chore: import upstream snapshot with attribution
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// Copyright (c) Microsoft Corporation.
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// SPDX-License-Identifier: Apache-2.0
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// DeepSpeed Team
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/*
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Functionality for swapping optimizer tensors to/from (NVMe) storage devices.
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*/
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#include <assert.h>
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#include <stdlib.h>
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#include <string.h>
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#include <fcntl.h>
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#include <sys/mman.h>
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#include <sys/stat.h>
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#include <sys/types.h>
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#include <unistd.h>
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#include <cassert>
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#include <chrono>
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#include <cstring>
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#include <fstream>
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#include <iostream>
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#include <memory>
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#include <string>
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#include <vector>
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#include "deepspeed_py_aio.h"
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using namespace std;
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using namespace std::chrono;
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#define DEBUG_DS_AIO_READ 0
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#define DEBUG_DS_AIO_WRITE 0
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static const std::string c_library_name = "deepspeed_aio";
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int deepspeed_py_aio_write(const torch::Tensor& buffer,
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const char* filename,
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const int block_size,
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const int queue_depth,
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const bool single_submit,
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const bool overlap_events,
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const bool validate)
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{
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const auto start_time = std::chrono::high_resolution_clock::now();
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deepspeed_aio_config_t config(block_size, queue_depth, single_submit, overlap_events, false);
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const auto fd = open_file(filename, false);
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if (fd == -1) { return -1; }
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auto write_buffer = (char*)buffer.data_ptr();
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const auto num_write_bytes = static_cast<int64_t>(buffer.nbytes());
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std::unique_ptr<io_xfer_ctxt> xfer_ctxt(
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new io_xfer_ctxt(fd, 0, 0, num_write_bytes, write_buffer));
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std::unique_ptr<aio_context> aio_ctxt(new aio_context(config._block_size, config._queue_depth));
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if (config._overlap_events) {
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do_aio_operation_overlap(false, aio_ctxt, xfer_ctxt, &config, nullptr);
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} else {
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do_aio_operation_sequential(false, aio_ctxt, xfer_ctxt, &config, nullptr);
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}
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const std::chrono::duration<double> aio_time =
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std::chrono::high_resolution_clock::now() - start_time;
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close(fd);
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if (validate) { validate_aio_operation(false, filename, write_buffer, num_write_bytes); }
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const std::chrono::duration<double> fn_time =
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std::chrono::high_resolution_clock::now() - start_time;
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std::cout << "Elapsed time(usec): " << "aio = " << aio_time.count() * 1e6
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<< " call = " << fn_time.count() * 1e6 << std::endl;
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return 0;
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}
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int deepspeed_py_aio_read(torch::Tensor& buffer,
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const char* filename,
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const int block_size,
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const int queue_depth,
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const bool single_submit,
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const bool overlap_events,
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const bool validate)
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{
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const auto start_time = std::chrono::high_resolution_clock::now();
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int64_t num_file_bytes;
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if (-1 == get_file_size(filename, num_file_bytes)) {
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const auto error_code = errno;
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report_file_error(filename, " fstat for read", error_code);
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return -1;
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}
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deepspeed_aio_config_t config(block_size, queue_depth, single_submit, overlap_events, false);
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const auto fd = open_file(filename, true);
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if (fd == -1) { return -1; }
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auto read_buffer = (char*)buffer.data_ptr();
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assert(static_cast<int64_t>(buffer.nbytes()) == num_file_bytes);
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std::unique_ptr<io_xfer_ctxt> xfer_ctxt(
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new io_xfer_ctxt(fd, 0, 0, num_file_bytes, read_buffer));
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std::unique_ptr<aio_context> aio_ctxt(new aio_context(config._block_size, config._queue_depth));
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if (config._overlap_events) {
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do_aio_operation_overlap(true, aio_ctxt, xfer_ctxt, &config, nullptr);
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} else {
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do_aio_operation_sequential(true, aio_ctxt, xfer_ctxt, &config, nullptr);
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}
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const std::chrono::duration<double> aio_time =
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std::chrono::high_resolution_clock::now() - start_time;
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close(fd);
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if (validate) { validate_aio_operation(true, filename, read_buffer, num_file_bytes); }
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const std::chrono::duration<double> fn_time =
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std::chrono::high_resolution_clock::now() - start_time;
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std::cout << "Elapsed time(usec): " << "aio = " << aio_time.count() * 1e6
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<< " call = " << fn_time.count() * 1e6 << std::endl;
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return 0;
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}
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