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lammps/lib/gpu/geryon/nvd_device.h

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/***************************************************************************
nvd_device.h
-------------------
W. Michael Brown
Utilities for dealing with cuda devices
__________________________________________________________________________
This file is part of the Geryon Unified Coprocessor Library (UCL)
__________________________________________________________________________
begin : Thu Jan 21 2010
copyright : (C) 2010 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 NVD_DEVICE
#define NVD_DEVICE
#include <string>
#include <vector>
#include <iostream>
#include "nvd_macros.h"
#include "ucl_types.h"
namespace ucl_cudadr {
// --------------------------------------------------------------------------
// - COMMAND QUEUE STUFF
// --------------------------------------------------------------------------
typedef CUstream command_queue;
inline void ucl_sync(CUstream &stream) {
CU_SAFE_CALL(cuStreamSynchronize(stream));
}
struct NVDProperties {
int device_id;
std::string name;
int major;
int minor;
CUDA_INT_TYPE totalGlobalMem;
int multiProcessorCount;
CUdevprop_st p;
int kernelExecTimeoutEnabled;
int integrated;
int canMapHostMemory;
int concurrentKernels;
int ECCEnabled;
int computeMode;
};
/// 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 **/
inline UCL_Device();
inline ~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
inline std::string platform_name()
{ return "NVIDIA Corporation NVIDIA CUDA Driver"; }
/// Delete any contexts/data and set the platform number to be used
inline int set_platform(const int pid);
/// Return the number of devices that support CUDA
inline int num_devices() { return _properties.size(); }
/// Set the CUDA device to the specified device number
/** A context and default command queue will be created for the device
* Returns UCL_SUCCESS if successful or UCL_ERROR if the device could not
* be allocated for use. clear() is called to delete any contexts and
* associated data from previous calls to set(). **/
inline int set(int num);
/// Delete any context and associated data stored from a call to set()
inline void clear();
/// 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]; }
/// 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()
{ return _cq.size(); }
/// Add a stream for device computations
inline void push_command_queue() {
_cq.push_back(CUstream());
CU_SAFE_CALL(cuStreamCreate(&_cq.back(),0));
}
/// Remove a stream for device computations
/** \note You cannot delete the default stream **/
inline void pop_command_queue() {
if (_cq.size()<2) return;
CU_SAFE_CALL_NS(cuStreamDestroy(_cq.back()));
_cq.pop_back();
}
/// 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];
}
/// 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 host memory is efficiently addressable from device
inline bool shared_memory() { return shared_memory(_device); }
/// Returns true if host memory is efficiently addressable from device
inline bool shared_memory(const int i) { return device_type(i)==UCL_CPU; }
/// Returns true if double precision is support for the current device
inline bool double_precision() { return double_precision(_device); }
/// Returns true if double precision is support for the device
inline bool double_precision(const int i) {return arch(i)>=1.3;}
/// Get the number of compute units on the current device
inline unsigned cus() { return cus(_device); }
/// Get the number of compute units
inline unsigned cus(const int i)
{ return _properties[i].multiProcessorCount; }
/// 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)<2.1) return _properties[i].multiProcessorCount*32;
else if (arch(i)<3.0) return _properties[i].multiProcessorCount*48;
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; }
// Get the gigabytes of free memory in the current device
inline double free_gigabytes() { return free_gigabytes(_device); }
// Get the gigabytes of free memory
inline double free_gigabytes(const int i)
{ return static_cast<double>(free_bytes(i))/1073741824; }
// Get the bytes of free memory in the current device
inline size_t free_bytes() { return free_bytes(_device); }
// Get the bytes of free memory
inline size_t free_bytes(const int i) {
CUDA_INT_TYPE dfree, dtotal;
CU_SAFE_CALL_NS(cuMemGetInfo(&dfree, &dtotal));
return static_cast<size_t>(dfree);
}
/// 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].p.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].p.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].p.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 == CU_COMPUTEMODE_DEFAULT); }
/// True if splitting device into equal subdevices supported
inline bool fission_equal()
{ return fission_equal(_device); }
/// True if splitting device into equal subdevices supported
inline bool fission_equal(const int i)
{ return false; }
/// True if splitting device into subdevices by specified counts supported
inline bool fission_by_counts()
{ return fission_by_counts(_device); }
/// True if splitting device into subdevices by specified counts supported
inline bool fission_by_counts(const int i)
{ return false; }
/// True if splitting device into subdevices by affinity domains supported
inline bool fission_by_affinity()
{ return fission_by_affinity(_device); }
/// True if splitting device into subdevices by affinity domains supported
inline bool fission_by_affinity(const int i)
{ return false; }
/// Maximum number of subdevices allowed from device fission
inline int max_sub_devices()
{ return max_sub_devices(_device); }
/// Maximum number of subdevices allowed from device fission
inline int max_sub_devices(const int i)
{ return 0; }
/// List all devices along with all properties
inline void print_all(std::ostream &out);
private:
int _device, _num_devices;
std::vector<NVDProperties> _properties;
std::vector<CUstream> _cq;
CUdevice _cu_device;
CUcontext _context;
};
// Grabs the properties for all devices
UCL_Device::UCL_Device() {
CU_SAFE_CALL_NS(cuInit(0));
CU_SAFE_CALL_NS(cuDeviceGetCount(&_num_devices));
for (int dev=0; dev<_num_devices; ++dev) {
CUdevice m;
CU_SAFE_CALL_NS(cuDeviceGet(&m,dev));
int major, minor;
CU_SAFE_CALL_NS(cuDeviceComputeCapability(&major,&minor,m));
if (major==9999)
continue;
_properties.push_back(NVDProperties());
_properties.back().device_id=dev;
_properties.back().major=major;
_properties.back().minor=minor;
char namecstr[1024];
CU_SAFE_CALL_NS(cuDeviceGetName(namecstr,1024,m));
_properties.back().name=namecstr;
CU_SAFE_CALL_NS(cuDeviceTotalMem(&_properties.back().totalGlobalMem,m));
CU_SAFE_CALL_NS(cuDeviceGetAttribute(&_properties.back().multiProcessorCount,
CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT,
m));
CU_SAFE_CALL_NS(cuDeviceGetProperties(&_properties.back().p,m));
#if CUDA_VERSION >= 2020
CU_SAFE_CALL_NS(cuDeviceGetAttribute(
&_properties.back().kernelExecTimeoutEnabled,
CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT,dev));
CU_SAFE_CALL_NS(cuDeviceGetAttribute(
&_properties.back().integrated,
CU_DEVICE_ATTRIBUTE_INTEGRATED, dev));
CU_SAFE_CALL_NS(cuDeviceGetAttribute(
&_properties.back().canMapHostMemory,
CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY, dev));
CU_SAFE_CALL_NS(cuDeviceGetAttribute(&_properties.back().computeMode,
CU_DEVICE_ATTRIBUTE_COMPUTE_MODE,dev));
#endif
#if CUDA_VERSION >= 3010
CU_SAFE_CALL_NS(cuDeviceGetAttribute(
&_properties.back().concurrentKernels,
CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS, dev));
CU_SAFE_CALL_NS(cuDeviceGetAttribute(
&_properties.back().ECCEnabled,
CU_DEVICE_ATTRIBUTE_ECC_ENABLED, dev));
#endif
}
_device=-1;
_cq.push_back(CUstream());
_cq.back()=0;
}
UCL_Device::~UCL_Device() {
clear();
}
int UCL_Device::set_platform(const int pid) {
clear();
#ifdef UCL_DEBUG
assert(pid<num_platforms());
#endif
return UCL_SUCCESS;
}
// Set the CUDA device to the specified device number
int UCL_Device::set(int num) {
clear();
_device=_properties[num].device_id;
CU_SAFE_CALL_NS(cuDeviceGet(&_cu_device,_device));
CUresult err=cuCtxCreate(&_context,0,_cu_device);
if (err!=CUDA_SUCCESS) {
#ifndef UCL_NO_EXIT
std::cerr << "UCL Error: Could not access accelerator number " << num
<< " for use.\n";
UCL_GERYON_EXIT;
#endif
return UCL_ERROR;
}
return UCL_SUCCESS;
}
void UCL_Device::clear() {
if (_device>-1) {
for (int i=1; i<num_queues(); i++) pop_command_queue();
cuCtxDestroy(_context);
}
_device=-1;
}
// List all devices along with all properties
void UCL_Device::print_all(std::ostream &out) {
#if CUDA_VERSION >= 2020
int driver_version;
cuDriverGetVersion(&driver_version);
out << "CUDA Driver Version: "
<< driver_version/1000 << "." << driver_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) << "\"\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 CUDA_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].p.totalConstantMemory << " bytes\n";
out << " Total amount of local/shared memory per block: "
<< _properties[i].p.sharedMemPerBlock << " bytes\n";
out << " Total number of registers available per block: "
<< _properties[i].p.regsPerBlock << std::endl;
out << " Warp size: "
<< _properties[i].p.SIMDWidth << std::endl;
out << " Maximum number of threads per block: "
<< _properties[i].p.maxThreadsPerBlock << std::endl;
out << " Maximum group size (# of threads per block) "
<< _properties[i].p.maxThreadsDim[0] << " x "
<< _properties[i].p.maxThreadsDim[1] << " x "
<< _properties[i].p.maxThreadsDim[2] << std::endl;
out << " Maximum item sizes (# threads for each dim) "
<< _properties[i].p.maxGridSize[0] << " x "
<< _properties[i].p.maxGridSize[1] << " x "
<< _properties[i].p.maxGridSize[2] << std::endl;
out << " Maximum memory pitch: "
<< max_pitch(i) << " bytes\n";
out << " Texture alignment: "
<< _properties[i].p.textureAlign << " bytes\n";
out << " Clock rate: "
<< clock_rate(i) << " GHz\n";
#if CUDA_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 == CU_COMPUTEMODE_DEFAULT)
out << "Default\n"; // multiple threads can use device
else if (_properties[i].computeMode == CU_COMPUTEMODE_EXCLUSIVE)
out << "Exclusive\n"; // only thread can use device
else if (_properties[i].computeMode == CU_COMPUTEMODE_PROHIBITED)
out << "Prohibited\n"; // no thread can use device
#if CUDART_VERSION >= 4000
else if (_properties[i].computeMode == CU_COMPUTEMODE_EXCLUSIVE_PROCESS)
out << "Exclusive Process\n"; // multiple threads 1 process
#endif
else
out << "Unknown\n";
#endif
#if CUDA_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
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