# Efficient Error-Correcting-Code Mechanism for High-Throughput Memristive Processing-in-Memory

arXiv: https://arxiv.org/abs/2105.04212 · HTML: https://mlsanity.com/paper/2105.04212/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 May 2021.

## Built on by (most cited first, 1 of 1)

- [Application of Machine Learning for Correcting Defect-induced Neuromorphic Circuit Inference Errors](https://mlsanity.com/paper/2509.11113/) (2025)

## Abstract (arXiv)

Inefficient data transfer between computation and memory inspired emerging processing-in-memory (PIM) technologies. Many PIM solutions enable storage and processing using memristors in a crossbar-array structure, with techniques such as memristor-aided logic (MAGIC) used for computation. This approach provides highly-paralleled logic computation with minimal data movement. However, memristors are vulnerable to soft errors and standard error-correcting-code (ECC) techniques are difficult to implement without moving data outside the memory. We propose a novel technique for efficient ECC implementation along diagonals to support reliable computation inside the memory without explicitly reading the data. Our evaluation demonstrates an improvement of over eight orders of magnitude in reliability (mean time to failure) for an increase of about 26% in computation latency.