In-Memory Non-Binary LDPC Decoding
Oscar Ferraz, Vitor Silva, and Gabriel Falcao

TL;DR
This paper introduces a novel in-memory decoding approach for non-binary LDPC codes using the UPMEM system, significantly improving decoding throughput and addressing data movement bottlenecks in error correction applications.
Contribution
It presents the first hardware PiM-based non-binary LDPC decoder, demonstrating competitive performance against GPU solutions.
Findings
Achieves 76 Mbit/s decoding throughput
First hardware PiM-based non-binary LDPC decoder
Outperforms traditional memory-bound solutions
Abstract
Low-density parity-check (LDPC) codes are an important feature of several communication and storage applications, offering a flexible and effective method for error correction. These codes are computationally complex and require the exploitation of parallel processing to meet real-time constraints. As advancements in arithmetic and logic unit technology allowed for higher performance of computing systems, memory technology has not kept the same pace of development, creating a data movement bottleneck and affecting parallel processing systems more dramatically. To alleviate the severity of this bottleneck, several solutions have been proposed, namely the processing in-memory (PiM) paradigm that involves the design of compute units to where (or near) the data is stored, utilizing thousands of low-complexity processing units to perform out bit-wise and simple arithmetic operations. This…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
