利用类星体实现gpu加速的实时机器视觉

Jonas De Vylder, S. Donné, D. V. Haerenborgh, B. Goossens
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引用次数: 1

摘要

图形处理单元(gpu)的计算性能得到了显著改善,与单线程CPU执行相比,实现10 -50倍的加速系数并不少见。这使得它们用于高吞吐量机器视觉非常有吸引力。然而,GPU编程是具有挑战性的,需要大量的编程专业知识。我们提出了一个新的编程框架,减轻了GPU编程的常见挑战,同时保持了显著的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time Machine Vision with GPU-acceleration using Quasar
The computational performance of graphical processing units (GPUs) has improved significantly, achieving even speed-up factors of 10x-50x compared to single-threaded CPU execution are not uncommon. This makes their use for high throughput machine vision very appealing. However, GPU programming is challenging, requiring a significant programming expertise. We present a new programming framework that mitigates the challenges common for GPU programming while maintaining the significant acceleration.
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