CoCa combines server-side global semantic caches with per-client dynamic cache allocation to cut edge inference latency by 23 to 45 percent with under 3 percent accuracy loss.
Ac- tion recognition framework in traffic scene for autonomous driving system,
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Many Hands Make Light Work: Accelerating Edge Inference via Multi-Client Collaborative Caching
CoCa combines server-side global semantic caches with per-client dynamic cache allocation to cut edge inference latency by 23 to 45 percent with under 3 percent accuracy loss.