mirror of
https://gitlab.com/libeigen/eigen.git
synced 2025-06-04 18:54:00 +08:00
Adds a fast memcpy function to Eigen. This takes advantage of the following:
1. For small fixed sizes, the compiler generates inline code for memcpy, which is much faster. 2. My colleague eriche at googl dot com discovered that for large sizes, memmove is significantly faster than memcpy (at least on Linux with GCC or Clang). See benchmark numbers measured on a Haswell (HP Z440) workstation here: https://docs.google.com/a/google.com/spreadsheets/d/1jLs5bKzXwhpTySw65MhG1pZpsIwkszZqQTjwrd_n0ic/pubhtml This is of course surprising since memcpy is a less constrained version of memmove. This stackoverflow thread contains some speculation as to the causes: http://stackoverflow.com/questions/22793669/poor-memcpy-performance-on-linux Below are numbers for copying and slicing tensors using the multithreaded TensorDevice. The numbers show significant improvements for memcpy of very small blocks and for memcpy of large blocks single threaded (we were already able to saturate memory bandwidth for >1 threads before on large blocks). The "slicingSmallPieces" benchmark also shows small consistent improvements, since memcpy cost is a fair portion of that particular computation. The benchmarks operate on NxN matrices, and the names are of the form BM_$OP_${NUMTHREADS}T/${N}. Measured improvements in wall clock time: Run on rmlarsen3.mtv (12 X 3501 MHz CPUs); 2017-01-20T11:26:31.493023454-08:00 CPU: Intel Haswell with HyperThreading (6 cores) dL1:32KB dL2:256KB dL3:15MB Benchmark Base (ns) New (ns) Improvement ------------------------------------------------------------------ BM_memcpy_1T/2 3.48 2.39 +31.3% BM_memcpy_1T/8 12.3 6.51 +47.0% BM_memcpy_1T/64 371 383 -3.2% BM_memcpy_1T/512 66922 66720 +0.3% BM_memcpy_1T/4k 9892867 6849682 +30.8% BM_memcpy_1T/5k 14951099 10332856 +30.9% BM_memcpy_2T/2 3.50 2.46 +29.7% BM_memcpy_2T/8 12.3 7.66 +37.7% BM_memcpy_2T/64 371 376 -1.3% BM_memcpy_2T/512 66652 66788 -0.2% BM_memcpy_2T/4k 6145012 6117776 +0.4% BM_memcpy_2T/5k 9181478 9010942 +1.9% BM_memcpy_4T/2 3.47 2.47 +31.0% BM_memcpy_4T/8 12.3 6.67 +45.8 BM_memcpy_4T/64 374 376 -0.5% BM_memcpy_4T/512 67833 68019 -0.3% BM_memcpy_4T/4k 5057425 5188253 -2.6% BM_memcpy_4T/5k 7555638 7779468 -3.0% BM_memcpy_6T/2 3.51 2.50 +28.8% BM_memcpy_6T/8 12.3 7.61 +38.1% BM_memcpy_6T/64 373 378 -1.3% BM_memcpy_6T/512 66871 66774 +0.1% BM_memcpy_6T/4k 5112975 5233502 -2.4% BM_memcpy_6T/5k 7614180 7772246 -2.1% BM_memcpy_8T/2 3.47 2.41 +30.5% BM_memcpy_8T/8 12.4 10.5 +15.3% BM_memcpy_8T/64 372 388 -4.3% BM_memcpy_8T/512 67373 66588 +1.2% BM_memcpy_8T/4k 5148462 5254897 -2.1% BM_memcpy_8T/5k 7660989 7799058 -1.8% BM_memcpy_12T/2 3.50 2.40 +31.4% BM_memcpy_12T/8 12.4 7.55 +39.1 BM_memcpy_12T/64 374 378 -1.1% BM_memcpy_12T/512 67132 66683 +0.7% BM_memcpy_12T/4k 5185125 5292920 -2.1% BM_memcpy_12T/5k 7717284 7942684 -2.9% BM_slicingSmallPieces_1T/2 47.3 47.5 +0.4% BM_slicingSmallPieces_1T/8 53.6 52.3 +2.4% BM_slicingSmallPieces_1T/64 491 476 +3.1% BM_slicingSmallPieces_1T/512 21734 18814 +13.4% BM_slicingSmallPieces_1T/4k 394660 396760 -0.5% BM_slicingSmallPieces_1T/5k 218722 209244 +4.3% BM_slicingSmallPieces_2T/2 80.7 79.9 +1.0% BM_slicingSmallPieces_2T/8 54.2 53.1 +2.0 BM_slicingSmallPieces_2T/64 497 477 +4.0% BM_slicingSmallPieces_2T/512 21732 18822 +13.4% BM_slicingSmallPieces_2T/4k 392885 390490 +0.6% BM_slicingSmallPieces_2T/5k 221988 208678 +6.0% BM_slicingSmallPieces_4T/2 80.8 80.1 +0.9% BM_slicingSmallPieces_4T/8 54.1 53.2 +1.7% BM_slicingSmallPieces_4T/64 493 476 +3.4% BM_slicingSmallPieces_4T/512 21702 18758 +13.6% BM_slicingSmallPieces_4T/4k 393962 404023 -2.6% BM_slicingSmallPieces_4T/5k 249667 211732 +15.2% BM_slicingSmallPieces_6T/2 80.5 80.1 +0.5% BM_slicingSmallPieces_6T/8 54.4 53.4 +1.8% BM_slicingSmallPieces_6T/64 488 478 +2.0% BM_slicingSmallPieces_6T/512 21719 18841 +13.3% BM_slicingSmallPieces_6T/4k 394950 397583 -0.7% BM_slicingSmallPieces_6T/5k 223080 210148 +5.8% BM_slicingSmallPieces_8T/2 81.2 80.4 +1.0% BM_slicingSmallPieces_8T/8 58.1 53.5 +7.9% BM_slicingSmallPieces_8T/64 489 480 +1.8% BM_slicingSmallPieces_8T/512 21586 18798 +12.9% BM_slicingSmallPieces_8T/4k 394592 400165 -1.4% BM_slicingSmallPieces_8T/5k 219688 208301 +5.2% BM_slicingSmallPieces_12T/2 80.2 79.8 +0.7% BM_slicingSmallPieces_12T/8 54.4 53.4 +1.8 BM_slicingSmallPieces_12T/64 488 476 +2.5% BM_slicingSmallPieces_12T/512 21931 18831 +14.1% BM_slicingSmallPieces_12T/4k 393962 396541 -0.7% BM_slicingSmallPieces_12T/5k 218803 207965 +5.0%
This commit is contained in:
Rasmus Munk Larsen
parent
156e6234f1
commit
e6b1020221
@ -63,7 +63,7 @@ namespace Eigen {
|
||||
|
||||
namespace internal {
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline void throw_std_bad_alloc()
|
||||
{
|
||||
#ifdef EIGEN_EXCEPTIONS
|
||||
@ -74,6 +74,41 @@ inline void throw_std_bad_alloc()
|
||||
#endif
|
||||
}
|
||||
|
||||
EIGEN_DEVICE_FUNC
|
||||
inline void fast_memcpy(void* dst, const void* src, size_t size) {
|
||||
#if defined(__CUDA__) || defined(__ANDROID__)
|
||||
::memcpy(dst, src, size);
|
||||
#else
|
||||
switch(size) {
|
||||
// Most compilers will generate inline code for fixed sizes,
|
||||
// which is significantly faster for small copies.
|
||||
case 1: memcpy(dst, src, 1); break;
|
||||
case 2: memcpy(dst, src, 2); break;
|
||||
case 3: memcpy(dst, src, 3); break;
|
||||
case 4: memcpy(dst, src, 4); break;
|
||||
case 5: memcpy(dst, src, 5); break;
|
||||
case 6: memcpy(dst, src, 6); break;
|
||||
case 7: memcpy(dst, src, 7); break;
|
||||
case 8: memcpy(dst, src, 8); break;
|
||||
case 9: memcpy(dst, src, 9); break;
|
||||
case 10: memcpy(dst, src, 10); break;
|
||||
case 11: memcpy(dst, src, 11); break;
|
||||
case 12: memcpy(dst, src, 12); break;
|
||||
case 13: memcpy(dst, src, 13); break;
|
||||
case 14: memcpy(dst, src, 14); break;
|
||||
case 15: memcpy(dst, src, 15); break;
|
||||
case 16: memcpy(dst, src, 16); break;
|
||||
#ifdef EIGEN_OS_LINUX
|
||||
// On Linux, memmove appears to be faster than memcpy for
|
||||
// large sizes, strangely enough.
|
||||
default: memmove(dst, src, size); break;
|
||||
#else
|
||||
default: memcpy(dst, src, size); break;
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
}
|
||||
|
||||
/*****************************************************************************
|
||||
*** Implementation of handmade aligned functions ***
|
||||
*****************************************************************************/
|
||||
@ -114,7 +149,7 @@ inline void* handmade_aligned_realloc(void* ptr, std::size_t size, std::size_t =
|
||||
void *previous_aligned = static_cast<char *>(original)+previous_offset;
|
||||
if(aligned!=previous_aligned)
|
||||
std::memmove(aligned, previous_aligned, size);
|
||||
|
||||
|
||||
*(reinterpret_cast<void**>(aligned) - 1) = original;
|
||||
return aligned;
|
||||
}
|
||||
@ -142,7 +177,7 @@ EIGEN_DEVICE_FUNC inline void check_that_malloc_is_allowed()
|
||||
{
|
||||
eigen_assert(is_malloc_allowed() && "heap allocation is forbidden (EIGEN_RUNTIME_NO_MALLOC is defined and g_is_malloc_allowed is false)");
|
||||
}
|
||||
#else
|
||||
#else
|
||||
EIGEN_DEVICE_FUNC inline void check_that_malloc_is_allowed()
|
||||
{}
|
||||
#endif
|
||||
@ -471,8 +506,8 @@ EIGEN_DEVICE_FUNC inline Index first_default_aligned(const Scalar* array, Index
|
||||
}
|
||||
|
||||
/** \internal Returns the smallest integer multiple of \a base and greater or equal to \a size
|
||||
*/
|
||||
template<typename Index>
|
||||
*/
|
||||
template<typename Index>
|
||||
inline Index first_multiple(Index size, Index base)
|
||||
{
|
||||
return ((size+base-1)/base)*base;
|
||||
@ -502,7 +537,7 @@ template<typename T> struct smart_copy_helper<T,false> {
|
||||
{ std::copy(start, end, target); }
|
||||
};
|
||||
|
||||
// intelligent memmove. falls back to std::memmove for POD types, uses std::copy otherwise.
|
||||
// intelligent memmove. falls back to std::memmove for POD types, uses std::copy otherwise.
|
||||
template<typename T, bool UseMemmove> struct smart_memmove_helper;
|
||||
|
||||
template<typename T> void smart_memmove(const T* start, const T* end, T* target)
|
||||
@ -522,15 +557,15 @@ template<typename T> struct smart_memmove_helper<T,true> {
|
||||
|
||||
template<typename T> struct smart_memmove_helper<T,false> {
|
||||
static inline void run(const T* start, const T* end, T* target)
|
||||
{
|
||||
{
|
||||
if (UIntPtr(target) < UIntPtr(start))
|
||||
{
|
||||
std::copy(start, end, target);
|
||||
}
|
||||
else
|
||||
else
|
||||
{
|
||||
std::ptrdiff_t count = (std::ptrdiff_t(end)-std::ptrdiff_t(start)) / sizeof(T);
|
||||
std::copy_backward(start, end, target + count);
|
||||
std::copy_backward(start, end, target + count);
|
||||
}
|
||||
}
|
||||
};
|
||||
@ -603,7 +638,7 @@ template<typename T> void swap(scoped_array<T> &a,scoped_array<T> &b)
|
||||
{
|
||||
std::swap(a.ptr(),b.ptr());
|
||||
}
|
||||
|
||||
|
||||
} // end namespace internal
|
||||
|
||||
/** \internal
|
||||
@ -622,7 +657,7 @@ template<typename T> void swap(scoped_array<T> &a,scoped_array<T> &b)
|
||||
* The underlying stack allocation function can controlled with the EIGEN_ALLOCA preprocessor token.
|
||||
*/
|
||||
#ifdef EIGEN_ALLOCA
|
||||
|
||||
|
||||
#if EIGEN_DEFAULT_ALIGN_BYTES>0
|
||||
// We always manually re-align the result of EIGEN_ALLOCA.
|
||||
// If alloca is already aligned, the compiler should be smart enough to optimize away the re-alignment.
|
||||
@ -645,7 +680,7 @@ template<typename T> void swap(scoped_array<T> &a,scoped_array<T> &b)
|
||||
Eigen::internal::check_size_for_overflow<TYPE>(SIZE); \
|
||||
TYPE* NAME = (BUFFER)!=0 ? BUFFER : reinterpret_cast<TYPE*>(Eigen::internal::aligned_malloc(sizeof(TYPE)*SIZE)); \
|
||||
Eigen::internal::aligned_stack_memory_handler<TYPE> EIGEN_CAT(NAME,_stack_memory_destructor)((BUFFER)==0 ? NAME : 0,SIZE,true)
|
||||
|
||||
|
||||
#endif
|
||||
|
||||
|
||||
@ -701,7 +736,7 @@ template<typename T> void swap(scoped_array<T> &a,scoped_array<T> &b)
|
||||
* Example:
|
||||
* \code
|
||||
* // Matrix4f requires 16 bytes alignment:
|
||||
* std::map< int, Matrix4f, std::less<int>,
|
||||
* std::map< int, Matrix4f, std::less<int>,
|
||||
* aligned_allocator<std::pair<const int, Matrix4f> > > my_map_mat4;
|
||||
* // Vector3f does not require 16 bytes alignment, no need to use Eigen's allocator:
|
||||
* std::map< int, Vector3f > my_map_vec3;
|
||||
|
||||
@ -56,7 +56,7 @@ void pack_simple(Scalar * dst, const Scalar * src, Index cols, Index rows, Index
|
||||
} else {
|
||||
// Naive memcpy calls
|
||||
for (Index col = 0; col < cols; ++col) {
|
||||
memcpy(dst + col*lddst, src + col*ldsrc, rows*sizeof(Scalar));
|
||||
internal::fast_memcpy(dst + col*lddst, src + col*ldsrc, rows*sizeof(Scalar));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -22,7 +22,7 @@ struct DefaultDevice {
|
||||
internal::aligned_free(buffer);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpy(void* dst, const void* src, size_t n) const {
|
||||
::memcpy(dst, src, n);
|
||||
internal::fast_memcpy(dst, src, n);
|
||||
}
|
||||
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void memcpyHostToDevice(void* dst, const void* src, size_t n) const {
|
||||
memcpy(dst, src, n);
|
||||
|
||||
@ -106,7 +106,7 @@ struct ThreadPoolDevice {
|
||||
}
|
||||
|
||||
EIGEN_STRONG_INLINE void memcpy(void* dst, const void* src, size_t n) const {
|
||||
::memcpy(dst, src, n);
|
||||
internal::fast_memcpy(dst, src, n);
|
||||
}
|
||||
EIGEN_STRONG_INLINE void memcpyHostToDevice(void* dst, const void* src, size_t n) const {
|
||||
memcpy(dst, src, n);
|
||||
|
||||
@ -253,7 +253,7 @@ struct TensorEvaluator<const TensorFFTOp<FFT, ArgType, FFTResultType, FFTDir>, D
|
||||
// get data into line_buf
|
||||
const Index stride = m_strides[dim];
|
||||
if (stride == 1) {
|
||||
memcpy(line_buf, &buf[base_offset], line_len*sizeof(ComplexScalar));
|
||||
m_device.memcpy(line_buf, &buf[base_offset], line_len*sizeof(ComplexScalar));
|
||||
} else {
|
||||
Index offset = base_offset;
|
||||
for (int j = 0; j < line_len; ++j, offset += stride) {
|
||||
@ -271,7 +271,7 @@ struct TensorEvaluator<const TensorFFTOp<FFT, ArgType, FFTResultType, FFTDir>, D
|
||||
|
||||
// write back
|
||||
if (FFTDir == FFT_FORWARD && stride == 1) {
|
||||
memcpy(&buf[base_offset], line_buf, line_len*sizeof(ComplexScalar));
|
||||
m_device.memcpy(&buf[base_offset], line_buf, line_len*sizeof(ComplexScalar));
|
||||
} else {
|
||||
Index offset = base_offset;
|
||||
const ComplexScalar div_factor = ComplexScalar(1.0 / line_len, 0);
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user