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Mixture-of-Experts (MoE) models are a compelling architecture for scaling model capacity, making them especially attractive for deployment on resource-constrained, single-GPU systems. However, this benefit is difficult to realize because expert parameters dominate memory, and token-level routing is dynamic, unpredictab...
Procyon, a fine-grain multi-tenancy framework that fuses the PE instruction streams of multiple workloads into a unified execution schedule, substantially reduces PE underutilization that results in 3 × speedup over state-of-the-art sparse streaming accelerators, and reaches a peak throughput of 61 .
This work categorizes LLM kernel operands into three inter-workgroup sharing patterns and shows that the required optimization strategies differ across categories, from simple per-workgroup pinning to subgroup-aware co-scheduling, highlighting the need for placement-aware kernel programming and smarter architectural su...
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