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Defect Characterization and Test Generation for Spintronic-based Compute-In-Memory

机译:基于自旋电子的内存计算的缺陷表征和测试生成

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Spin Transfer Torque Magnetic Random Access Memory (STT-MRAM), as one of the most promising emerging memory technology for on-chip memory, offers many advantageous features such as high density, non-volatility, scalability, high endurance and CMOS compatibility. Additionally, its resistive storage concept can be utilized for Compute-in-Memory (CiM), where bit-wise logical operations can be performed within the memory without the need for transferring the data from the memory to the processor and back. However, these new CiM operations are impacted by defects, resulting in faults which are different from the conventional memory faults. Hence, these CiM specific faults need to be modeled and appropriate test strategies need to be derived to ensure correct functionality of the CiM enabled memories. In this paper, we first perform extensive defect injection in the CiM bit-cell and build fault models based on the impact of the defects. We also compare CiM specific faults to normal memory faults based on this technology. From this model, we derive an efficient test algorithm to fully cover CiM related faults, which cannot be found with conventional memory test algorithms.
机译:自旋转移扭矩磁随机存取存储器(STT-MRAM)作为片上存储器中最有前途的新兴存储器技术之一,具有许多优势,例如高密度,非易失性,可扩展性,高耐久性和CMOS兼容性。此外,其电阻存储概念可用于内存计算(CiM),其中可以在内存内执行按位逻辑运算,而无需将数据从内存传输到处理器再返回。但是,这些新的CiM操作会受到缺陷的影响,从而导致出现与常规内存错误不同的错误。因此,需要对这些特定于CiM的故障进行建模,并需要导出适当的测试策略,以确保支持CiM的存储器的正确功能。在本文中,我们首先在CiM位单元中进行大量的缺陷注入,然后根据缺陷的影响建立故障模型。我们还将基于此技术的CiM特定故障与正常内存故障进行比较。从该模型中,我们得出了一种有效的测试算法,可以完全覆盖与CiM相关的故障,而传统的内存测试算法无法找到这种算法。

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