{"ID":2844977,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.05321","arxiv_id":"2511.05321","title":"MultiVic: A Time-Predictable RISC-V Multi-Core Processor Optimized for Neural Network Inference","abstract":"Real-time systems, particularly those used in domains like automated driving, are increasingly adopting neural networks. From this trend arises the need for high-performance hardware exhibiting predictable timing behavior. While state-of-the-art real-time hardware often suffers from limited memory and compute resources, modern AI accelerators typically lack the crucial predictability due to memory interference. We present a new hardware architecture to bridge this gap between performance and predictability. The architecture features a multi-core vector processor with predictable cores, each equipped with local scratchpad memories. A central management core orchestrates access to shared external memory following a statically determined schedule. To evaluate the proposed hardware architecture, we analyze different variants of our parameterized design. We compare these variants to a baseline architecture consisting of a single-core vector processor with large vector registers. We find that configurations with a larger number of smaller cores achieve better performance due to increased effective memory bandwidth and higher clock frequencies. Crucially for real-time systems, execution time fluctuation remains very low, demonstrating the platform's time predictability.","short_abstract":"Real-time systems, particularly those used in domains like automated driving, are increasingly adopting neural networks. From this trend arises the need for high-performance hardware exhibiting predictable timing behavior. While state-of-the-art real-time hardware often suffers from limited memory and compute resources...","url_abs":"https://arxiv.org/abs/2511.05321","url_pdf":"https://arxiv.org/pdf/2511.05321v2","authors":"[\"Maximilian Kirschner\",\"Konstantin Dudzik\",\"Ben Krusekamp\",\"Jürgen Becker\"]","published":"2025-11-07T15:19:14Z","proceeding":"cs.AR","tasks":"[\"cs.AR\"]","methods":"[]","has_code":false}