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The sequence-to-sequence (seq2seq) model for neural machine translation hassignificantly improved the accuracy of language translation. There have beennew efforts to use this seq2seq model for program language translation orprogram comparisons. In this work, we present the detailed steps of using aseq2seq model to translate CUDA programs to OpenCL programs, which both havevery similar programming styles. Our work shows (i) a training input setgeneration method, (ii) pre/post processing, and (iii) a case study usingPolybench-gpu-1.0, NVIDIA SDK, and Rodinia benchmarks.

A Case Study: Exploiting Neural Machine Translation to Translate CUDA to OpenCL