Committing CUTLASS for release.
This commit is contained in:
akerr
@@ -0,0 +1,312 @@
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/******************************************************************************
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* Copyright (c) 2011-2017, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
|
||||
* modification, are not permitted.
|
||||
*
|
||||
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
|
||||
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
|
||||
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
||||
* DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
|
||||
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
|
||||
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
|
||||
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
|
||||
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
||||
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
|
||||
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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||||
*
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******************************************************************************/
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#pragma once
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/**
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* \file
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* Utility for parsing command line arguments
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*/
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#include <string>
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#include <vector>
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#include <sstream>
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#include <iostream>
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#include <limits>
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#include <cuda_runtime.h>
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#include <cutlass/util/debug.h>
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namespace cutlass {
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/******************************************************************************
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* command_line
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******************************************************************************/
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/**
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* Utility for parsing command line arguments
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*/
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struct command_line
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{
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std::vector<std::string> keys;
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std::vector<std::string> values;
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std::vector<std::string> args;
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int device_id;
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cudaDeviceProp device_prop;
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float device_giga_bandwidth;
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size_t device_free_physmem;
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size_t device_total_physmem;
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/**
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* Constructor
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*/
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command_line(int argc, const char **argv, int device_id = -1) :
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keys(10),
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values(10),
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device_id(device_id)
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{
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using namespace std;
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for (int i = 1; i < argc; i++)
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{
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string arg = argv[i];
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if ((arg[0] != '-') || (arg[1] != '-'))
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{
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args.push_back(arg);
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continue;
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}
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string::size_type pos;
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string key, val;
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if ((pos = arg.find('=')) == string::npos) {
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key = string(arg, 2, arg.length() - 2);
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val = "";
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} else {
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key = string(arg, 2, pos - 2);
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val = string(arg, pos + 1, arg.length() - 1);
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}
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keys.push_back(key);
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values.push_back(val);
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}
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// Initialize device
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CUDA_PERROR_EXIT(device_init());
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}
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/**
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* Checks whether a flag "--<flag>" is present in the commandline
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*/
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bool check_cmd_line_flag(const char* arg_name)
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{
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using namespace std;
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for (int i = 0; i < int(keys.size()); ++i)
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{
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if (keys[i] == string(arg_name))
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return true;
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}
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return false;
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}
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/**
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* Returns number of naked (non-flag and non-key-value) commandline parameters
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*/
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template <typename value_t>
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int num_naked_args()
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{
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return args.size();
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}
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/**
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* Returns the commandline parameter for a given index (not including flags)
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*/
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template <typename value_t>
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void get_cmd_line_argument(int index, value_t &val)
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{
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using namespace std;
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if (index < args.size()) {
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istringstream str_stream(args[index]);
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str_stream >> val;
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}
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}
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/**
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* Returns the value specified for a given commandline parameter --<flag>=<value>
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*/
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template <typename value_t>
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void get_cmd_line_argument(const char *arg_name, value_t &val)
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{
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using namespace std;
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for (int i = 0; i < int(keys.size()); ++i)
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{
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if (keys[i] == string(arg_name))
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{
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istringstream str_stream(values[i]);
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str_stream >> val;
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}
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}
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}
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/**
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* Returns the values specified for a given commandline parameter --<flag>=<value>,<value>*
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*/
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template <typename value_t>
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void get_cmd_line_arguments(
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const char *arg_name,
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std::vector<value_t> &vals,
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char sep = ',')
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{
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using namespace std;
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if (check_cmd_line_flag(arg_name))
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{
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// Clear any default values
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vals.clear();
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// Recover from multi-value string
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for (int i = 0; i < keys.size(); ++i)
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{
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if (keys[i] == string(arg_name))
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{
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string val_string(values[i]);
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istringstream str_stream(val_string);
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string::size_type old_pos = 0;
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string::size_type new_pos = 0;
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// Iterate <sep>-delimited values
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value_t val;
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while ((new_pos = val_string.find(sep, old_pos)) != string::npos)
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{
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if (new_pos != old_pos)
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{
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str_stream.width(new_pos - old_pos);
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str_stream >> val;
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vals.push_back(val);
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}
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// skip over delimiter
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str_stream.ignore(1);
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old_pos = new_pos + 1;
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}
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// Read last value
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str_stream >> val;
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vals.push_back(val);
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}
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}
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}
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}
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/**
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* The number of pairs parsed
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*/
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int parsed_argc()
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{
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return (int) keys.size();
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}
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/**
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* Initialize device
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*/
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cudaError_t device_init()
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{
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cudaError_t error = cudaSuccess;
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do
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{
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int deviceCount;
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if (CUDA_PERROR(error = cudaGetDeviceCount(&deviceCount))) break;
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if (deviceCount == 0) {
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fprintf(stderr, "No devices supporting CUDA.\n");
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exit(1);
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}
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if (device_id < 0)
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{
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get_cmd_line_argument("device", device_id);
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}
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if ((device_id > deviceCount - 1) || (device_id < 0))
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{
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device_id = 0;
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}
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if (CUDA_PERROR(error = cudaSetDevice(device_id))) break;
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if (CUDA_PERROR(error = cudaMemGetInfo(&device_free_physmem, &device_total_physmem))) break;
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if (CUDA_PERROR(error = cudaGetDeviceProperties(&device_prop, device_id))) break;
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if (device_prop.major < 1) {
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fprintf(stderr, "Device does not support CUDA.\n");
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exit(1);
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}
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device_giga_bandwidth = float(device_prop.memoryBusWidth) * device_prop.memoryClockRate * 2 / 8 / 1000 / 1000;
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} while (0);
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return error;
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}
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//-------------------------------------------------------------------------
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// Utility functions
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//-------------------------------------------------------------------------
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/// Tokenizes a comma-delimited list of string pairs delimited by ':'
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static void tokenize(
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std::vector<std::pair<std::string, std::string> > &tokens,
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std::string const &str,
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char delim = ',',
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char sep = ':')
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{
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// Home-built to avoid Boost dependency
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size_t s_idx = 0;
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size_t d_idx = std::string::npos;
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while (s_idx < str.size())
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{
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d_idx = str.find_first_of(delim, s_idx);
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size_t end_idx = (d_idx != std::string::npos ? d_idx : str.size());
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size_t sep_idx = str.find_first_of(sep, s_idx);
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size_t offset = 1;
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if (sep_idx == std::string::npos || sep_idx >= end_idx)
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{
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sep_idx = end_idx;
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offset = 0;
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}
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std::pair<std::string, std::string> item(
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str.substr(s_idx, sep_idx - s_idx),
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str.substr(sep_idx + offset, end_idx - sep_idx - offset));
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tokens.push_back(item);
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s_idx = end_idx + 1;
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}
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}
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/// Tokenizes a comma-delimited list of string pairs delimited by ':'
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static void tokenize(
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std::vector<std::string > &tokens,
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std::string const &str,
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char delim = ',',
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char sep = ':')
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{
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std::vector<std::pair<std::string, std::string> > token_pairs;
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tokenize(token_pairs, str, delim, sep);
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for (auto const &tok : token_pairs)
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{
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tokens.push_back(tok.first);
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}
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}
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};
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} // namespace cutlass
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@@ -0,0 +1,83 @@
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/******************************************************************************
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* Copyright (c) 2011-2017, NVIDIA CORPORATION. All rights reserved.
|
||||
*
|
||||
* Redistribution and use in source and binary forms, with or without
|
||||
* modification, are not permitted.
|
||||
*
|
||||
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
|
||||
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
|
||||
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
||||
* DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
|
||||
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
|
||||
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
|
||||
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
|
||||
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
||||
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
|
||||
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
||||
*
|
||||
******************************************************************************/
|
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#pragma once
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/**
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* \file
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* \brief C++ exception semantics for CUDA error codes
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*/
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#include <iosfwd>
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#include <cuda_runtime.h>
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namespace cutlass {
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/// C++ exception wrapper for CUDA \p cudaError_t
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class cuda_exception : public std::exception
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{
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public:
|
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|
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/// Constructor
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||||
cuda_exception(
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const char *msg = "",
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cudaError_t err = cudaErrorUnknown)
|
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:
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msg(msg), err(err)
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{}
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/// Returns the explanatory string
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const char *what() const noexcept
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{
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return msg;
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}
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|
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/// Returns the underlying CUDA \p cudaError_t
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cudaError_t cudaError() const
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{
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return err;
|
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}
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protected:
|
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/// Explanatory string
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const char *msg;
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|
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/// Underlying CUDA \p cudaError_t
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cudaError_t err;
|
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};
|
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|
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/// Writes a cudaError_t to an output stream
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inline std::ostream & operator<<(std::ostream &out, cudaError_t result)
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{
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return out << cudaGetErrorString(result);
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}
|
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|
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/// Writes a cuda_exception instance to an output stream
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inline std::ostream & operator<<(std::ostream &out, cuda_exception const &e)
|
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{
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return out << e.what() << ": " << e.cudaError();
|
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}
|
||||
|
||||
|
||||
} // namespace cutlass
|
||||
@@ -0,0 +1,224 @@
|
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/******************************************************************************
|
||||
* Copyright (c) 2011-2017, NVIDIA CORPORATION. All rights reserved.
|
||||
*
|
||||
* Redistribution and use in source and binary forms, with or without
|
||||
* modification, are not permitted.
|
||||
*
|
||||
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
|
||||
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
|
||||
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
||||
* DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
|
||||
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
|
||||
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
|
||||
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
|
||||
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
||||
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
|
||||
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
||||
*
|
||||
******************************************************************************/
|
||||
|
||||
#pragma once
|
||||
|
||||
/**
|
||||
* \file
|
||||
* Utilities for interacting with the opaque CUDA __half type
|
||||
*/
|
||||
|
||||
#include <stdint.h>
|
||||
#include <cuda_fp16.h>
|
||||
#include <iosfwd>
|
||||
|
||||
namespace cutlass {
|
||||
|
||||
|
||||
/******************************************************************************
|
||||
* half_t
|
||||
******************************************************************************/
|
||||
|
||||
/**
|
||||
* Host-based fp16 data type compatible and convertible with __half
|
||||
*/
|
||||
struct half_t
|
||||
{
|
||||
uint16_t __x;
|
||||
|
||||
/// Constructor from __half
|
||||
half_t(const __half &other)
|
||||
{
|
||||
__x = reinterpret_cast<const uint16_t&>(other);
|
||||
}
|
||||
|
||||
/// Constructor from integer
|
||||
half_t(int a)
|
||||
{
|
||||
*this = half_t(float(a));
|
||||
}
|
||||
|
||||
|
||||
/// Constructor from float
|
||||
half_t(float a)
|
||||
{
|
||||
uint32_t ia = *reinterpret_cast<uint32_t*>(&a);
|
||||
uint16_t ir;
|
||||
|
||||
ir = (ia >> 16) & 0x8000;
|
||||
|
||||
if ((ia & 0x7f800000) == 0x7f800000)
|
||||
{
|
||||
if ((ia & 0x7fffffff) == 0x7f800000)
|
||||
{
|
||||
ir |= 0x7c00; /* infinity */
|
||||
}
|
||||
else
|
||||
{
|
||||
ir = 0x7fff; /* canonical NaN */
|
||||
}
|
||||
}
|
||||
else if ((ia & 0x7f800000) >= 0x33000000)
|
||||
{
|
||||
int32_t shift = (int32_t) ((ia >> 23) & 0xff) - 127;
|
||||
if (shift > 15)
|
||||
{
|
||||
ir |= 0x7c00; /* infinity */
|
||||
}
|
||||
else
|
||||
{
|
||||
ia = (ia & 0x007fffff) | 0x00800000; /* extract mantissa */
|
||||
if (shift < -14)
|
||||
{ /* denormal */
|
||||
ir |= ia >> (-1 - shift);
|
||||
ia = ia << (32 - (-1 - shift));
|
||||
}
|
||||
else
|
||||
{ /* normal */
|
||||
ir |= ia >> (24 - 11);
|
||||
ia = ia << (32 - (24 - 11));
|
||||
ir = ir + ((14 + shift) << 10);
|
||||
}
|
||||
/* IEEE-754 round to nearest of even */
|
||||
if ((ia > 0x80000000) || ((ia == 0x80000000) && (ir & 1)))
|
||||
{
|
||||
ir++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
this->__x = ir;
|
||||
}
|
||||
|
||||
/// Cast to __half
|
||||
operator __half() const
|
||||
{
|
||||
return reinterpret_cast<const __half&>(__x);
|
||||
}
|
||||
|
||||
/// Cast to float
|
||||
operator float() const
|
||||
{
|
||||
int sign = ((this->__x >> 15) & 1);
|
||||
int exp = ((this->__x >> 10) & 0x1f);
|
||||
int mantissa = (this->__x & 0x3ff);
|
||||
uint32_t f = 0;
|
||||
|
||||
if (exp > 0 && exp < 31)
|
||||
{
|
||||
// normal
|
||||
exp += 112;
|
||||
f = (sign << 31) | (exp << 23) | (mantissa << 13);
|
||||
}
|
||||
else if (exp == 0)
|
||||
{
|
||||
if (mantissa)
|
||||
{
|
||||
// subnormal
|
||||
exp += 113;
|
||||
while ((mantissa & (1 << 10)) == 0)
|
||||
{
|
||||
mantissa <<= 1;
|
||||
exp--;
|
||||
}
|
||||
mantissa &= 0x3ff;
|
||||
f = (sign << 31) | (exp << 23) | (mantissa << 13);
|
||||
}
|
||||
else
|
||||
{
|
||||
// zero
|
||||
f = 0;
|
||||
}
|
||||
}
|
||||
else if (exp == 31)
|
||||
{
|
||||
if (mantissa)
|
||||
{
|
||||
f = 0x7fffffff; // not a number
|
||||
}
|
||||
else
|
||||
{
|
||||
f = (0xff << 23) | (sign << 31); // inf
|
||||
}
|
||||
}
|
||||
return *reinterpret_cast<float const *>(&f);
|
||||
}
|
||||
|
||||
|
||||
/// Get raw storage
|
||||
uint16_t raw()
|
||||
{
|
||||
return this->__x;
|
||||
}
|
||||
|
||||
/// Assignment by sum
|
||||
bool operator ==(const half_t &other)
|
||||
{
|
||||
return (this->__x == other.__x);
|
||||
}
|
||||
|
||||
/// Increment
|
||||
half_t& operator +=(const half_t &rhs)
|
||||
{
|
||||
*this = half_t(float(*this) + float(rhs));
|
||||
return *this;
|
||||
}
|
||||
|
||||
/// Decrement
|
||||
half_t& operator -=(const half_t &rhs)
|
||||
{
|
||||
*this = half_t(float(*this) - float(rhs));
|
||||
return *this;
|
||||
}
|
||||
|
||||
/// Multiply
|
||||
half_t operator*(const half_t &other)
|
||||
{
|
||||
return half_t(float(*this) * float(other));
|
||||
}
|
||||
|
||||
/// Multiply
|
||||
half_t operator+(const half_t &other)
|
||||
{
|
||||
return half_t(float(*this) + float(other));
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
|
||||
/******************************************************************************
|
||||
* I/O stream overloads
|
||||
******************************************************************************/
|
||||
|
||||
/// Insert formatted \p half_t into the output stream
|
||||
std::ostream& operator<<(std::ostream &out, const half_t &x)
|
||||
{
|
||||
out << (float)x;
|
||||
return out;
|
||||
}
|
||||
|
||||
|
||||
/// Insert formatted \p __half into the output stream
|
||||
std::ostream& operator<<(std::ostream &out, const __half &x)
|
||||
{
|
||||
return out << half_t(x);
|
||||
}
|
||||
|
||||
|
||||
} // namespace cutlass
|
||||
@@ -0,0 +1,495 @@
|
||||
/******************************************************************************
|
||||
* Copyright (c) 2011-2017, NVIDIA CORPORATION. All rights reserved.
|
||||
*
|
||||
* Redistribution and use in source and binary forms, with or without
|
||||
* modification, are not permitted.
|
||||
*
|
||||
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
|
||||
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
|
||||
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
||||
* DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
|
||||
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
|
||||
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
|
||||
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
|
||||
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
||||
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
|
||||
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
||||
*
|
||||
******************************************************************************/
|
||||
|
||||
#pragma once
|
||||
|
||||
/**
|
||||
* \file
|
||||
* Matrix data structure providing basic CPU-based algorithms and
|
||||
* operations that can be cloned and synchronized in GPU device memory
|
||||
*/
|
||||
|
||||
#include <vector>
|
||||
#include <fstream>
|
||||
|
||||
#include <cutlass/util/debug.h>
|
||||
#include "../cutlass/util/matrix_transform.h"
|
||||
#include "half.h"
|
||||
|
||||
|
||||
namespace cutlass {
|
||||
|
||||
/**
|
||||
* \brief Matrix data structure providing basic CPU-based algorithms and
|
||||
* operations that be synchronized with a GPU-based replica
|
||||
*/
|
||||
template <typename value_t>
|
||||
struct matrix
|
||||
{
|
||||
// Host value type (must be convertible to/from value_t)
|
||||
typedef typename nv_std::conditional<
|
||||
(nv_std::is_same<value_t, __half>::value), // If (value_t == __half) ...
|
||||
half_t, // ... use half_t internally for host storage, else...
|
||||
value_t>::type // ... use value_t directly
|
||||
host_value_t;
|
||||
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
// Data members
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
private:
|
||||
|
||||
/// M dimension (height in rows)
|
||||
int _m;
|
||||
|
||||
/// N dimension (width in columns)
|
||||
int _n;
|
||||
|
||||
/// Data array on host
|
||||
std::vector<host_value_t> _h_data;
|
||||
|
||||
/// Clone of data array on GPU device
|
||||
value_t *_d_data;
|
||||
|
||||
/// GPU Device identifier that clone synchronizes with
|
||||
int _device_id;
|
||||
|
||||
public:
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
// Lifetime and synchronization
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
/**
|
||||
* Constructor: zero-initializes the matrix.
|
||||
*/
|
||||
matrix(
|
||||
int m, ///< Height of the matrix in rows
|
||||
int n) ///< Width of the matrix in columns
|
||||
:
|
||||
_m(m),
|
||||
_n(n),
|
||||
_d_data(NULL),
|
||||
_device_id(0)
|
||||
{
|
||||
_h_data.resize(_m * _n, 0);
|
||||
CUDA_PERROR_EXIT(cudaMalloc((void ** )&_d_data, sizeof(value_t) * _m * _n));
|
||||
CUDA_PERROR_EXIT(cudaGetDevice(&_device_id));
|
||||
}
|
||||
|
||||
/// Destructor
|
||||
~matrix()
|
||||
{
|
||||
if (_d_data)
|
||||
{
|
||||
CUDA_PERROR_EXIT(cudaFree(_d_data));
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Synchronize the GPU-based replica with the current host-based matrix data
|
||||
*/
|
||||
void sync_device()
|
||||
{
|
||||
size_t bytes = _m * _n * sizeof(value_t);
|
||||
CUDA_PERROR_EXIT(cudaMemcpy(_d_data, &_h_data[0], bytes, cudaMemcpyHostToDevice));
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Synchronize the host-based replica with the current GPU-based matrix data
|
||||
*/
|
||||
void sync_host()
|
||||
{
|
||||
size_t bytes = _m * _n * sizeof(value_t);
|
||||
CUDA_PERROR_EXIT(cudaMemcpy(&_h_data[0], _d_data, bytes, cudaMemcpyDeviceToHost));
|
||||
}
|
||||
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
// Inspectors
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
/**
|
||||
* Return the height of the matrix, subject to the optional \p transpose_op
|
||||
*/
|
||||
int height(matrix_transform_t transpose_op = matrix_transform_t::NonTranspose) const
|
||||
{
|
||||
switch (transpose_op)
|
||||
{
|
||||
case matrix_transform_t::NonTranspose : return _m;
|
||||
case matrix_transform_t::Transpose : return _n;
|
||||
default: return -1;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Return the width of the matrix, subject to the optional \p transpose_op
|
||||
*/
|
||||
int width(matrix_transform_t transpose_op = matrix_transform_t::NonTranspose) const
|
||||
{
|
||||
switch (transpose_op)
|
||||
{
|
||||
case matrix_transform_t::NonTranspose : return _n;
|
||||
case matrix_transform_t::Transpose : return _m;
|
||||
default: return -1;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Return item at (x, y) coordinate of matrix, subject to the optional \p transform op
|
||||
*/
|
||||
host_value_t get(
|
||||
int x,
|
||||
int y,
|
||||
matrix_transform_t transpose_op = matrix_transform_t::NonTranspose) const
|
||||
{
|
||||
switch (transpose_op)
|
||||
{
|
||||
case matrix_transform_t::NonTranspose : return _h_data[y + (x * _m)];
|
||||
case matrix_transform_t::Transpose : return _h_data[x + (y * _m)];
|
||||
default: return 0;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Return the distance (in items) within memory between elements of two
|
||||
* consecutive columns which have the same row index, subject to the optional \p transform op
|
||||
*/
|
||||
int leading_dim(matrix_transform_t transpose_op = matrix_transform_t::NonTranspose) const
|
||||
{
|
||||
switch (transpose_op)
|
||||
{
|
||||
case matrix_transform_t::NonTranspose : return _m;
|
||||
case matrix_transform_t::Transpose : return _n;
|
||||
default: return 0;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get host data pointer
|
||||
*/
|
||||
value_t* h_data()
|
||||
{
|
||||
return _h_data.data();
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Get host data pointer
|
||||
*/
|
||||
value_t const* h_data() const
|
||||
{
|
||||
return _h_data.data();
|
||||
}
|
||||
|
||||
/**
|
||||
* Get device data pointer
|
||||
*/
|
||||
value_t const* d_data() const
|
||||
{
|
||||
return _d_data;
|
||||
}
|
||||
|
||||
/**
|
||||
* Get device data pointer
|
||||
*/
|
||||
value_t * d_data()
|
||||
{
|
||||
return _d_data;
|
||||
}
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
// Initialization
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
/**
|
||||
* Initialize matrix values with a 2D "ramp" defined as
|
||||
* <tt>values(x, y) = (y * rs) + (x * cs)</tt>
|
||||
*/
|
||||
void fill_ramp(
|
||||
host_value_t rs,
|
||||
host_value_t cs)
|
||||
{
|
||||
for (int x = 0; x < _n; x++)
|
||||
{
|
||||
for (int y = 0; y < _m; y++)
|
||||
{
|
||||
_h_data[y + (x * _m)] = host_value_t((y * rs) + (x * cs));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Initialize matrix values such that all the elements of the principal diagonal
|
||||
* are ones and all other elements are zeros
|
||||
*/
|
||||
void fill_identity()
|
||||
{
|
||||
for (int j = 0; j < _n; j++)
|
||||
{
|
||||
for (int i = 0; i < _m; i++)
|
||||
{
|
||||
_h_data[i + j * _m] = host_value_t(i == j ? 1 : 0);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Initialize matrix values using the random number \p generator. The
|
||||
* \p generator reference is assumed to be a nullary functor that returns
|
||||
* values convertible to the matrix \p value_t.
|
||||
*/
|
||||
template <typename T>
|
||||
void fill_random(T & generator)
|
||||
{
|
||||
for (int j = 0; j < _n; j++)
|
||||
{
|
||||
for (int i = 0; i < _m; i++)
|
||||
{
|
||||
_h_data[i + j * _m] = (value_t) generator();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Element-wise matrix addition
|
||||
*/
|
||||
matrix & operator+=(matrix const &mat)
|
||||
{
|
||||
for (int j = 0; j < _n; j++)
|
||||
{
|
||||
for (int i = 0; i < _m; i++)
|
||||
{
|
||||
_h_data[i + j * _m] += mat._h_data[i + j * _m];
|
||||
}
|
||||
}
|
||||
return *this;
|
||||
}
|
||||
|
||||
/**
|
||||
* Element-wise matrix subtraction
|
||||
*/
|
||||
matrix & operator-=(matrix const &mat)
|
||||
{
|
||||
for (int j = 0; j < _n; j++)
|
||||
{
|
||||
for (int i = 0; i < _m; i++)
|
||||
{
|
||||
_h_data[i + j * _m] -= mat._h_data[i + j * _m];
|
||||
}
|
||||
}
|
||||
return *this;
|
||||
}
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
// Output
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
/**
|
||||
* Prints matrix in CSV to output stream
|
||||
*/
|
||||
template <typename _hv_t>
|
||||
std::ostream & write_matrix(std::ostream &out, _hv_t)
|
||||
{
|
||||
for (int i = 0; i < _m; i++)
|
||||
{
|
||||
for (int j = 0; j < _n; j++)
|
||||
{
|
||||
out << (j ? "," : "") << _h_data[i + j * _m];
|
||||
}
|
||||
out << "\n";
|
||||
}
|
||||
return out;
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Prints matrix in CSV to output stream
|
||||
*/
|
||||
std::ostream & write_matrix(std::ostream &out, int8_t)
|
||||
{
|
||||
for (int i = 0; i < _m; i++)
|
||||
{
|
||||
for (int j = 0; j < _n; j++)
|
||||
{
|
||||
out << (j ? "," : "") << int32_t(_h_data[i + j * _m]);
|
||||
}
|
||||
out << "\n";
|
||||
}
|
||||
return out;
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Prints matrix in CSV to output stream
|
||||
*/
|
||||
std::ostream & write_matrix(std::ostream &out)
|
||||
{
|
||||
return write_matrix(out, _h_data[0]);
|
||||
}
|
||||
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
// Floating point "almost-equal" utilities
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
static bool almost_equal_ulps(half_t a, half_t b, int max_ulps)
|
||||
{
|
||||
if (a == b)
|
||||
return true;
|
||||
|
||||
int32_t int_diff = abs(a.raw() - b.raw());
|
||||
if (int_diff <= max_ulps)
|
||||
return true;
|
||||
return false;
|
||||
}
|
||||
|
||||
|
||||
static bool almost_equal_ulps(float a, float b, int max_ulps)
|
||||
{
|
||||
if (a == b)
|
||||
return true;
|
||||
int32_t int_diff = abs(*(int32_t*)&a - *(int32_t*)&b);
|
||||
if (int_diff <= max_ulps)
|
||||
return true;
|
||||
return false;
|
||||
}
|
||||
|
||||
|
||||
static bool almost_equal_ulps(double a, double b, int max_ulps)
|
||||
{
|
||||
if (a == b)
|
||||
return true;
|
||||
int64_t int_diff = abs(*(int64_t*)&a - *(int64_t*)&b);
|
||||
if (int_diff <= max_ulps)
|
||||
return true;
|
||||
return false;
|
||||
}
|
||||
|
||||
static bool almost_equal_ulps(int32_t a, int32_t b, int max_ulps)
|
||||
{
|
||||
return (a == b);
|
||||
}
|
||||
|
||||
|
||||
//-----------------------------------------------------------------------------
|
||||
// matrix operations
|
||||
//-----------------------------------------------------------------------------
|
||||
|
||||
|
||||
/**
|
||||
* Returns matrix equality
|
||||
*/
|
||||
bool operator==(const matrix<value_t> &mat) const
|
||||
{
|
||||
int max_ulps = 30;
|
||||
|
||||
if (_m != mat._m || _n != mat._n)
|
||||
{
|
||||
fprintf(stderr, "Error: dimension mismatch during matrix comparison.\n"); exit(1);
|
||||
}
|
||||
|
||||
for (int j = 0; j < _n; j++)
|
||||
{
|
||||
for (int i = 0; i < _m; i++)
|
||||
{
|
||||
if (!almost_equal_ulps(_h_data[i + j * _m], mat._h_data[i + j * _m], max_ulps))
|
||||
{
|
||||
return false;
|
||||
}
|
||||
}
|
||||
}
|
||||
return true;
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Returns matrix inequality
|
||||
*/
|
||||
bool operator!=(const matrix<value_t> &mat) const
|
||||
{
|
||||
return !(*this == mat);
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Computes this = (alpha * op(A) * op(B)) + (beta * this), specialized for gemm_nn
|
||||
*/
|
||||
template <typename multiplicand_t>
|
||||
void gemm(
|
||||
matrix_transform_t transform_a,
|
||||
matrix_transform_t transform_b,
|
||||
host_value_t alpha,
|
||||
const matrix<multiplicand_t> &A,
|
||||
const matrix<multiplicand_t> &B,
|
||||
host_value_t beta)
|
||||
{
|
||||
// Sanity check dimensions
|
||||
if ((_m != A.height(transform_a)) ||
|
||||
(_n != B.width(transform_b)) ||
|
||||
(A.width(transform_a) != B.height(transform_b)))
|
||||
{
|
||||
fprintf(stderr, "Error: dimension mismatch during gemm.\n");
|
||||
exit(1);
|
||||
}
|
||||
|
||||
int M = A.height(transform_a);
|
||||
int K = A.width(transform_a);
|
||||
int N = B.width(transform_b);
|
||||
|
||||
// Even the host-side implementation utilizes a blocking structure to improve
|
||||
// verification performance
|
||||
int DimBlockM = (M % 16 == 0) ? 16 : 1;
|
||||
int DimBlockN = (N % 16 == 0) ? 16 : 1;
|
||||
|
||||
for (int i = 0; i < M; i += DimBlockM)
|
||||
{
|
||||
for (int j = 0; j < N; j += DimBlockN)
|
||||
{
|
||||
for (int block_y = 0; block_y < DimBlockM; block_y++)
|
||||
{
|
||||
for (int block_x = 0; block_x < DimBlockN; block_x++)
|
||||
{
|
||||
int y = i + block_y;
|
||||
int x = j + block_x;
|
||||
|
||||
host_value_t accum(0);
|
||||
for (int k = 0; k < K; k++)
|
||||
{
|
||||
accum += host_value_t(A.get(k, y, transform_a)) * host_value_t(B.get(x, k, transform_b));
|
||||
}
|
||||
|
||||
_h_data[y + x * M] = (alpha * accum) + (beta * _h_data[y + x * M]);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
} // namespace cutlass
|
||||
@@ -0,0 +1,99 @@
|
||||
/******************************************************************************
|
||||
* Copyright (c) 2011-2017, NVIDIA CORPORATION. All rights reserved.
|
||||
*
|
||||
* Redistribution and use in source and binary forms, with or without
|
||||
* modification, are not permitted.
|
||||
*
|
||||
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
|
||||
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
|
||||
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
||||
* DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
|
||||
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
|
||||
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
|
||||
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
|
||||
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
||||
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
|
||||
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
||||
*
|
||||
******************************************************************************/
|
||||
|
||||
#pragma once
|
||||
|
||||
/**
|
||||
* \file
|
||||
* GPU kernel timer
|
||||
*/
|
||||
|
||||
#include <cuda_runtime.h>
|
||||
|
||||
#include <cutlass/util/debug.h>
|
||||
|
||||
namespace cutlass {
|
||||
|
||||
|
||||
/******************************************************************************
|
||||
* gpu_timer
|
||||
******************************************************************************/
|
||||
|
||||
/**
|
||||
* GPU event-based timer
|
||||
*/
|
||||
struct gpu_timer
|
||||
{
|
||||
cudaEvent_t _start;
|
||||
cudaEvent_t _stop;
|
||||
|
||||
gpu_timer()
|
||||
{
|
||||
CUDA_PERROR_EXIT(cudaEventCreate(&_start));
|
||||
CUDA_PERROR_EXIT(cudaEventCreate(&_stop));
|
||||
}
|
||||
|
||||
~gpu_timer()
|
||||
{
|
||||
CUDA_PERROR_EXIT(cudaEventDestroy(_start));
|
||||
CUDA_PERROR_EXIT(cudaEventDestroy(_stop));
|
||||
}
|
||||
|
||||
void start()
|
||||
{
|
||||
CUDA_PERROR_EXIT(cudaEventRecord(_start, 0));
|
||||
}
|
||||
|
||||
void stop()
|
||||
{
|
||||
CUDA_PERROR_EXIT(cudaEventRecord(_stop, 0));
|
||||
}
|
||||
|
||||
float elapsed_millis()
|
||||
{
|
||||
float elapsed = 0.0;
|
||||
CUDA_PERROR_EXIT(cudaEventSynchronize(_stop));
|
||||
CUDA_PERROR_EXIT(cudaEventElapsedTime(&elapsed, _start, _stop));
|
||||
return elapsed;
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
/******************************************************************************
|
||||
* sleep_millis
|
||||
******************************************************************************/
|
||||
|
||||
#ifdef _WIN32
|
||||
#include <windows.h>
|
||||
|
||||
void sleep_millis(unsigned milliseconds)
|
||||
{
|
||||
Sleep(milliseconds);
|
||||
}
|
||||
#else
|
||||
#include <unistd.h>
|
||||
|
||||
void sleep_millis(unsigned milliseconds)
|
||||
{
|
||||
usleep(milliseconds * 1000); // takes microseconds
|
||||
}
|
||||
#endif
|
||||
|
||||
|
||||
} // namespace cutlass
|
||||
@@ -0,0 +1,155 @@
|
||||
/******************************************************************************
|
||||
* Copyright (c) 2011-2017, NVIDIA CORPORATION. All rights reserved.
|
||||
*
|
||||
* Redistribution and use in source and binary forms, with or without
|
||||
* modification, are not permitted.
|
||||
*
|
||||
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
|
||||
* ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
|
||||
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
||||
* DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE FOR ANY
|
||||
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
|
||||
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
|
||||
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
|
||||
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
||||
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
|
||||
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
||||
*
|
||||
******************************************************************************/
|
||||
|
||||
#pragma once
|
||||
|
||||
/**
|
||||
* \file
|
||||
* \brief Utilities for converting between types and assessing traits
|
||||
*/
|
||||
|
||||
#include "half.h"
|
||||
|
||||
namespace cutlass {
|
||||
|
||||
/******************************************************************************
|
||||
* Float conversion utilities
|
||||
******************************************************************************/
|
||||
|
||||
/// Convert float to value type
|
||||
template <typename value_t>
|
||||
value_t from_float(float val)
|
||||
{
|
||||
return value_t(val);
|
||||
}
|
||||
|
||||
/// Convert float to value type (__half specialization)
|
||||
template <>
|
||||
__half from_float<__half>(float val)
|
||||
{
|
||||
return half_t(val);
|
||||
}
|
||||
|
||||
|
||||
/******************************************************************************
|
||||
* Type conversion utilities
|
||||
******************************************************************************/
|
||||
|
||||
/// Member \p type is defined as the signed integer type having the same size as \p T
|
||||
template <typename T>
|
||||
struct integer_alias;
|
||||
|
||||
template <>
|
||||
struct integer_alias<int8_t> {
|
||||
using type = int8_t;
|
||||
};
|
||||
|
||||
template <>
|
||||
struct integer_alias<half_t> {
|
||||
using type = int16_t;
|
||||
};
|
||||
|
||||
template <>
|
||||
struct integer_alias<__half> {
|
||||
using type = int16_t;
|
||||
};
|
||||
|
||||
template <>
|
||||
struct integer_alias<float> {
|
||||
using type = int32_t;
|
||||
};
|
||||
|
||||
template <>
|
||||
struct integer_alias<int> {
|
||||
using type = int32_t;
|
||||
};
|
||||
|
||||
template <>
|
||||
struct integer_alias<double> {
|
||||
using type = int64_t;
|
||||
};
|
||||
|
||||
|
||||
|
||||
/******************************************************************************
|
||||
* Type-info utilities
|
||||
******************************************************************************/
|
||||
|
||||
/// Returns a string to prefix 'gemm' to construct CUBLAS-like kernel names
|
||||
template <math_operation_class_t math_op, typename value_t, typename accum_t> char const *to_prefix_string();
|
||||
|
||||
template <> char const *to_prefix_string<math_operation_class_t::scalar, half_t, half_t>() {
|
||||
return "H";
|
||||
}
|
||||
|
||||
template <> char const *to_prefix_string<math_operation_class_t::scalar, __half, __half>() {
|
||||
return "H";
|
||||
}
|
||||
|
||||
template <> char const *to_prefix_string<math_operation_class_t::scalar, float, float>() {
|
||||
return "S";
|
||||
}
|
||||
|
||||
template <> char const *to_prefix_string<math_operation_class_t::matrix, __half, __half>() {
|
||||
return "WmmaH";
|
||||
}
|
||||
|
||||
template <> char const *to_prefix_string<math_operation_class_t::matrix, __half, float>() {
|
||||
return "WmmaS";
|
||||
}
|
||||
|
||||
template <> char const *to_prefix_string<math_operation_class_t::scalar, double, double>() {
|
||||
return "D";
|
||||
}
|
||||
|
||||
template <> char const *to_prefix_string<math_operation_class_t::scalar, int8_t, int32_t>() {
|
||||
return "I";
|
||||
}
|
||||
|
||||
|
||||
/******************************************************************************
|
||||
* Maps value_t to the minimum vector size used to load operand
|
||||
******************************************************************************/
|
||||
|
||||
template <typename T>
|
||||
struct operand_load_type;
|
||||
|
||||
template <>
|
||||
struct operand_load_type<int8_t> { using type = int32_t; };
|
||||
|
||||
template <typename T>
|
||||
struct operand_load_type { using type = T; };
|
||||
|
||||
|
||||
/******************************************************************************
|
||||
* Minimum alignment requirement, if any, determined from value_t.
|
||||
******************************************************************************/
|
||||
|
||||
template <typename value_t>
|
||||
struct gemm_alignment_requirement;
|
||||
|
||||
template <>
|
||||
struct gemm_alignment_requirement<uint8_t> { static const int value = 4; };
|
||||
|
||||
template <typename value_t>
|
||||
struct gemm_alignment_requirement { static const int value = 0; };
|
||||
|
||||
|
||||
|
||||
} // namespace cutlass
|
||||
Reference in New Issue
Block a user