CRISP: Co-designing Pruning and Scheduling for Efficient MoE Inference on Edge Servers
Research framing: expert-weight movement dominates edge MoE inference.
3 items · 2 sources · 3 days
Operational story trace
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Latest change
A Show HN project (Nov 3) claims faster MoE inference on a Mac with less RAM, following a Nov 2 post on running a 124B MoE on one DGX Spark.
An Oct 27 arXiv paper framed edge MoE inference as an expert-weight movement problem rather than a compute problem. Two Hacker News posts followed within a week, showing the same memory constraint being attacked on a single DGX Spark and on Macs.
Arc
Research framing: expert-weight movement dominates edge MoE inference.
Practitioner report on fitting a 124B MoE onto one DGX Spark.
Applies the memory-reduction goal to Mac hardware.
Research framing: expert-weight movement dominates edge MoE inference.
Practitioner report on fitting a 124B MoE onto one DGX Spark.
Applies the memory-reduction goal to Mac hardware.
What to watch — open questions
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