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Performance Analysis Framework for High-Level Language Applications in Reconfigurable Computing

机译:可重构计算中高级语言应用程序的性能分析框架

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摘要

High-Level Languages (HLLs) for Field-Programmable Gate Arrays (FPGAs) facilitate the use of reconfigurable computing resources for application developers by using familiar, higher-level syntax, semantics, and abstractions, typically enabling faster development times than with traditional Hardware Description Languages (HDLs). However, programming at a higher level of abstraction is typically accompanied by some loss of performance as well as reduced transparency of application behavior, making it difficult to understand and improve application performance. While runtime tools for performance analysis are often featured in development with traditional HLLs for sequential and parallel programming, HLL-based development for FPGAs has an equal or greater need yet lacks these tools. This article presents a novel and portable framework for runtime performance analysis of HLL applications for FPGAs, including an automated tool for performance analysis of designs created with Impulse C, a commercial HLL for FPGAs. As a case study, this tool is used to successfully locate performance bottlenecks in a molecular dynamics kernel in order to gain speedup.
机译:现场可编程门阵列(FPGA)的高级语言(HLL)通过使用熟悉的高级语法,语义和抽象,为应用程序开发人员促进了可重配置计算资源的使用,与传统的硬件描述相比,通常可缩短开发时间语言(HDL)。但是,在较高抽象级别进行编程通常会伴随一些性能损失,并降低应用程序行为的透明度,从而难以理解和提高应用程序性能。尽管用于性能分析的运行时工具通常是在具有用于顺序和并行编程的传统HLL的开发中使用的,但是针对FPGA的基于HLL的开发具有同等或更大的需求,但缺少这些工具。本文介绍了一种新颖且可移植的框架,用于FPGA HLL应用程序的运行时性能分析,其中包括一个自动化工具,用于对使用FPGA商业HLL Impulse C创建的设计进行性能分析。作为案例研究,该工具可用于成功定位分子动力学内核中的性能瓶颈,从而提高速度。

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