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Team Manifold - includes NVIDIA employee

We removed all the extra compute in all the kernels.

Code Cerebral Valley

Core trick

Removes redundant per-element compute from kernels, and replaces outer products with hl.dot matmuls plus autotuned tile sizes.

Tags

dev tools

Description

We removed all the extra compute in all the kernels. We adjusted tile size and autotuned the kernels and used hl.dot instead of separate outer products for the gated_deltanet_recompute_w_u_py.
andrewbriand/helion-hackathon★ 00 forksPythonMITCreated Mar 14, 2026 · last push Mar 14, 2026

README excerpt

## Reference Kernels

This repo holds reference kernels for the KernelBot which hosts regular competitions on [discord.gg/gpumode](discord.gg/gpumode).

You can see what's going on [gpumode.com](https://www.gpumode.com/)

## Competition
1. [PMPP practice problems](https://github.com/gpu-mode/reference-kernels/tree/main/problems/pmpp_v2)
2. [AMD $100K kernel competition](problems/amd)
3. [BioML kernels](problems/bioml)
4. [AMD $100K distributed kernel competition](problems/amd_distributed)
5. [NVIDIA Blackwell NVFP4 competition](problems/nvidia)

## Making a Leaderboard Submission

Please take a look at `vectoradd_py` to see multiple examples of expected submisisons ranging from PyTorch code to Triton to inline CUDA.


## Contributing New Problems

To add a new problem, create a new folder in the `problems/glory` directory where you need to add the following files:
- `reference.py` - This is the PyTorch reference implementation of the problem.
- `task.yml` - This is the problem specification that will be used to generate test cases for different shapes
- `task.py` - Specifies the schema of the inputs and outputs for the problem

You can evaluate problems with your own Modal account (they give you a free $30) by borrowing this [neat script from @gau-nernst](https://github.com/gpu-mode/reference-kernels/pull/96#issue-3850136894)

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