PV-ReCAM: Process Variation-Aware Testing for ReRAM-based Content Addressable Memory

Computation-in-Memory (CiM) is a promising solution to reduce the energy and latency caused by frequent data transfers between the processor and memory, a problem commonly referred to as the memory wall. For instance, comparing binary patterns to measure similarity is a common and challenging task in today’s emerging artificial intelligence applications. This can be implemented efficiently using Content Addressable Memory (CAM), which is well-suited for CiM-based acceleration of such tasks. To improve energy efficiency and performance, non-volatile memories (NVM) such as ReRAM (Redox-based RAM) can be utilized for the realization of CiMbased CAM. However, ReRAM is highly susceptible to process variations (PV), due to the immaturity of its process and inherent stochasticity. Moreover, the analog realization of CAM functionality using NVMs makes it more sensitive to these non-idealities. Conventional March tests, originally designed for memory fault detection, become ineffective in the presence of PV, which can alter ReCAM behavior and lead to test escapes. To address these challenges, this work systematically analyzes the impact of PV on ReCAM functionality. ... mehrIt proposes a generalized PV-aware March test that optimizes test patterns for both hard and PV-induced soft defects, achieving 100% defect coverage.