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Online Correction of Hard Errors and Soft Errors via One-Step Decodable OLS Codes for Emerging Last Level Caches

机译:通过一步解码的OLS代码在线纠正硬错误和软错误,用于新兴级别缓存

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The number of marginal cells in static random-access memory (SRAM) increases as technology scales further. Spin transfer torque magnetic random-access memory (STT-MRAM) which is gaining popularity as a L3 cache alternative due to their small size, nonvolatility, high endurance, fast speed, scalability and low power consumption, also suffers from various stochastic and process variations causing both hard-errors and soft-errors in field. Orthogonal Latin Square (OLS) codes have been conventionally used in SRAMs for their low latency decoding. In this paper, an error-correcting scheme is proposed based on OLS codes which corrects both hard- errors and soft-errors simultaneously in a single step. The idea proposed is that in general a t-error correcting OLS code can be modified so that it can correct a certain number (ts <; t) of soft-errors while tolerating a certain number of hard errors as well. This is achieved by storing the hard-error locations during the encoding procedure and masking the hard-error locations during the decoding procedure. A threshold voting based decoding is used instead of majority logic decoding. The proposed one-step decoding methodology is shown to have a small decoding latency. This enables high throughput for STT-MRAMs and SRAMs, even in the presence of errors, and increases their reliability. It is shown that compared to a naive increased strength code to address both hard errors and soft errors, the proposed codes achieve better hardware overhead as well as better data redundancy.
机译:静态随机存取存储器(SRAM)中的边缘电池数量进一步缩放增加。由于其体积小,非易失性,高耐久性,快速,可扩展性和低功耗,旋转传递扭矩随机存取存储器(STT-MRAM)作为L3缓存替代的替代。也存在各种随机和工艺变化的替代导致字段中的硬错误和软错误。正交拉丁方(OLS)代码在SRAM中通常用于其低延迟解码。在本文中,基于OLS代码提出了一种纠错方案,其在单个步骤中校正硬误差和软误差。所提出的想法是,通常可以修改T误差校正OLS代码,以便它可以纠正一定的数量(t s <; T)软误差,同时容忍一定数量的硬错误。这是通过在编码过程期间存储硬错误位置并在解码过程期间掩蔽硬错误位置来实现的。使用基于阈值的基于投票的解码而不是多数逻辑解码。所提出的一步解码方法被示出具有小的解码延迟。这使得STT-MRAMS和SRAM的高吞吐量即使在存在错误时也会增加其可靠性。结果表明,与天真的增加的强度代码相比解决了困难误差和软错误,所提出的代码可以实现更好的硬件开销以及更好的数据冗余。

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