refactor: Get compiled_kernel from Triton Call Directly

[sgjzfzzf]

Triton call will return the CompiledKernel directly to get the cubin. The previous code searches the cubin by cache, which is unnecessary and not robust.

This PR refactors that by taking compiled_kernel directly from the Triton kernel call.

[gemini-code-assist]

Summary of Changes

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This pull request refactors the method of acquiring a CompiledKernel instance after a Triton kernel execution. Previously, the code would perform a dummy kernel call and then manually search through Triton's internal device caches to retrieve the compiled kernel. The updated approach leverages a change where the Triton kernel call now directly returns the CompiledKernel object, simplifying the code, enhancing its reliability, and removing an indirect and potentially fragile lookup mechanism.

Highlights

• Direct CompiledKernel Retrieval: The pull request modifies the examples to directly obtain the CompiledKernel object from the return value of a Triton kernel call, rather than extracting it from internal device caches.
• Simplified CUBIN Extraction: This change removes the previous, more complex logic of iterating through device_caches to find the compiled kernel, streamlining the process of getting CUBIN bytes.
• Improved Robustness: By directly receiving the CompiledKernel, the code becomes more robust as it no longer relies on the internal structure or search mechanism of the device cache, which the PR description notes was 'unnecessary and not robust'.

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[gemini-code-assist]

Code Review

This pull request refactors the way CompiledKernel is obtained from a Triton kernel call. The previous method of accessing the internal device cache was brittle and relied on implementation details. The new approach, which gets the CompiledKernel directly from the return value of the kernel launch, is much cleaner, more robust, and simplifies the code significantly in both benchmark_overhead.py and example_triton_cubin.py. The changes are correct and represent a good improvement in code quality and maintainability.