A collaborative inference framework combining offline DAG partitioning with online semantic-cache-based early exit and adaptive quantization achieves large latency and throughput gains in experiments, but with unverified accuracy and no released code.
Dyno: Dynamic onloading of deep neural networks from cloud to device,
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Accelerating End-Cloud Collaborative Inference via Near Bubble-free Pipeline Optimization
A collaborative inference framework combining offline DAG partitioning with online semantic-cache-based early exit and adaptive quantization achieves large latency and throughput gains in experiments, but with unverified accuracy and no released code.