Cost-effective soft-error protection for SRAM-based structures in GPGPUs

Jingweijia Tan, Zhi Li, Xin Fu
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引用次数: 7

Abstract

The general-purpose computing on graphics processing units (GPGPUs) are increasingly used to accelerate parallel applications. This makes reliability a growing concern in GPUs as they are originally designed for graphics processing with relaxed requirements for execution correctness. With CMOS processing technologies continuously scaling down to the nano-scale, on-chip soft error rate (SER) has been predicted to increase exponentially. GPGPUs with hundreds of cores integrated into a single chip are prone to manifest high SER. This paper aims to enhance the GPGPU reliability in light of soft errors. We leverage the GPGPU microarchitecture characteristics, and propose energy-efficient protection mechanisms for two typical SRAM-based structures (i.e. instruction buffer and registers) which suffer high susceptibility. We develop Similarity-AWare Protection (SAWP) scheme that leverages the instruction similarity to provide the near-full ECC protection to the instruction buffer with quite little area and power overhead. Based on the observation that shared memory usually exhibits low utilization, we propose SHAred memory to Register Protection (SHARP) scheme, it intelligently leverages shared memory to hold the ECCs of registers. Experimental results show that our techniques have the strong capability of substantially improving the structure vulnerability, and significantly reducing the power consumption compared to the full ECC protection mechanism.
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基于sram的gpgpu结构的高性价比软错误保护
图形处理单元(gpgpu)上的通用计算越来越多地用于加速并行应用程序。这使得可靠性在gpu中越来越受到关注,因为它们最初是为图形处理而设计的,对执行正确性的要求并不高。随着CMOS处理技术的不断缩小到纳米级,片上软错误率(SER)预计将呈指数级增长。将数百个核集成到单个芯片中的gpgpu容易表现出高SER。本文旨在针对软误差问题,提高GPGPU的可靠性。利用GPGPU微架构的特点,针对两种典型的易受影响的sram结构(即指令缓冲区和寄存器)提出了节能保护机制。我们开发了相似感知保护(similarity - aware Protection, SAWP)方案,该方案利用指令相似度为指令缓冲区提供近乎完全的ECC保护,且面积和功耗开销很小。基于共享内存通常表现出较低的利用率,我们提出了共享内存寄存器保护(SHARP)方案,它智能地利用共享内存来保存寄存器的ecc。实验结果表明,与全ECC保护机制相比,我们的技术具有较强的改善结构脆弱性的能力,并且显著降低了功耗。
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