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

  • Company
    Joule

    Founder. Joule is an inference power economics engine that ties physical GPU energy to token throughput and SLO goodput.

  • Curriculum
    gpuengineering.com

    The public list behind the domain: CUDA, kernels, serving engines, multi-GPU systems. ~600 stars as awesome-gpu-engineering.

  • Serving
    RelayServe

    Minimal LLM inference gateway for heterogeneous devices. OpenAI-compatible chat, batching, streaming, request IDs, /metrics. On PyPI as relayserve.

  • Engine
    smol-vllm

    Educational paged-attention engine: KV cache, continuous batching, preemption, prefill vs decode. Built to be read, not shipped as production vLLM.

  • Lab / Lambda
    fullstack-inferencing

    vLLM on Lambda Cloud, FastAPI gateway, nginx, Prometheus, Grafana, optional Jaeger. Documents engine-flag limits, cost metrics, and Lambda image caveats.

  • Observability
    AbideX

    Zero-code OpenTelemetry monitoring for agent workflows (CrewAI, LangGraph, Pydantic AI). The Abide-era observability product.

  • Observability
    awesome-observability

    Curated tools and frameworks for LLM observability.

  • Systems
    llm-cluster-simulator

    Browser simulator for distributed LLM training and inference: memory, throughput, cost, parallelism.

  • Thesis
    ai-infra-fragility

    Code for Cascading Fragility in National AI Infrastructure, market structure, exposure, network models. Submitting to AI & Society (Springer).

Course labs

  • Workshop
    nexus-workshop-code

    Packt Nexus: build a first agent / multi-agent system with CrewAI, roles, tasks, orchestration.

  • Course
    inferencing_maven

    Labs for the Maven inference engineering cohort.

  • Course
    class-code

    Class exercises that sit next to RelayServe and the serving labs.

  • Course
    concurrency

    Concurrency exercises for inference workloads.

  • Course
    ray_project

    Student exercise on concurrency and profiling with Ray.