[Wave] Fun projects for beginnners

[raikonenfnu]

Are you interested in learning more about GPU programming and developing cool optimizations? Do you want to help build next generation and state-of-the-art machine learning models and layers? Do you want to define the future programming paradigm of machine learning and GPU layers? Look no further, come join us in building "Wave"!

Here are some fun starter tasks to look at:

• [ ] Implement backwards attention kernel on TKW
• [ ] Cache kernels
• [ ] #285 - @nithinsubbiah
• [x] Auto detection of hardware architecture in runtime - https://github.com/iree-org/iree-turbine/pull/279
• [ ] Support more architecture in codegen aside from CDNA.
• [ ] Refactor Wave ops definition and make it autogen documentations
• [ ] Implement Pytorch Linear Layer (forward, backward) that uses custom TKW kernel
• [ ] Implement Pytorch Conv2d Layer (forward, backward) that uses custom TKW kernel
• [ ] Implement Pytorch Attention Layer (forward, backward) that uses custom TKW kernel
• [ ] Integrate Wave kernel into sharktank for e2e S.T we can inject IR from TKW into model IR.

[NoumanAmir657]

Would this be open for someone who has almost no knowledge of GPU programming except for some basic understanding.