We present a way to implement term rewriting on a GPU. We do this by letting the GPU repeatedly perform a massively parallel evaluation of all subterms. We find that if the term rewrite systems exhibit sufficient internal parallelism, GPU rewriting substantially outperforms the CPU. Since we expect that our implementation can be further optimized, and because in any case GPUs will become much more powerful in the future, this suggests that GPUs are an interesting platform for term rewriting. As term rewriting can be viewed as a universal programming language, this also opens a route towards programming GPUs by term rewriting, especially for irregular computations.

中文翻译：

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GPU 上的术语重写

我们提出了一种在 GPU 上实现术语重写的方法。我们通过让 GPU 重复执行对所有子项的大规模并行评估来做到这一点。我们发现，如果术语重写系统表现出足够的内部并行性，则 GPU 重写的性能大大优于 CPU。由于我们希望我们的实现可以进一步优化，而且无论如何 GPU 在未来都会变得更加强大，这表明 GPU 是一个有趣的术语重写平台。由于术语重写可以被视为一种通用编程语言，这也为通过术语重写对 GPU 进行编程开辟了道路，尤其是对于不规则计算。