ICODE-ADC/lammps
4
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

git-svn-id: svn://svn.icms.temple.edu/lammps-ro/trunk@8699 f3b2605a-c512-4ea7-a41b-209d697bcdaa

Browse Source
This commit is contained in:
sjplimp
2012-08-23 13:03:38 +00:00
parent 2512429ccf
commit c81a8f1bc9
3 changed files with 0 additions and 493 deletions
Download Patch File Download Diff File Expand all files Collapse all files

346
lib/gpu/geryon/nvc_device.h
View File

@ -1,346 +0,0 @@
/***************************************************************************
nvc_device.h
-------------------
W. Michael Brown
Utilities for dealing with cuda devices
__________________________________________________________________________
This file is part of the Geryon Unified Coprocessor Library (UCL)
__________________________________________________________________________
begin : Wed Jan 28 2009
copyright : (C) 2009 by W. Michael Brown
email : brownw@ornl.gov
***************************************************************************/
/* -----------------------------------------------------------------------
Copyright (2009) Sandia Corporation. Under the terms of Contract
DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
certain rights in this software. This software is distributed under
the Simplified BSD License.
----------------------------------------------------------------------- */
#ifndef NVC_DEVICE
#define NVC_DEVICE
#include <string>
#include <vector>
#include <iostream>
#include <cstdlib>
#include "nvc_macros.h"
#include "ucl_types.h"
namespace ucl_cudart {
// --------------------------------------------------------------------------
// - COMMAND QUEUE STUFF
// --------------------------------------------------------------------------
typedef cudaStream_t command_queue;
inline void ucl_sync(cudaStream_t &stream) {
CUDA_SAFE_CALL(cudaStreamSynchronize(stream));
}
/// Class for looking at device properties
/** \note Calls to change the device outside of the class results in incorrect
* behavior
* \note There is no error checking for indexing past the number of devices **/
class UCL_Device {
public:
/// Collect properties for every GPU on the node
/** \note You must set the active GPU with set() before using the device **/
UCL_Device();
~UCL_Device();
/// Returns 1 (For compatibility with OpenCL)
inline int num_platforms() { return 1; }
/// Return a string with name and info of the current platform
std::string platform_name() { return "NVIDIA Corporation NVIDIA CUDA"; }
/// Return the number of devices that support CUDA
inline int num_devices() { return _properties.size(); }
/// Set the CUDA device to the specified device number
/** Returns UCL_SUCCESS if successful or UCL_ERROR if the device could not
* be allocated for use **/
int set(int num);
/// Get the current device number
inline int device_num() { return _device; }
/// Returns the default stream for the current device
inline command_queue & cq() { return cq(0); }
/// Returns the stream indexed by i
inline command_queue & cq(const int i) { return _cq[i]; }
/// Set the default command queue (by default this is the null stream)
/** \param i index of the command queue (as added by push_command_queue())
If i is 0, the default command queue is set to the null stream **/
inline void set_command_queue(const int i) {
if (i==0) _cq[0]=0;
else _cq[0]=_cq[i];
}
/// Block until all commands in the default stream have completed
inline void sync() { sync(0); }
/// Block until all commands in the specified stream have completed
inline void sync(const int i) { ucl_sync(cq(i)); }
/// Get the number of command queues currently available on device
inline int num_queues()
{ if (_device==-1) return 0; else return _cq.size(); }
/// Add a stream for device computations
inline void push_command_queue() {
_cq.push_back(cudaStream_t());
CUDA_SAFE_CALL_NS(cudaStreamCreate(&_cq.back()));
}
/// Remove a stream for device computations
/** \note You cannot delete the default stream **/
inline void pop_command_queue() {
if (_cq.size()<2) return;
CUDA_DESTRUCT_CALL_NS(cudaStreamDestroy(_cq.back()));
_cq.pop_back();
}
/// Get the current CUDA device name
inline std::string name() { return name(_device); }
/// Get the CUDA device name
inline std::string name(const int i)
{ return std::string(_properties[i].name); }
/// Get a string telling the type of the current device
inline std::string device_type_name() { return device_type_name(_device); }
/// Get a string telling the type of the device
inline std::string device_type_name(const int i) { return "GPU"; }
/// Get current device type (UCL_CPU, UCL_GPU, UCL_ACCELERATOR, UCL_DEFAULT)
inline int device_type() { return device_type(_device); }
/// Get device type (UCL_CPU, UCL_GPU, UCL_ACCELERATOR, UCL_DEFAULT)
inline int device_type(const int i) { return UCL_GPU; }
/// Returns true if double precision is support for the current device
bool double_precision() { return double_precision(_device); }
/// Returns true if double precision is support for the device
bool double_precision(const int i) {return arch(i)>=1.3;}
/// Get the number of cores in the current device
inline unsigned cores() { return cores(_device); }
/// Get the number of cores
inline unsigned cores(const int i)
{ if (arch(i)<2.0) return _properties[i].multiProcessorCount*8;
else if (arch(i)<3.0) return _properties[i].multiProcessorCount*32;
else return _properties[i].multiProcessorCount*192; }
/// Get the gigabytes of global memory in the current device
inline double gigabytes() { return gigabytes(_device); }
/// Get the gigabytes of global memory
inline double gigabytes(const int i)
{ return static_cast<double>(_properties[i].totalGlobalMem)/1073741824; }
/// Get the bytes of global memory in the current device
inline size_t bytes() { return bytes(_device); }
/// Get the bytes of global memory
inline size_t bytes(const int i) { return _properties[i].totalGlobalMem; }
/// Return the GPGPU compute capability for current device
inline double arch() { return arch(_device); }
/// Return the GPGPU compute capability
inline double arch(const int i)
{ return static_cast<double>(_properties[i].minor)/10+_properties[i].major;}
/// Clock rate in GHz for current device
inline double clock_rate() { return clock_rate(_device); }
/// Clock rate in GHz
inline double clock_rate(const int i) { return _properties[i].clockRate*1e-6;}
/// Get the maximum number of threads per block
inline size_t group_size() { return group_size(_device); }
/// Get the maximum number of threads per block
inline size_t group_size(const int i)
{ return _properties[i].maxThreadsPerBlock; }
/// Return the maximum memory pitch in bytes for current device
inline size_t max_pitch() { return max_pitch(_device); }
/// Return the maximum memory pitch in bytes
inline size_t max_pitch(const int i) { return _properties[i].memPitch; }
/// Returns false if accelerator cannot be shared by multiple processes
/** If it cannot be determined, true is returned **/
inline bool sharing_supported() { return sharing_supported(_device); }
/// Returns false if accelerator cannot be shared by multiple processes
/** If it cannot be determined, true is returned **/
inline bool sharing_supported(const int i)
{ return (_properties[i].computeMode == cudaComputeModeDefault); }
/// List all devices along with all properties
void print_all(std::ostream &out);
private:
int _device, _num_devices;
std::vector<cudaDeviceProp> _properties;
std::vector<cudaStream_t> _cq;
std::vector<int> _device_ids;
};
// Grabs the properties for all devices
inline UCL_Device::UCL_Device() {
CUDA_SAFE_CALL_NS(cudaGetDeviceCount(&_num_devices));
for (int dev=0; dev<_num_devices; ++dev) {
cudaDeviceProp deviceProp;
CUDA_SAFE_CALL_NS(cudaGetDeviceProperties(&deviceProp, dev));
if (deviceProp.major == 9999 && deviceProp.minor == 9999)
break;
_properties.push_back(deviceProp);
_device_ids.push_back(dev);
}
_device=-1;
_cq.push_back(cudaStream_t());
_cq.back()=0;
}
inline UCL_Device::~UCL_Device() {
for (int i=1; i<num_queues(); i++) pop_command_queue();
}
// Set the CUDA device to the specified device number
inline int UCL_Device::set(int num) {
if (_device==num)
return UCL_SUCCESS;
for (int i=1; i<num_queues(); i++) pop_command_queue();
_cq[0]=0;
cudaThreadExit();
cudaError err=cudaSetDevice(_device_ids[num]);
if (err!=cudaSuccess) {
#ifndef UCL_NO_EXIT
std::cerr << "UCL Error: Could not access accelerator number " << num
<< " for use.\n";
UCL_GERYON_EXIT;
#endif
return UCL_ERROR;
}
_device=num;
return UCL_SUCCESS;
}
// List all devices along with all properties
inline void UCL_Device::print_all(std::ostream &out) {
#if CUDART_VERSION >= 2020
int driver_version, runtime_version;
cudaDriverGetVersion(&driver_version);
out << "CUDA Driver Version: "
<< driver_version/1000 << "." << driver_version%100
<< std::endl;
cudaRuntimeGetVersion(&runtime_version);
out << "CUDA Runtime Version: "
<< runtime_version/1000 << "." << runtime_version%100
<< std::endl;
#endif
if (num_devices() == 0)
out << "There is no device supporting CUDA\n";
for (int i=0; i<num_devices(); ++i) {
out << "\nDevice " << i << ": \"" << name(i).c_str() << "\"\n";
out << " Type of device: "
<< device_type_name(i).c_str() << std::endl;
out << " Compute capability: "
<< arch(i) << std::endl;
out << " Double precision support: ";
if (double_precision(i))
out << "Yes\n";
else
out << "No\n";
out << " Total amount of global memory: "
<< gigabytes(i) << " GB\n";
#if CUDART_VERSION >= 2000
out << " Number of compute units/multiprocessors: "
<< _properties[i].multiProcessorCount << std::endl;
out << " Number of cores: "
<< cores(i) << std::endl;
#endif
out << " Total amount of constant memory: "
<< _properties[i].totalConstMem << " bytes\n";
out << " Total amount of local/shared memory per block: "
<< _properties[i].sharedMemPerBlock << " bytes\n";
out << " Total number of registers available per block: "
<< _properties[i].regsPerBlock << std::endl;
out << " Warp size: "
<< _properties[i].warpSize << std::endl;
out << " Maximum number of threads per block: "
<< _properties[i].maxThreadsPerBlock << std::endl;
out << " Maximum group size (# of threads per block) "
<< _properties[i].maxThreadsDim[0] << " x "
<< _properties[i].maxThreadsDim[1] << " x "
<< _properties[i].maxThreadsDim[2] << std::endl;
out << " Maximum item sizes (# threads for each dim) "
<< _properties[i].maxGridSize[0] << " x "
<< _properties[i].maxGridSize[1] << " x "
<< _properties[i].maxGridSize[2] << std::endl;
out << " Maximum memory pitch: "
<< max_pitch(i) << " bytes\n";
out << " Texture alignment: "
<< _properties[i].textureAlignment << " bytes\n";
out << " Clock rate: "
<< clock_rate(i) << " GHz\n";
#if CUDART_VERSION >= 2000
out << " Concurrent copy and execution: ";
if (_properties[i].deviceOverlap)
out << "Yes\n";
else
out << "No\n";
#endif
#if CUDART_VERSION >= 2020
out << " Run time limit on kernels: ";
if (_properties[i].kernelExecTimeoutEnabled)
out << "Yes\n";
else
out << "No\n";
out << " Integrated: ";
if (_properties[i].integrated)
out << "Yes\n";
else
out << "No\n";
out << " Support host page-locked memory mapping: ";
if (_properties[i].canMapHostMemory)
out << "Yes\n";
else
out << "No\n";
out << " Compute mode: ";
if (_properties[i].computeMode == cudaComputeModeDefault)
out << "Default\n"; // multiple threads can use device
else if (_properties[i].computeMode == cudaComputeModeExclusive)
out << "Exclusive\n"; // only thread can use device
else if (_properties[i].computeMode == cudaComputeModeProhibited)
out << "Prohibited\n"; // no thread can use device
#if CUDART_VERSION >= 4000
else if (_properties[i].computeMode == cudaComputeModeExclusiveProcess)
out << "Exclusive Process\n"; // multiple threads 1 process
#endif
else
out << "Unknown\n";
#endif
#if CUDART_VERSION >= 3010
out << " Concurrent kernel execution: ";
if (_properties[i].concurrentKernels)
out << "Yes\n";
else
out << "No\n";
out << " Device has ECC support enabled: ";
if (_properties[i].ECCEnabled)
out << "Yes\n";
else
out << "No\n";
#endif
}
}
}
#endif

78
lib/gpu/geryon/nvc_macros.h
View File

@ -1,78 +0,0 @@
#ifndef NVC_MACROS_H
#define NVC_MACROS_H
#if defined(__APPLE__)
#if _GLIBCXX_ATOMIC_BUILTINS == 1
#undef _GLIBCXX_ATOMIC_BUILTINS
#endif // _GLIBCXX_ATOMIC_BUILTINS
#endif // __APPLE__
#include <stdio.h>
#include <cassert>
#include <cuda_runtime.h>
#ifdef MPI_GERYON
#include "mpi.h"
#define NVC_GERYON_EXIT MPI_Abort(MPI_COMM_WORLD,-1)
#else
#define NVC_GERYON_EXIT assert(0==1)
#endif
#ifndef UCL_GERYON_EXIT
#define UCL_GERYON_EXIT NVC_GERYON_EXIT
#endif
#ifdef UCL_DEBUG
#define UCL_SYNC_DEBUG
#define UCL_DESTRUCT_CHECK
#endif
#ifndef UCL_NO_API_CHECK
#define CUDA_SAFE_CALL_NS( call) do { \
cudaError err = call; \
if( cudaSuccess != err) { \
fprintf(stderr, "Cuda error in call at file '%s' in line %i : %s.\n", \
__FILE__, __LINE__, cudaGetErrorString( err) ); \
NVC_GERYON_EXIT; \
} } while (0)
#ifdef UCL_SYNC_DEBUG
#define CUDA_SAFE_CALL( call) do { \
CUDA_SAFE_CALL_NS( call); \
cudaError err=cudaThreadSynchronize(); \
if( cudaSuccess != err) { \
fprintf(stderr, "Cuda error in file '%s' in line %i : %s.\n", \
__FILE__, __LINE__, cudaGetErrorString( err) ); \
NVC_GERYON_EXIT; \
} } while (0)
#else
#define CUDA_SAFE_CALL( call) CUDA_SAFE_CALL_NS( call)
#endif
#else // not DEBUG
// void macros for performance reasons
#define CUDA_SAFE_CALL( call) call
#define CUDA_SAFE_CALL_NS( call) call
#endif
#ifdef UCL_DESTRUCT_CHECK
#define CUDA_DESTRUCT_CALL( call) CUDA_SAFE_CALL( call)
#define CUDA_DESTRUCT_CALL_NS( call) CUDA_SAFE_CALL_NS( call)
#else
#define CUDA_DESTRUCT_CALL( call) call
#define CUDA_DESTRUCT_CALL_NS( call) call
#endif
#endif

69
lib/gpu/geryon/nvc_texture.h
View File

@ -1,69 +0,0 @@
/***************************************************************************
nvc_texture.h
-------------------
W. Michael Brown
Utilities for dealing with CUDA Runtime textures
__________________________________________________________________________
This file is part of the Geryon Unified Coprocessor Library (UCL)
__________________________________________________________________________
begin : Fri Jul 2 2010
copyright : (C) 2010 by W. Michael Brown
email : brownw@ornl.gov
***************************************************************************/
/* -----------------------------------------------------------------------
Copyright (2010) Sandia Corporation. Under the terms of Contract
DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains
certain rights in this software. This software is distributed under
the Simplified BSD License.
----------------------------------------------------------------------- */
#ifndef NVC_TEXTURE
#define NVC_TEXTURE
#include "nvc_mat.h"
namespace ucl_cudart {
/// Class storing a texture reference
class UCL_Texture {
public:
UCL_Texture() {}
~UCL_Texture() {}
/// Construct with a specified texture reference
inline UCL_Texture(textureReference *t) { get_texture(t); }
/// Set the texture reference for this object
inline void get_texture(textureReference *t) { _tex_ptr=t; }
/// Bind a float array where each fetch grabs a vector of length numel
template<class mat_typ>
inline void bind_float(mat_typ &vec, const unsigned numel) {
#ifdef UCL_DEBUG
assert(numel!=0 && numel<5);
#endif
int bits[4]={0,0,0,0};
for (int i=0; i<numel; i++) bits[i]=32;
_channel = cudaCreateChannelDesc(bits[0], bits[1], bits[2], bits[3],
cudaChannelFormatKindFloat);
(*_tex_ptr).addressMode[0] = cudaAddressModeClamp;
(*_tex_ptr).addressMode[1] = cudaAddressModeClamp;
(*_tex_ptr).filterMode = cudaFilterModePoint;
(*_tex_ptr).normalized = false;
CUDA_SAFE_CALL(cudaBindTexture(NULL,_tex_ptr,vec.cbegin(),&_channel));
}
/// Unbind the texture reference from the memory allocation
inline void unbind() { CUDA_SAFE_CALL(cudaUnbindTexture(_tex_ptr)); }
private:
textureReference *_tex_ptr;
cudaChannelFormatDesc _channel;
};
} // namespace
#endif