various minor OpenCL related fixes and improvements to the GPU package
- document previously undocumented OpenCL tune settings - implement OpenCL platform selection through prefixing the device type with the platform id separated by a colon - allow passing custom tune parameters though postfixing the device type with the 13 tuneable parameters separated by commas - remove an extra clear() that would delete device properties structs an cause LAMMPS to output garbage strings
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@ -33,8 +33,10 @@ args = arguments specific to the style :l
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last = ID of last GPU to be used on each node
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{tpa} value = Nthreads
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Nthreads = # of GPU threads used per atom
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{device} value = device_type
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device_type = {kepler} or {fermi} or {cypress} or {generic}
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{device} value = device_type or platform_id:device_type or platform_id:custom,val1,val2,val3,..,val13
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platform_id = numerical OpenCL platform id (default: -1)
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device_type = {kepler} or {fermi} or {cypress} or {intel} or {phi} or {generic} or {custom}
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val1,val2,... = custom OpenCL tune parameters (see below for details)
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{blocksize} value = size
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size = thread block size for pair force computation
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{intel} args = NPhi keyword value ...
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@ -96,6 +98,9 @@ args = arguments specific to the style :l
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package gpu 1
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package gpu 1 split 0.75
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package gpu 2 split -1.0
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package gpu 1 device kepler
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package gpu 1 device 2:generic
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package gpu 1 device custom,32,4,8,256,11,128,256,128,32,64,8,128,128
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package kokkos neigh half comm device
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package omp 0 neigh no
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package omp 4
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@ -244,12 +249,40 @@ the value can improve performance. The number of threads per atom must
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be a power of 2 and currently cannot be greater than 32.
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The {device} keyword can be used to tune parameters optimized for a
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specific accelerator, when using OpenCL. For CUDA, the {device}
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keyword is ignored. Currently, the device type is limited to NVIDIA
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Kepler, NVIDIA Fermi, AMD Cypress, or a generic device. More devices
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may be added later. The default device type can be specified when
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building LAMMPS with the GPU library, via settings in the
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lib/gpu/Makefile that is used.
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specific accelerator and platform when using OpenCL. OpenCL supports
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the concept of a [platform], which represents one or more devices that
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share the same driver (e.g. there would be a different platform for
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GPUs from different vendors or for CPU based accelerator support).
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In LAMMPS only one platform can be active at a time and by default
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the first platform with an accelerator is selected. This is equivalent
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to using a platform ID of -1. The platform ID is a number corresponding
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to the output of the ocl_get_devices tool. The platform ID is passed
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to the GPU library, by prefixing the {device} keyword with that number
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separated by a colon. For CUDA, the {device} keyword is ignored.
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Currently, the device tuning support is limited to NVIDIA Kepler, NVIDIA
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Fermi, AMD Cypress, Intel x86_64 CPU, Intel Xeon Phi, or a generic device.
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More devices may be added later. The default device type can be
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specified when building LAMMPS with the GPU library, via setting a
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variable in the lib/gpu/Makefile that is used.
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In addition, a device type {custom} is available, which is followed by
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13 comma separated numbers, which allows to set those tweakable parameters
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from the package command. It can be combined with the (colon separated)
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platform id. The individual settings are:
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MEM_THREADS
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THREADS_PER_ATOM
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THREADS_PER_CHARGE
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BLOCK_PAIR
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MAX_SHARED_TYPES
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BLOCK_NBOR_BUILD
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BLOCK_BIO_PAIR
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BLOCK_ELLIPSE
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WARP_SIZE
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PPPM_BLOCK_1D
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BLOCK_CELL_2D
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BLOCK_CELL_ID
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MAX_BIO_SHARED_TYPES :ul
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The {blocksize} keyword allows you to tweak the number of threads used
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per thread block. This number should be a multiple of 32 (for GPUs)
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@ -165,8 +165,8 @@ class UCL_Device {
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/// Get the current OpenCL device name
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inline std::string name() { return name(_device); }
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/// Get the OpenCL device name
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inline std::string name(const int i)
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{ return std::string(_properties[i].name); }
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inline std::string name(const int i) {
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return std::string(_properties[i].name); }
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/// Get a string telling the type of the current device
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inline std::string device_type_name() { return device_type_name(_device); }
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@ -281,7 +281,7 @@ class UCL_Device {
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inline cl_device_id & cl_device() { return _cl_device; }
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/// Select the platform that has accelerators
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inline void set_platform_accelerator(int pid=-1);
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inline int set_platform_accelerator(int pid=-1);
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private:
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int _num_platforms; // Number of platforms
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@ -324,6 +324,7 @@ UCL_Device::~UCL_Device() {
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void UCL_Device::clear() {
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_properties.clear();
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_cl_devices.clear();
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if (_device>-1) {
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for (size_t i=0; i<_cq.size(); i++) {
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CL_DESTRUCT_CALL(clReleaseCommandQueue(_cq.back()));
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@ -520,8 +521,6 @@ int UCL_Device::device_type(const int i) {
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// Set the CUDA device to the specified device number
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int UCL_Device::set(int num) {
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clear();
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cl_device_id *device_list = new cl_device_id[_num_devices];
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cl_uint n;
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CL_SAFE_CALL(clGetDeviceIDs(_cl_platform,CL_DEVICE_TYPE_ALL,_num_devices,
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@ -612,7 +611,7 @@ void UCL_Device::print_all(std::ostream &out) {
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// Select the platform that is associated with accelerators
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// if pid < 0, select the first platform
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void UCL_Device::set_platform_accelerator(int pid) {
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int UCL_Device::set_platform_accelerator(int pid) {
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if (pid < 0) {
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int found = 0;
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for (int n=0; n<_num_platforms; n++) {
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@ -625,10 +624,11 @@ void UCL_Device::set_platform_accelerator(int pid) {
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break;
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}
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}
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if (found) break;
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if (found) return UCL_SUCCESS;
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}
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return UCL_ERROR;
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} else {
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set_platform(pid);
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return set_platform(pid);
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}
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}
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@ -35,7 +35,7 @@ using namespace LAMMPS_AL;
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template <class numtyp, class acctyp>
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DeviceT::Device() : _init_count(0), _device_init(false),
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_gpu_mode(GPU_FORCE), _first_device(0),
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_last_device(0), _compiled(false) {
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_last_device(0), _platform_id(-1), _compiled(false) {
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}
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template <class numtyp, class acctyp>
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@ -67,6 +67,17 @@ int DeviceT::init_device(MPI_Comm world, MPI_Comm replica, const int first_gpu,
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_particle_split=p_split;
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_cell_size=cell_size;
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_block_pair=block_pair;
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// support selecting platform though "package device" keyword.
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// "0:generic" will select platform 0 and tune for generic device
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// "1:fermi" will select platform 1 and tune for Nvidia Fermi gpu
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if (ocl_vendor) {
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char *sep = NULL;
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if ((sep = strstr(ocl_vendor,":"))) {
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*sep = '\0';
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_platform_id = atoi(ocl_vendor);
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ocl_vendor = sep+1;
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}
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}
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// Get the rank/size within the world
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MPI_Comm_rank(_comm_world,&_world_me);
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@ -135,6 +146,9 @@ int DeviceT::init_device(MPI_Comm world, MPI_Comm replica, const int first_gpu,
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return -7;
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#endif
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if (gpu->set_platform_accelerator(_platform_id)!=UCL_SUCCESS)
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return -12;
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if (gpu->set(my_gpu)!=UCL_SUCCESS)
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return -6;
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@ -191,13 +205,15 @@ int DeviceT::set_ocl_params(char *ocl_vendor) {
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_ocl_vendor_string="-DUSE_OPENCL";
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int token_count=0;
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std::string params[13];
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char *pch = strtok(ocl_vendor,"\" ");
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char *pch = strtok(ocl_vendor,",");
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pch = strtok(NULL,",");
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if (pch == NULL) return -11;
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while (pch != NULL) {
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if (token_count==13)
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return -11;
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params[token_count]=pch;
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token_count++;
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pch = strtok(NULL,"\" ");
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pch = strtok(NULL,",");
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}
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_ocl_vendor_string+=" -DMEM_THREADS="+params[0]+
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" -DTHREADS_PER_ATOM="+params[1]+
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@ -656,7 +672,7 @@ int DeviceT::compile_kernels() {
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dev_program=new UCL_Program(*gpu);
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int success=dev_program->load_string(device,compile_string().c_str());
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if (success!=UCL_SUCCESS)
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return -4;
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return -6;
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k_zero.set_function(*dev_program,"kernel_zero");
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k_info.set_function(*dev_program,"kernel_info");
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_compiled=true;
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@ -292,7 +292,7 @@ class Device {
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MPI_Comm _comm_world, _comm_replica, _comm_gpu;
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int _procs_per_gpu, _gpu_rank, _world_me, _world_size, _replica_me,
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_replica_size;
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int _gpu_mode, _first_device, _last_device, _nthreads;
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int _gpu_mode, _first_device, _last_device, _platform_id, _nthreads;
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double _particle_split;
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double _cpu_full;
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double _ptx_arch;
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@ -58,6 +58,9 @@ namespace GPU_EXTRA {
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else if (all_success == -11)
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error->all(FLERR,
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"Invalid custom OpenCL parameter string.");
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else if (all_success == -12)
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error->all(FLERR,
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"Invalid OpenCL platform ID.");
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else
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error->all(FLERR,"Unknown error in GPU library");
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}
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