{"ID":2886445,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.03567","arxiv_id":"2508.03567","title":"In-Memory Non-Binary LDPC Decoding","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 paper presents a novel efficient solution for near-memory non-binary LDPC decoders in the UPMEM system, for the best of our knowledge the first real hardware PiM-based non-binary LDPC decoder that is benchmarked against low-power GPU parallel solutions highly optimized for throughput performance. PiM-based non-binary LDPC decoders can achieve 76 Mbit/s of decoding throughput, which is even competitive when compared against implementations running in edge GPUs.","short_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 a...","url_abs":"https://arxiv.org/abs/2508.03567","url_pdf":"https://arxiv.org/pdf/2508.03567v1","authors":"[\"Oscar Ferraz\",\"Vitor Silva\",\"Gabriel Falcao\"]","published":"2025-08-05T15:36:58Z","proceeding":"cs.DC","tasks":"[\"cs.DC\",\"cs.CE\"]","methods":"[]","has_code":false}