We present a new approach to searching for Continuous gravitational Waves (CWs) emitted by isolated rotating neutron stars, using the high parallel computing efficiency and computational power of modern Graphic Processing Units (GPUs). Specifically, in this paper the porting of one of the algorithms used to search for CW signals, the so-called FrequencyHough transform, on the TensorFlow framework, is described. The new code has been fully tested and its performance on GPUs has been compared to those in a CPU multicore system of the same class, showing a factor of 10 speed-up. This demonstrates that GPU programming with general purpose libraries (the those of the TensorFlow framework) of a high-level programming language can provide a significant improvement of the performance of data analysis, opening new perspectives on wide-parameter searches for CWs.

中文翻译：

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在图形处理单元上使用通用计算进行连续引力波数据分析

我们提出了一种使用现代图形处理单元 (GPU) 的高并行计算效率和计算能力来搜索孤立旋转中子星发出的连续引力波 (CW) 的新方法。具体而言，本文介绍了在 TensorFlow 框架上移植用于搜索 CW 信号的算法之一，即所谓的 FrequencyHough 变换。新代码已经过全面测试，其在 GPU 上的性能与同类 CPU 多核系统中的性能进行了比较，显示速度提高了 10 倍。这表明使用高级编程语言的通用库（TensorFlow 框架的库）进行 GPU 编程可以显着提高数据分析的性能，