fpga的迭代改进

Jun Kyu Lee, G. D. Peterson
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引用次数: 8

摘要

混合精度迭代细化的可实现精度取决于计算平台所支持的精度。尽管算术单元精度对于可编程逻辑计算架构(例如fpga)来说是灵活的,但以前的工作很少讨论由于实现灵活的可实现精度而带来的性能优势。因此,我们提出了一种fpga的迭代细化方法,该方法采用任意精度进行迭代细化以获得任意精度。我们在Xilinx XC5VLX110T上实现了单个处理元素,并将它们与Xilinx xc6vlx475t进行了性能评估。本文表明,当用户要求精度介于单精度和双精度之间时,其性能与NVIDIA GTX480相似,但实现也可以产生超越双精度的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Iterative Refinement on FPGAs
Achievable accuracy for mixed precision iterative refinement depends on the precisions supported by computing platforms. Even though the arithmetic unit precision can be flexible for programmable logic computing architectures (e.g. FPGAs), previous work rarely discusses the performance benefits due to enabling flexible achievable accuracy. Hence, we propose an iterative refinement approach on FPGAs which employs an arbitrary precision for the iterative refinement to obtain an arbitrary accuracy. We implement single processing elements for the refinement on the Xilinx XC5VLX110T and compare them to Xilinx XC6VSX475T for performance estimation. This paper shows that the performance is similar to the NVIDIA GTX480 when a user requires accuracies between single and double precision, but the implementation can also produce beyond double precision accuracy.
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