GitHub
Things you can run.
Joule is an inference power economics engine that ties physical GPU energy to token throughput and SLO goodput. The public repos are the rest of the argument: serving code, an educational engine, a Lambda lab, observability for agents, the Packt Nexus workshop, thesis code for national AI-infrastructure fragility, and the GPU list at gpuengineering.com.
Builds
- Joule
Founder. Joule is an inference power economics engine that ties physical GPU energy to token throughput and SLO goodput.
- gpuengineering.com
The public list behind the domain: CUDA, kernels, serving engines, multi-GPU systems. ~600 stars as awesome-gpu-engineering.
- RelayServe
Minimal LLM inference gateway for heterogeneous devices. OpenAI-compatible chat, batching, streaming, request IDs, /metrics. On PyPI as relayserve.
- smol-vllm
Educational paged-attention engine: KV cache, continuous batching, preemption, prefill vs decode. Built to be read, not shipped as production vLLM.
- fullstack-inferencing
vLLM on Lambda Cloud, FastAPI gateway, nginx, Prometheus, Grafana, optional Jaeger. Documents engine-flag limits, cost metrics, and Lambda image caveats.
- AbideX
Zero-code OpenTelemetry monitoring for agent workflows (CrewAI, LangGraph, Pydantic AI). The Abide-era observability product.
- awesome-observability
Curated tools and frameworks for LLM observability.
- llm-cluster-simulator
Browser simulator for distributed LLM training and inference: memory, throughput, cost, parallelism.
- ai-infra-fragility
Code for Cascading Fragility in National AI Infrastructure, market structure, exposure, network models. Submitting to AI & Society (Springer).
Course labs
- nexus-workshop-code
Packt Nexus: build a first agent / multi-agent system with CrewAI, roles, tasks, orchestration.
- inferencing_maven
Labs for the Maven inference engineering cohort.
- class-code
Class exercises that sit next to RelayServe and the serving labs.
- concurrency
Concurrency exercises for inference workloads.
- ray_project
Student exercise on concurrency and profiling with Ray.