FPGA Accelerated Computing Platform for MATLAB and C/C++

Rizwan Rasul, Abdul Mutaal, N. Saqib, Mohammad Kaleem, A. Shaukat, Aasia Khanum, M. Khan
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引用次数: 5

Abstract

With latest advancements in architecture, reprogram ability and availability of abundant on-chip resources, FPGAs (Field Programmable Gate Array) are used as hardware accelerators to speedup computationally intensive tasks with inherent parallelism. However non-availability of standard MATLAB and C/C++ computation routines and communication interface for general purpose programming restricted researchers and developers from easily utilizing the parallel computational ability of FPGAs in MATLAB and C/C++. In this article we propose a proof of concept implementation for software-hardware co-design that can be used with MATLAB and C/C++ to share the burden of intensified computing with the FPGA. Typical applications which can be divided into multiple tasks to be executed in parallel can be easily transferred to FPGA by utilizing the proposed method. Some of the applications which can efficiently use this concept are image processing, video processing, data encryption and data compression. Results obtained by using our method and routines implemented in software and hardware provide 50% to 100% computational acceleration, as compared to routines running in software on MATLAB running on a computer. The design and concept can aid developers to use FPGAs in combination with higher level computational languages such as MATLAB and C/C++.
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FPGA加速计算平台的MATLAB和C/ c++
随着体系结构、可重编程能力和丰富的片上资源的最新发展,fpga(现场可编程门阵列)被用作硬件加速器来加速具有固有并行性的计算密集型任务。然而,由于缺乏标准的MATLAB和C/ c++计算例程和通用编程的通信接口,研究人员和开发人员无法轻松利用MATLAB和C/ c++中fpga的并行计算能力。在本文中,我们提出了一个软硬件协同设计的概念验证实现,它可以与MATLAB和C/ c++一起使用,与FPGA一起分担强化计算的负担。典型的应用程序可以分为多个并行执行的任务,可以很容易地通过利用所提出的方法转移到FPGA。图像处理、视频处理、数据加密和数据压缩等应用都可以有效地利用这一概念。与在计算机上运行的MATLAB软件中运行的例程相比,使用我们的方法获得的结果和在软件和硬件中实现的例程提供了50%到100%的计算加速。该设计和概念可以帮助开发人员将fpga与更高级别的计算语言(如MATLAB和C/ c++)结合使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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