nvd_device.h
e368acdaeb22master

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
			#if CUDA_VERSION >= 8000
			else if (_properties[i].computeMode == CU_COMPUTEMODE_EXCLUSIVE_PROCESS)
			#else
			else if (_properties[i].computeMode == CU_COMPUTEMODE_EXCLUSIVE)
			#endif
			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

lammps/lib/gpu/geryon/nvd_device.he368acdaeb22master

nvd_device.hView Options

lammps/lib/gpu/geryon/nvd_device.h
e368acdaeb22master

nvd_device.h
View Options