Files
project_6/cccl_upstream/libcudacxx/test/support/hexfloat.h
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

58 lines
1.4 KiB
C++

//===----------------------------------------------------------------------===//
//
// Part of the LLVM Project, 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
//
//===----------------------------------------------------------------------===//
// Define a hexfloat literal emulator since we can't depend on being able to
// for hexfloat literals
// 0x10.F5p-10 == hexfloat<double>(0x10, 0xF5, -10)
#ifndef HEXFLOAT_H
#define HEXFLOAT_H
#include <climits>
#include <cmath>
template <class T>
class hexfloat
{
T value_;
static int CountLeadingZeros(unsigned long long n)
{
const std::size_t Digits = sizeof(unsigned long long) * CHAR_BIT;
const unsigned long long TopBit = 1ull << (Digits - 1);
if (n == 0)
{
return Digits;
}
int LeadingZeros = 0;
while ((n & TopBit) == 0)
{
++LeadingZeros;
n <<= 1;
}
return LeadingZeros;
}
public:
hexfloat(long long m1, unsigned long long m0, int exp)
{
const std::size_t Digits = sizeof(unsigned long long) * CHAR_BIT;
int s = m1 < 0 ? -1 : 1;
int exp2 = -static_cast<int>(Digits - CountLeadingZeros(m0) / 4 * 4);
value_ = std::ldexp(m1 + s * std::ldexp(T(m0), exp2), exp);
}
operator T() const
{
return value_;
}
};
#endif