TIRx Harness

Give your agent the language, tools, and execution environment to develop kernels for graphics processing units (GPUs). Use the components directly or connect them in an agent loop.

TIRx Harness brings together tirx-lite for kernel authoring, tirx_tools for analysis, and kcoral for remote execution. Skills guide the agent in using them, while workload contracts define correctness and performance. Start with the component or task you need.

How the pieces fit

Your agent orchestrates the loop.

Skills guide its choices. tirx-lite produces a kernel; tirx_tools inspects its TIRx function. A benchmark runs the compiled candidate locally or through kcoral. Correctness results, timings, and profiler artifacts inform the next edit.

Choose a component

tirx-lite

Kernel language & examples

Write kernels in tirx-lite, a domain-specific language over the TIRx intermediate representation. Explore complete implementations and launch examples.

tirx-lite
tirx_tools

Domain-specific compiler analysis

Check synchronization, memory races, and numerical behavior. Inspect compiler output and generated GPU instructions.

tirx_tools
kcoral

Remote GPU execution

Keep your agent on one machine and run GPU work on another. Use remote execution adapters to run kernels and retrieve diagnostic artifacts.

https://kcoral.mlc.ai/

Choose your next step

What you want to do

Start here

Optimize a kernel in your own project

Quick Start

Run a registered workload

Optimization Runs

Define a new optimization task

Add a workload

Publish a kernel produced by a run

Contribute a kernel

Reproduce and resolve a defect

Report and fix bugs

For hardware and kernel-programming background, see Modern GPU Programming for MLSys. For complete implementations, browse the Kernel Zoo.