproc
 PYTHON_LIBRARIES := boost_python python2.7
 WARNINGS := -Wall
 
-COMMON_FLAGS := -DNDEBUG -O2 $(foreach includedir,$(INCLUDE_DIRS),-I$(includedir))
+COMMON_FLAGS := -DNDEBUG -O2
+
+# MKL switch (default = non-MKL)
+USE_MKL ?= 0
+ifeq ($(USE_MKL), 1)
+  LIBRARIES += mkl_rt
+  COMMON_FLAGS += -DUSE_MKL
+  INCLUDE_DIRS += $(MKL_INCLUDE_DIR)
+  LIBRARY_DIRS += $(MKL_LIB_DIR)
+else
+  LIBRARIES += cblas atlas
+endif
+
+COMMON_FLAGS += $(foreach includedir,$(INCLUDE_DIRS),-I$(includedir))
 CXXFLAGS += -pthread -fPIC $(COMMON_FLAGS)
 NVCCFLAGS := -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS)
 LDFLAGS += $(foreach librarydir,$(LIBRARY_DIRS),-L$(librarydir)) \
 		$(foreach library,$(LIBRARIES),-l$(library))
 PYTHON_LDFLAGS := $(LDFLAGS) $(foreach library,$(PYTHON_LIBRARIES),-l$(library))
 
-
 ##############################
 # Define build targets
 ##############################

Makefile.config.example

@@ -10,6 +10,8 @@ CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
     -gencode arch=compute_30,code=sm_30 \
     -gencode arch=compute_35,code=sm_35
 
+# MKL switch: set to 1 for MKL
+USE_MKL := 0
 # MKL directory contains include/ and lib/ directions that we need.
 MKL_DIR := /opt/intel/mkl
 

include/caffe/blob.hpp

@@ -27,6 +27,14 @@ class Blob {
   inline int count() const {return count_; }
   inline int offset(const int n, const int c = 0, const int h = 0,
       const int w = 0) const {
+    CHECK_GE(n, 0);
+    CHECK_LE(n, num_);
+    CHECK_GE(channels_, 0);
+    CHECK_LE(c, channels_);
+    CHECK_GE(height_, 0);
+    CHECK_LE(h, height_);
+    CHECK_GE(width_, 0);
+    CHECK_LE(w, width_);
     return ((n * channels_ + c) * height_ + h) * width_ + w;
   }
   // Copy from source. If copy_diff is false, we copy the data; if copy_diff

include/caffe/common.hpp

@@ -1,4 +1,4 @@
-// Copyright 2013 Yangqing Jia
+// Copyright 2014 BVLC and contributors.
 
 #ifndef CAFFE_COMMON_HPP_
 #define CAFFE_COMMON_HPP_
@@ -7,28 +7,8 @@
 #include <cublas_v2.h>
 #include <cuda.h>
 #include <curand.h>
-// cuda driver types
-#include <driver_types.h>
+#include <driver_types.h>  // cuda driver types
 #include <glog/logging.h>
-#include <mkl_vsl.h>
-
-// various checks for different function calls.
-#define CUDA_CHECK(condition) CHECK_EQ((condition), cudaSuccess)
-#define CUBLAS_CHECK(condition) CHECK_EQ((condition), CUBLAS_STATUS_SUCCESS)
-#define CURAND_CHECK(condition) CHECK_EQ((condition), CURAND_STATUS_SUCCESS)
-#define VSL_CHECK(condition) CHECK_EQ((condition), VSL_STATUS_OK)
-
-#define CUDA_KERNEL_LOOP(i, n) \
-  for (int i = blockIdx.x * blockDim.x + threadIdx.x; \
-       i < (n); \
-       i += blockDim.x * gridDim.x)
-
-// After a kernel is executed, this will check the error and if there is one,
-// exit loudly.
-#define CUDA_POST_KERNEL_CHECK \
-  if (cudaSuccess != cudaPeekAtLastError()) \
-    LOG(FATAL) << "Cuda kernel failed. Error: " \
-        << cudaGetErrorString(cudaPeekAtLastError())
 
 // Disable the copy and assignment operator for a class.
 #define DISABLE_COPY_AND_ASSIGN(classname) \
@@ -45,6 +25,23 @@ private:\
 // is executed we will see a fatal log.
 #define NOT_IMPLEMENTED LOG(FATAL) << "Not Implemented Yet"
 
+// CUDA: various checks for different function calls.
+#define CUDA_CHECK(condition) CHECK_EQ((condition), cudaSuccess)
+#define CUBLAS_CHECK(condition) CHECK_EQ((condition), CUBLAS_STATUS_SUCCESS)
+#define CURAND_CHECK(condition) CHECK_EQ((condition), CURAND_STATUS_SUCCESS)
+
+// CUDA: grid stride looping
+#define CUDA_KERNEL_LOOP(i, n) \
+  for (int i = blockIdx.x * blockDim.x + threadIdx.x; \
+       i < (n); \
+       i += blockDim.x * gridDim.x)
+
+// CUDA: check for error after kernel execution and exit loudly if there is one.
+#define CUDA_POST_KERNEL_CHECK \
+  if (cudaSuccess != cudaPeekAtLastError()) \
+    LOG(FATAL) << "Cuda kernel failed. Error: " \
+        << cudaGetErrorString(cudaPeekAtLastError())
+
 
 namespace caffe {
 
@@ -53,20 +50,6 @@ namespace caffe {
 using boost::shared_ptr;
 
 
-// We will use 1024 threads per block, which requires cuda sm_2x or above.
-#if __CUDA_ARCH__ >= 200
-    const int CAFFE_CUDA_NUM_THREADS = 1024;
-#else
-    const int CAFFE_CUDA_NUM_THREADS = 512;
-#endif
-
-
-
-inline int CAFFE_GET_BLOCKS(const int N) {
-  return (N + CAFFE_CUDA_NUM_THREADS - 1) / CAFFE_CUDA_NUM_THREADS;
-}
-
-
 // A singleton class to hold common caffe stuff, such as the handler that
 // caffe is going to use for cublas, curand, etc.
 class Caffe {
@@ -81,15 +64,32 @@ class Caffe {
   enum Brew { CPU, GPU };
   enum Phase { TRAIN, TEST };
 
-  // The getters for the variables.
-  // Returns the cublas handle.
+
+  // This random number generator facade hides boost and CUDA rng
+  // implementation from one another (for cross-platform compatibility).
+  class RNG {
+   public:
+    RNG();
+    explicit RNG(unsigned int seed);
+    ~RNG();
+    RNG(const RNG&);
+    RNG& operator=(const RNG&);
+    const void* generator() const;
+    void* generator();
+   private:
+    class Generator;
+    Generator* generator_;
+  };
+
+  // Getters for boost rng, curand, and cublas handles
+  inline static RNG &rng_stream() {
+    return Get().random_generator_;
+  }
   inline static cublasHandle_t cublas_handle() { return Get().cublas_handle_; }
-  // Returns the curand generator.
   inline static curandGenerator_t curand_generator() {
     return Get().curand_generator_;
   }
-  // Returns the MKL random stream.
-  inline static VSLStreamStatePtr vsl_stream() { return Get().vsl_stream_; }
+
   // Returns the mode: running on CPU or GPU.
   inline static Brew mode() { return Get().mode_; }
   // Returns the phase: TRAIN or TEST.
@@ -102,7 +102,7 @@ class Caffe {
   inline static void set_mode(Brew mode) { Get().mode_ = mode; }
   // Sets the phase.
   inline static void set_phase(Phase phase) { Get().phase_ = phase; }
-  // Sets the random seed of both MKL and curand
+  // Sets the random seed of both boost and curand
   static void set_random_seed(const unsigned int seed);
   // Sets the device. Since we have cublas and curand stuff, set device also
   // requires us to reset those values.
@@ -113,7 +113,8 @@ class Caffe {
  protected:
   cublasHandle_t cublas_handle_;
   curandGenerator_t curand_generator_;
-  VSLStreamStatePtr vsl_stream_;
+  RNG random_generator_;
+
   Brew mode_;
   Phase phase_;
   static shared_ptr<Caffe> singleton_;
@@ -126,6 +127,21 @@ class Caffe {
 };
 
 
+// CUDA: thread number configuration.
+// Use 1024 threads per block, which requires cuda sm_2x or above,
+// or fall back to attempt compatibility (best of luck to you).
+#if __CUDA_ARCH__ >= 200
+    const int CAFFE_CUDA_NUM_THREADS = 1024;
+#else
+    const int CAFFE_CUDA_NUM_THREADS = 512;
+#endif
+
+// CUDA: number of blocks for threads.
+inline int CAFFE_GET_BLOCKS(const int N) {
+  return (N + CAFFE_CUDA_NUM_THREADS - 1) / CAFFE_CUDA_NUM_THREADS;
+}
+
+
 }  // namespace caffe
 
 #endif  // CAFFE_COMMON_HPP_

include/caffe/filler.hpp

@@ -7,7 +7,6 @@
 #ifndef CAFFE_FILLER_HPP
 #define CAFFE_FILLER_HPP
 
-#include <mkl.h>
 #include <string>
 
 #include "caffe/common.hpp"

include/caffe/util/math_functions.hpp

@@ -4,9 +4,11 @@
 #ifndef CAFFE_UTIL_MATH_FUNCTIONS_H_
 #define CAFFE_UTIL_MATH_FUNCTIONS_H_
 
-#include <mkl.h>
+
 #include <cublas_v2.h>
 
+#include "caffe/util/mkl_alternate.hpp"
+
 namespace caffe {
 
 // Decaf gemm provides a simpler interface to the gemm functions, with the
@@ -45,7 +47,7 @@ void caffe_gpu_axpy(const int N, const Dtype alpha, const Dtype* X,
     Dtype* Y);
 
 template <typename Dtype>
-void caffe_axpby(const int N, const Dtype alpha, const Dtype* X,
+void caffe_cpu_axpby(const int N, const Dtype alpha, const Dtype* X,
     const Dtype beta, Dtype* Y);
 
 template <typename Dtype>
@@ -85,13 +87,19 @@ void caffe_div(const int N, const Dtype* a, const Dtype* b, Dtype* y);
 template <typename Dtype>
 void caffe_powx(const int n, const Dtype* a, const Dtype b, Dtype* y);
 
+template <typename Dtype>
+Dtype caffe_nextafter(const Dtype b);
+
 template <typename Dtype>
 void caffe_vRngUniform(const int n, Dtype* r, const Dtype a, const Dtype b);
 
 template <typename Dtype>
 void caffe_vRngGaussian(const int n, Dtype* r, const Dtype a,
     const Dtype sigma);
 
+template <typename Dtype>
+void caffe_vRngBernoulli(const int n, Dtype* r, const double p);
+
 template <typename Dtype>
 void caffe_exp(const int n, const Dtype* a, Dtype* y);
 

include/caffe/util/mkl_alternate.hpp

@@ -0,0 +1,97 @@
+// Copyright 2013 Rowland Depp
+
+#ifndef CAFFE_UTIL_MKL_ALTERNATE_H_
+#define CAFFE_UTIL_MKL_ALTERNATE_H_
+
+#ifdef USE_MKL
+
+#include <mkl.h>
+
+#else  // If use MKL, simply include the MKL header
+
+extern "C" {
+#include <cblas.h>
+}
+#include <math.h>
+
+// Functions that caffe uses but are not present if MKL is not linked.
+
+// A simple way to define the vsl unary functions. The operation should
+// be in the form e.g. y[i] = sqrt(a[i])
+#define DEFINE_VSL_UNARY_FUNC(name, operation) \
+  template<typename Dtype> \
+  void v##name(const int n, const Dtype* a, Dtype* y) { \
+    CHECK_GT(n, 0); CHECK(a); CHECK(y); \
+    for (int i = 0; i < n; ++i) { operation; } \
+  } \
+  inline void vs##name( \
+    const int n, const float* a, float* y) { \
+    v##name<float>(n, a, y); \
+  } \
+  inline void vd##name( \
+      const int n, const double* a, double* y) { \
+    v##name<double>(n, a, y); \
+  }
+
+DEFINE_VSL_UNARY_FUNC(Sqr, y[i] = a[i] * a[i]);
+DEFINE_VSL_UNARY_FUNC(Exp, y[i] = exp(a[i]));
+
+// A simple way to define the vsl unary functions with singular parameter b.
+// The operation should be in the form e.g. y[i] = pow(a[i], b)
+#define DEFINE_VSL_UNARY_FUNC_WITH_PARAM(name, operation) \
+  template<typename Dtype> \
+  void v##name(const int n, const Dtype* a, const Dtype b, Dtype* y) { \
+    CHECK_GT(n, 0); CHECK(a); CHECK(y); \
+    for (int i = 0; i < n; ++i) { operation; } \
+  } \
+  inline void vs##name( \
+    const int n, const float* a, const float b, float* y) { \
+    v##name<float>(n, a, b, y); \
+  } \
+  inline void vd##name( \
+      const int n, const double* a, const float b, double* y) { \
+    v##name<double>(n, a, b, y); \
+  }
+
+DEFINE_VSL_UNARY_FUNC_WITH_PARAM(Powx, y[i] = pow(a[i], b));
+
+// A simple way to define the vsl binary functions. The operation should
+// be in the form e.g. y[i] = a[i] + b[i]
+#define DEFINE_VSL_BINARY_FUNC(name, operation) \
+  template<typename Dtype> \
+  void v##name(const int n, const Dtype* a, const Dtype* b, Dtype* y) { \
+    CHECK_GT(n, 0); CHECK(a); CHECK(b); CHECK(y); \
+    for (int i = 0; i < n; ++i) { operation; } \
+  } \
+  inline void vs##name( \
+    const int n, const float* a, const float* b, float* y) { \
+    v##name<float>(n, a, b, y); \
+  } \
+  inline void vd##name( \
+      const int n, const double* a, const double* b, double* y) { \
+    v##name<double>(n, a, b, y); \
+  }
+
+DEFINE_VSL_BINARY_FUNC(Add, y[i] = a[i] + b[i]);
+DEFINE_VSL_BINARY_FUNC(Sub, y[i] = a[i] - b[i]);
+DEFINE_VSL_BINARY_FUNC(Mul, y[i] = a[i] * b[i]);
+DEFINE_VSL_BINARY_FUNC(Div, y[i] = a[i] / b[i]);
+
+// In addition, MKL comes with an additional function axpby that is not present
+// in standard blas. We will simply use a two-step (inefficient, of course) way
+// to mimic that.
+inline void cblas_saxpby(const int N, const float alpha, const float* X,
+                         const int incX, const float beta, float* Y,
+                         const int incY) {
+  cblas_sscal(N, beta, Y, incY);
+  cblas_saxpy(N, alpha, X, incX, Y, incY);
+}
+inline void cblas_daxpby(const int N, const double alpha, const double* X,
+                         const int incX, const double beta, double* Y,
+                         const int incY) {
+  cblas_dscal(N, beta, Y, incY);
+  cblas_daxpy(N, alpha, X, incX, Y, incY);
+}
+
+#endif  // USE_MKL
+#endif  // CAFFE_UTIL_MKL_ALTERNATE_H_

include/caffe/util/rng.hpp

@@ -0,0 +1,19 @@
+// Copyright 2014 BVLC and contributors.
+
+#ifndef CAFFE_RNG_CPP_HPP_
+#define CAFFE_RNG_CPP_HPP_
+
+#include <boost/random/mersenne_twister.hpp>
+#include "caffe/common.hpp"
+
+namespace caffe {
+
+  typedef boost::mt19937 rng_t;
+  inline rng_t& caffe_rng() {
+    Caffe::RNG &generator = Caffe::rng_stream();
+    return *(caffe::rng_t*) generator.generator();
+  }
+
+}  // namespace caffe
+
+#endif  // CAFFE_RNG_HPP_