56fd68e7dd
CCCL (CUDA C++ Core Libraries) provides: - CUB: device/block/warp-level GPU primitives (reduce, scan, sort, topk) - Thrust: high-level parallel algorithms (transform_reduce, sort, scan) - libcudacxx: CUDA C++ standard library (atomics, barriers, memory) - cudax: experimental features (memory resources, allocators) - Tuning policies: per-SM hardware-specific algorithm parameters Competition optimization vectors mapped to CCCL: - Output TPS (83% weight): warp_reduce, block_reduce, device_topk - Input TPS (14% weight): device_scan, block_load, prefetch - Cache TPS (3% weight): prefix caching strategy patterns - Memory (0.9 util): pooled/cached/buddy allocators Source: https://github.com/NVIDIA/cccl (shallow clone, HEAD only) License: Apache-2.0
87 lines
2.2 KiB
C++
87 lines
2.2 KiB
C++
//===----------------------------------------------------------------------===//
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//
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// Part of CUDA Experimental in CUDA C++ Core Libraries,
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// under the Apache License v2.0 with LLVM Exceptions.
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// See https://llvm.org/LICENSE.txt for license information.
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// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
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// SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES.
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//
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//===----------------------------------------------------------------------===//
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#pragma once
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#include <cstdio>
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#include <format>
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#include <memory>
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#include <utility>
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#include <nvrtc/nvjitlink_helper.h>
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#include <util/errors.h>
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// Links LTO-IR blobs via nvJitLink → returns SASS cubin (PTX fallback if SASS unavailable).
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// Caller owns the returned buffer.
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[[nodiscard]] inline std::pair<std::unique_ptr<char[]>, size_t>
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nvjitlink_link(const void** blobs, const size_t* sizes, size_t num, int cc_major, int cc_minor)
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{
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const std::string arch = std::format("-arch=sm_{}{}", cc_major, cc_minor);
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const char* lopts[] = {"-lto", arch.c_str()};
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nvJitLinkHandle h{};
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check(nvJitLinkCreate(&h, 2, lopts));
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auto cleanup = [&]() {
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if (h)
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{
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nvJitLinkDestroy(&h);
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h = nullptr;
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}
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};
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try
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{
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for (size_t i = 0; i < num; ++i)
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{
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if (blobs[i] && sizes[i] > 0)
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{
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check(nvJitLinkAddData(h, NVJITLINK_INPUT_ANY, blobs[i], sizes[i], "serialization_input"));
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}
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}
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auto rc = nvJitLinkComplete(h);
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size_t log_size = 0;
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check(nvJitLinkGetErrorLogSize(h, &log_size));
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if (log_size > 1)
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{
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auto log = std::make_unique<char[]>(log_size);
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check(nvJitLinkGetErrorLog(h, log.get()));
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fprintf(stderr, "%s\n", log.get());
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}
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check(rc);
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size_t cubin_size = 0;
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bool use_ptx = (nvJitLinkGetLinkedCubinSize(h, &cubin_size) != NVJITLINK_SUCCESS);
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if (use_ptx)
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{
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check(nvJitLinkGetLinkedPtxSize(h, &cubin_size));
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}
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auto cubin = std::make_unique<char[]>(cubin_size);
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if (use_ptx)
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{
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check(nvJitLinkGetLinkedPtx(h, cubin.get()));
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}
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else
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{
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check(nvJitLinkGetLinkedCubin(h, cubin.get()));
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}
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cleanup();
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return {std::move(cubin), cubin_size};
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}
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catch (...)
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{
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cleanup();
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throw;
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}
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}
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