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arXiv · 2511.08381

Fault Tolerant Reconfigurable ML Multiprocessor

Tangrui Li·Justin Y. Shi·Matteo Spatola·Hongzheng Wang
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Abstract

This paper reports three computational experiments for a von Neumann inspired reconfigurable fault tolerant multiprocessor for neural network (NN) training workflows. The experiments are intended to prove the feasibility of the proposed reconfigurable multiprocessor architecture for non-regular workflows on robustness of adaptability. A potential integration with MLIR compilers is also discussed for integrating diverse accelerator hardware for existing practical applications.

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Tangrui Li, Justin Y. Shi, Matteo Spatola, Hongzheng Wang. 2025-11-11. Fault Tolerant Reconfigurable ML Multiprocessor. https://arxiv.org/abs/2511.08381

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