Various applications, such as multimedia, machine learning, and signal processing, have a significant intrinsic error resilience. This makes them preferable for approximate computing as they have the ability to tolerate computations and data errors along with producing acceptable outputs. From the technology perspective, emerging technologies with inherent non-determinism and high failure rates are candidates for the realization of approximate computing. Spin Transfer Torque Magnetic Random Access Memories (STT-MRAM) is an emerging non-volatile memory technology and a potential candidate to replace SRAM due to its high density, scalability, and zero-leakage. The write operation in this technology is inherently stochastic and increases the rate of write errors. Moreover, this technology is associated with other failure mechanisms such as read-disturb and failures due to data retention. These errors are highly dependent on the STT-MRAM parameters (i.e., thermal stability, read/write current, and read/write latency), which varies with the operating temperature and the process variation effects. Fast and energy-efficient STT-MRAM designed for on-chip memories can be easily achieved by relaxing the device parameters at the cost of increased error rate, which can be addressed by approximating memory accesses. In this work, a detailed study of reliability and gains (i.e., performance and energy) tradeoff at the device and system-level of the STT-MRAM-based data cache system is presented in the scope of approximate memories.

中文翻译：

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近似自旋电子记忆

各种应用，例如多媒体、机器学习和信号处理，都具有显着的内在错误恢复能力。这使得它们更适合于近似计算，因为它们能够容忍计算和数据错误以及产生可接受的输出。从技术角度看，具有内在非确定性和高故障率的新兴技术是实现近似计算的候选。自旋转移扭矩磁性随机存取存储器(STT-MRAM) 是一种新兴的非易失性存储器技术，由于其高密度、可扩展性和零泄漏，是替代 SRAM 的潜在候选者。该技术中的写入操作本质上是随机的，并且会增加写入错误率。此外，该技术与其他故障机制相关，例如读取干扰和由于数据保留而导致的故障。这些误差高度依赖于 STT-MRAM 参数（即热稳定性、读/写电流和读/写延迟），这些参数随工作温度和工艺变化影响而变化。为片上存储器设计的快速且节能的 STT-MRAM 可以通过以增加错误率为代价放宽设备参数来轻松实现，这可以通过近似存储器访问来解决。在这项工作中，