EVX:低功耗EDGE内核上的矢量执行

M. Duric, Oscar Palomar, Aaron Smith, O. Unsal, A. Cristal, M. Valero, D. Burger
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引用次数: 7

摘要

在本文中,我们提出了一个矢量执行模型,该模型提供了矢量处理器在低功耗,通用内核上的优势,并且具有有限的额外硬件。在加速数据级并行(DLP)工作负载的同时,矢量模型提高了效率和硬件资源利用率。我们使用基于显式数据图执行(EDGE)架构的适度双问题核心来实现我们的方法,称为EVX。与大多数使用额外硬件并增加低功耗处理器复杂性的DLP加速器不同,EVX利用EDGE内核的可用资源,并且以最小的成本允许资源专业化。EVX增加了一个控制逻辑,使核心面积增加了2.1%。我们表明,与标量基线相比,EVX的平均加速速度提高了3倍,并且优于多媒体SIMD扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EVX: Vector execution on low power EDGE cores
In this paper, we present a vector execution model that provides the advantages of vector processors on low power, general purpose cores, with limited additional hardware. While accelerating data-level parallel (DLP) workloads, the vector model increases the efficiency and hardware resources utilization. We use a modest dual issue core based on an Explicit Data Graph Execution (EDGE) architecture to implement our approach, called EVX. Unlike most DLP accelerators which utilize additional hardware and increase the complexity of low power processors, EVX leverages the available resources of EDGE cores, and with minimal costs allows for specialization of the resources. EVX adds a control logic that increases the core area by 2.1%. We show that EVX yields an average speedup of 3x compared to a scalar baseline and outperforms multimedia SIMD extensions.
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