An imperative command-line-interface for AI workload orchestration
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Updated
Jul 13, 2026 - Python
An imperative command-line-interface for AI workload orchestration
A lightweight LLM inference runtime, evolving toward heterogeneous, stage-disaggregated serving.
A policy layer above transport for KV movement, workload-aware admissibility, and explainable routing in disaggregated inference.
Open-source Python control plane for LLM inference: launch, route, scale, and observe disaggregated serving on infrastructure you control.
DiSpec — a from-scratch LLM inference engine: paged attention, continuous batching, CUDA-graph decode, speculative decoding, and prefill/decode disaggregation
Research fork of LLMServingSim 2.0 investigating Head-of-Line (HoL) blocking mitigation in disaggregated LLM serving via novel scheduling algorithms.
A fault-tolerant LLM routing system that decouples inference from AWS Bedrock by routing prefill and decode tasks through SQS and ensuring zero-downtime scaling with a graceful drain sidecar.
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