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
25 lines
626 B
Plaintext
25 lines
626 B
Plaintext
#include <thrust/detail/config.h>
|
|
|
|
#include <thrust/detail/caching_allocator.h>
|
|
|
|
#include <unittest/unittest.h>
|
|
|
|
template <typename Allocator>
|
|
void test_implementation(Allocator alloc)
|
|
{
|
|
using Traits = typename cuda::std::allocator_traits<Allocator>;
|
|
using Ptr = typename Allocator::pointer;
|
|
|
|
Ptr p = Traits::allocate(alloc, 123);
|
|
Traits::deallocate(alloc, p, 123);
|
|
|
|
Ptr p2 = Traits::allocate(alloc, 123);
|
|
ASSERT_EQUAL(p, p2);
|
|
}
|
|
|
|
void TestSingleDeviceTLSCachingAllocator()
|
|
{
|
|
test_implementation(thrust::detail::single_device_tls_caching_allocator());
|
|
};
|
|
DECLARE_UNITTEST(TestSingleDeviceTLSCachingAllocator);
|