使用商品图形处理器的vspl++加速

D. Campbell
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引用次数: 6

摘要

高性能嵌入式计算软件计划(HPEC-SI)正在开发用于并行计算机上高性能信号处理任务的计算和通信的统一软件框架。该计划的目标是通过提高信号处理应用开发的可移植性和生产力,同时提高与当前实践相比的性能,解决国防部(DoD)系统中软件的高成本问题。矢量、信号和图像处理库(VSIPL)是一种便携式应用程序编程接口(API),广泛用于嵌入式国防部信号处理系统。HPEC-SI工作的一部分包括为现有的VSIPL标准开发c++扩展,称为VSIPL++。商品图形处理单元(gpu)是特定于应用程序的处理器,它实现了标准化的三维图形呈现管道,与通用处理器相比,它以更低的成本、功耗和物理空间提供了重要的浮点处理能力。gpu最近的变化增加了部分渲染管道的可编程性和灵活性,允许非图形应用程序利用其计算能力。编程模型的限制、缺乏适当的工具、异常的性能行为和其他因素使得应用程序开发人员开发gpu成为一个昂贵、困难和耗时的过程。常用的VSIPL和VSIPL++的嵌入式系统具有gpu的几个重要特性,使得VSIPL++非常适合对gpu进行抽象和开发。本文描述了gpuvsipl++,它是vsipl++标准部分的实现,它利用GPU来加速计算,超越了开发工作站的能力
本文章由计算机程序翻译,如有差异,请以英文原文为准。
VSIPL++ Acceleration Using Commodity Graphics Processors
The High Performance Embedded Computing Software Initiative (HPEC-SI) is developing a unified software framework for computation and communication for high performance signal processing tasks on parallel computers. The goal of the program is to address the high cost of software in Department of Defense (DoD) systems by improving the portability and productivity of signal processing application development, while simultaneously improving performance compared to current practices. The Vector, Signal, and Image Processing Library (VSIPL) is a portable application programming interface (API) that is widely used for embedded DoD signal processing systems. One portion of the HPEC-SI effort includes the development of C++ extensions for the existing VSIPL standard, called VSIPL++. Commodity graphics processing units (GPUs) are application-specific processors that implement a standardized three-dimensional graphics-rendering pipeline, and provide significant floating-point processing capacity at much lower cost, power consumption, and physical space compared to general-purpose processors. Recent changes in GPUs have increased programmability and flexibility in portions of the rendering pipeline, allowing non-graphics applications to exploit their computational capacity. Restrictions on the programming model, lack of appropriate tools, unusual performance behavior, and other factors make exploiting GPUs a costly, difficult, and time-consuming process for application developers. The embedded systems that VSIPL and VSIPL++ are commonly used on share several important characteristics with GPUs, making VSIPL++ well suited to abstract and exploit GPUs. This paper describes GPUVSIPL++, an implementation of portions of the VSIPL++ standard that exploits a GPU to accelerate computation beyond what is possible on a development workstation
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