Accelerating Dedispersion Using Many-core Architectures
Accelerating Dedispersion Using Many-core Architectures
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DOI：
10.3847/1538-4365/acfef6
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发表时间：
2023-11
期刊：
影响因子：
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通讯作者：
Jan Novotný;Karel Adámek;M. A. Clark;Mike Giles;W. Armour
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文献类型：
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作者：
Jan Novotný;Karel Adámek;M. A. Clark;Mike Giles;W. Armour
天体物理学的无线电信号是探测发射它们的极端物理过程的极好探针。然而，为了到达地球，电磁辐射穿过电离的星际介质，对发射的信号引入频率依赖的时间延迟（色散）。消除色散可以搜索瞬态信号，如快速无线电爆发或来自孤立卫星或其他紧凑物体轨道上的重复信号。下一代射电望远镜将产生大量高分辨率的数据，这需要高性能的计算解决方案和算法用于时域数据处理管道，以真实的时间提取有科学价值的结果。本文介绍了一个国家的最先进的实施暴力的非相干去色散的NVIDIA图形处理单元和英特尔和AMD的中央处理单元。我们表明，我们的实现比其他可用的解决方案快4倍（8位8192通道输入），我们使用11个现有的望远镜证明，我们的实现比真实的时间至少快20倍。这项工作是AstroAccelerate软件包的一部分。
Astrophysical radio signals are excellent probes of extreme physical processes that emit them. However, to reach Earth, electromagnetic radiation passes through the ionized interstellar medium, introducing a frequency-dependent time delay (dispersion) to the emitted signal. Removing dispersion enables searches for transient signals like fast radio bursts or repeating signals from isolated pulsars or those in orbit around other compact objects. The sheer volume and high resolution of data that next-generation radio telescopes will produce require high-performance computing solutions and algorithms to be used in time-domain data-processing pipelines to extract scientifically valuable results in real time. This paper presents a state-of-the-art implementation of brute force incoherent dedispersion on NVIDIA graphics-processing units and on Intel and AMD central-processing units. We show that our implementation is 4× faster (8-bit 8192 channels input) than other available solutions, and we demonstrate, using 11 existing telescopes, that our implementation is at least 20× faster than real time. This work is part of the AstroAccelerate package.