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project_6/cccl_upstream/cudax/test/execution/test_trampoline_scheduler.cu
EngineX CI 56fd68e7dd [INFRA] Import NVIDIA/CCCL upstream as optimization reference library
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
2026-07-30 09:35:51 +00:00

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//===----------------------------------------------------------------------===//
//
// Part of CUDA Experimental in CUDA C++ Core Libraries,
// under the Apache License v2.0 with LLVM Exceptions.
// See https://llvm.org/LICENSE.txt for license information.
// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
// SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES.
//
//===----------------------------------------------------------------------===//
#include <cuda/experimental/execution.cuh>
#include "./common/retry.cuh"
#include "testing.cuh"
namespace ex = ::cuda::experimental::execution;
#if !_CCCL_DEVICE_COMPILATION()
namespace
{
struct try_again
{};
class fails_alot
{
template <class Receiver>
struct operation;
public:
using sender_concept = ex::sender_t;
fails_alot() = default;
__host__ fails_alot(fails_alot&& other) noexcept
: counter_(std::move(other.counter_))
{}
__host__ fails_alot(const fails_alot& other) noexcept
: counter_(other.counter_)
{}
template <class Receiver>
[[nodiscard]] auto connect(Receiver rcvr) const noexcept -> operation<Receiver>
{
return operation<Receiver>{static_cast<Receiver&&>(rcvr), --*counter_};
}
template <class...>
static _CCCL_CONSTEVAL auto get_completion_signatures() noexcept
{
return ex::completion_signatures<ex::set_value_t(), ex::set_error_t(try_again)>{};
}
private:
template <class Receiver>
struct operation
{
void start() & noexcept
{
if (counter_ == 0)
{
ex::set_value(static_cast<Receiver&&>(rcvr_));
}
else
{
ex::set_error(static_cast<Receiver&&>(rcvr_), try_again{});
}
}
Receiver rcvr_;
int counter_;
};
std::shared_ptr<int> counter_ = std::make_shared<int>(1'000'000);
};
// #if defined(REQUIRE_TERMINATE)
// // For some reason, when compiling with nvc++, the forked process dies with SIGSEGV
// // but the error code returned from ::wait reports success, so this test fails.
// TEST_CASE("running deeply recursing algo blows the stack", "[schedulers][trampoline_scheduler]") {
// auto recurse_deeply = retry(fails_alot{});
// REQUIRE_TERMINATE([&] { sync_wait(std::move(recurse_deeply)); });
// }
// #endif
TEST_CASE("running deeply recursing algo on trampoline_scheduler doesn't blow the stack",
"[scheduler][trampoline_scheduler]")
{
ex::trampoline_scheduler sched;
auto recurse_deeply = retry(ex::on(sched, fails_alot{}));
ex::sync_wait(std::move(recurse_deeply));
}
} // namespace
#endif // !_CCCL_DEVICE_COMPILATION()