Distributed Computing
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Closed-Form Reliability Modeling for Distributed AI Inference on Volatile Consumer Edge Devices
This paper introduces an analytical framework for quantifying computational reliability in Extreme Edge Computing (XEC), where AI inference workloads are distributed across consumer-owned devices with unpredictable availability. The framework derives closed-form reliability expressions — the probabi…
FastMPS: A Multi-Level Parallel Framework for Scalable Matrix Product State Sampling
FastMPS addresses limitations in large-scale Matrix Product State (MPS) sampling by integrating data parallelism across samples with tensor parallelism along bond dimensions. This novel approach mitigates memory and I/O bottlenecks through compression and overlapping, effectively reactivating data p…