Official repo for the ACSOS 2021 paper on how to manage many deep learning models at the edge!
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Updated
Sep 29, 2021 - Python
Official repo for the ACSOS 2021 paper on how to manage many deep learning models at the edge!
NexusKV is a model-state intelligence layer for inference systems.
Local inference serving with adaptive batching, benchmark sweeps, and regression gates for batching tradeoffs.
Reproducible Apple-Silicon (Apple MLX) deployment and one-token verification kit for the FreeToken edge-native MoE serving API — pinned, loopback-only, schema-validated evidence.
Reactive LLM inference.
Machine-readable companion to the IEEE OJ-CS survey 'Semantic Caching and Response Reuse for Large Language Model Services: A Survey' (Chukkapalli, Mishra, Naik, 2026): 21-work evidence matrix, systematic-search log, proposed benchmark trace schema, stdlib-only contract validator, and CPU pilot. Code MIT; data CC-BY-4.0.
cost-aware-inference-cluster: FastAPI inference-serving prototype with Redis queues, worker heartbeats, dynamic batching, autoscaling simulation, and local Docker Compose benchmark evidence.
GPU-aware LLM serving runtime with async scheduling, dynamic batching, streaming, admission control, metrics, and mock/llama.cpp/vLLM backends.
GSM artifact for exact online GNN inference serving with degree-based scheduling and memory-aware batch division.
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