Add Triton to ASR frontend

[certik]

The high level motivation

Some real world PyTorch benchmarks that we would like to run are at: https://github.com/pytorch/benchmark/tree/64409d5704b6136c6cb28071ff8eba61751b1b02/torchbenchmark/models, those compile via Triton, so if we add Triton to ASR, we'll be able to compile them via LCompilers.

Details

Here are example files with real-world kernels in Triton:

• https://github.com/openai/triton/blob/bf3171f5c735ea216fb624107c807e4e026c5638/python/triton/ops/flash_attention.py
• https://github.com/openai/triton/blob/bf3171f5c735ea216fb624107c807e4e026c5638/python/triton/ops/matmul.py
• Tutorials: https://github.com/openai/triton/blob/bf3171f5c735ea216fb624107c807e4e026c5638/python/tutorials/01-vector-add.py

The goal should be to add a frontend that can translate them to ASR. Most likely tapping at the intermediate representation in Triton. Triton seems to be using their own dialect in MLIR as the IR: https://github.com/openai/triton/blob/bf3171f5c735ea216fb624107c807e4e026c5638/python/src/triton.cc, so most likely taking that and transforming to ASR might work (https://github.com/lcompilers/lpython/issues/2341). Triton can print the intermediate representation that it sees, so we should use that.

[certik]

Another idea is to not even go to Triton, but add a PyTorch backend here: https://github.com/pytorch/pytorch/blob/3c46e859aa7a5721322d67b2b9af4c2d47460a18/torch/_inductor/codegen/, similar to the cpp backend. It would generate Python (LPython) code, that LPython can compile.