近似硬件的快速架构模拟

Isaías B. Felzmann, M. M. Susin, Liana Duenha, R. Azevedo, L. Wanner
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引用次数: 3

摘要

最近的研究引入了一些近似的硬件单元,这些硬件单元对于一小部分输入会确定性地或概率地产生不正确的输出,但与没有错误的同类相比,它们具有更高的吞吐量或更低的功耗。然而,在体系结构和处理器中对这些近似单元的集成、验证和评估仍然具有挑战性。在本文中,我们介绍了一种用于描述、配置和将近似硬件单元集成到处理器中的高级语言ADeLe。ADeLe减少了近似硬件的设计工作量,通过在高抽象级别对近似进行建模,并自动将其注入处理器模型中进行架构模拟。ADeLe中的近似可以根据用户定义的策略修改或完全替换指令的功能行为。指令可以确定性地或概率地近似(例如,基于工作电压和频率)。为了允许控制测试,可以从软件中启用和禁用近似。根据可定制的模型自动计算能源,该模型考虑了系统中启用的近似的潜在节能。ADeLe为设计人员提供了一个通用而灵活的验证框架,使他们能够轻松评估其设计在应用中的能源质量权衡。我们通过在处理器模型中引入不同的近似技术来演示语言和相应的框架,并在其上运行选定的应用程序。我们使用6个近似设计,4个图像处理和2个浮点应用程序来演示ADeLe。我们的实验展示了如何使用ADeLe来生成近似cpu,并以更少的努力来评估不同应用程序的能源质量权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ADeLe: Rapid Architectural Simulation for Approximate Hardware
Recent research has introduced approximate hardware units that produce incorrect outputs deterministically or probabilistically for some small subset of inputs but allow significantly higher throughput or lower power than their errorfree counterparts. The integration, validation, and evaluation of these approximate units in architectures and processors, however, remains challenging. In this paper, we introduce ADeLe, a high-level language for the description, configuration, and integration of approximate hardware units into processors. ADeLe reduces the design effort for approximate hardware by modeling approximations at a high level of abstraction and automatically injecting them into a processor model for architectural simulation. Approximations in ADeLe may modify or completely replace the functional behavior of instructions according to user-defined policies. Instructions may be approximated deterministically or probabilistically (e.g., based on operating voltage and frequency). To allow for controlled testing, approximations may be enabled and disabled from software. Energy is automatically accounted based on customizable models that consider the potential power savings of the approximations that are enabled in the system. ADeLe provides designers with a generic and flexible verification framework, allowing them to easily evaluate the energy-quality trade-offs of their designs in applications. We demonstrate the language and corresponding framework by introducing different approximation techniques into a processor model, on top of which we run selected applications. We demonstrate ADeLe using 6 approximate designs with 4 image processing and 2 floating point applications. Our experiments show how ADeLe may be used to generate approximate CPUs and to evaluate energy-quality trade-offs for different applications with reduced effort.
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