论文标题
评估应用程序功能块的自动GPU和FPGA卸载
Evaluation of Automatic GPU and FPGA Offloading for Function Blocks of Applications
论文作者
论文摘要
近年来，与CPU相比，使用FPGA的系统由于其优势（例如功率效率）而增加。但是，在诸如FPGA和GPU之类的系统中使用需要了解特定于硬件的技术规格，例如HDL和CUDA，这是一个很高的障碍。基于此背景，我以前提出了可以根据要放置的硬件进行自动转换，配置和高性能操作的自动环境自适应软件。作为概念的一个元素，我提出了一种方法，可以自动将CPU应用程序源代码的循环语句转换为FPGA和GPU。在本文中，我提出并评估一种卸载功能块的方法，该功能块是一个较大的单元，而不是应用程序中的单个循环语句，以通过自动卸载到GPU和FPGA来实现更高的速度。我实施了提出的方法，并通过现有应用程序卸载到GPU进行评估。
In the recent years, systems using FPGAs, GPUs have increased due to their advantages such as power efficiency compared to CPUs. However, use in systems such as FPGAs and GPUs requires understanding hardware-specific technical specifications such as HDL and CUDA, which is a high hurdle. Based on this background, I previously proposed environment adaptive software that enables automatic conversion, configuration, and high-performance operation of once written code according to the hardware to be placed. As an element of the concept, I proposed a method to automatically offload loop statements of application source code for CPU to FPGA and GPU. In this paper, I propose and evaluate a method for offloading a function block, which is a larger unit, instead of individual loop statements in an application, to achieve higher speed by automatic offloading to GPU and FPGA. I implement the proposed method and evaluate with existing applications offloading to GPU.
