* Some prep work for adding batched_gemm_wmma_universal. Moved batched_gemm in general to gfx11 and gfx12 categories, and split existing batched_gemm test into xdl and wmma versions. Updated profiler and instance factory. For now only adding f16-row-row-row-GemmDefault. For now actual device instance list is empty.
* Add DeviceBatchedGemm_Wmma_CShuffleV3 based on DeviceGemm_Wmma_CShuffleV3 and make sure it's used in the instance factory and tests. Currently the new batched device level struct cannot actually handle batching, but it does pass tests with a trivial batch size of 1, meaning that the overall structure is good.
* Add custom kernel and Argument type to DeviceBatchedGemm_Wmma_CShuffleV3. Batching arguments not passed to kernel yet.
* Implement kernel-level batching logic for DeviceBatchedGemm_Wmma_CShuffleV3. In principle the whole thing works now, just need to add other data types and perhaps do some cleanup.
* Add other layouts for batched gemm wmma chufflev3 f16 f16 f16. Now matching XDL (for f16).
* Add bf16 bf16 bf16 support for batched gemm wmma cshuffle v3 for all layouts.
* Fixup comments and TODOs
* Expand test cases for batched gemm wmma cshuffle v3 with more unusual shapes. Some of the original test cases for batched gemm do not work based on cshuffle v3 because the dimensions are too small.
* Fix argument order for calls to profile_batched_gemm_impl() ONLY in wmma tests.
* Take batching into account when using rotating memory or clearing the C tensor.
* Implement small refactors / comments etc. from review.
* Port recent gemm wmma updates to batched gemm wmma: V1 pipeline, non-main-k-block-loop, check compute type, packed buffer size calc. Ported new instance lists.
* Add MNKPadding instances to batched gemm wmma cshuffle v3, remove incompatible test problems.
* Put clearing the C matrix in a pre-process lambda for the non-flush case + small fixups.
* Once again switch order of strides and batch strides in calls to profile_batched_gemm_impl() from test_batched_gemm_wmma to match latest definition of that function.
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Co-authored-by: kiefer <kiefer.van.teutem@streamhpc.com>
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