[rocm-libraries] ROCm/rocm-libraries#10179 (commit 6c627c2)

feat(ck) [CK] Wavelet gemm pipeline for conv fwd
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## Motivation

In the current CShuffleV3 conv fwd kernel, the in-kernel conv-to-GEMM
transform generates significant INT32 VALU pressure per MFMA
instruction. On VALU-heavy shapes (e.g., G=1, 3×3, C=256), these index
computation ops compete with MFMA for VALU issue slots, creating a
bottleneck that cannot be resolved by pipeline prefetching alone.

This PR adds a wave-specialized ("wavelet") convolutions forward kernel
that splits workgroup threads into two roles:
- **Load waves**: conv-to-GEMM address computation + global memory loads
+ LDS writes (all VALU/VMEM)
- **Math waves**: LDS reads + MFMA + CShuffle epilogue (no index
computation)

By physically separating the two instruction classes onto different
waves, VALU and MFMA execute on different hardware functional units
without contention.

## Technical Details

**Wave pipeline (modified):**
- `gridwise_gemm_waveletmodel.hpp` — load/math wave pipeline structs
with `sched_group_barrier` scheduling hints to front-load VMEM reads
before address-advance VALU

**Two wave ratios:**
- **(4,4)**: 256 load + 256 math = 512 threads (8 waves). Best on large
shapes.
- **(4,2)**: 256 load + 128 math = 384 threads (6 waves). Best on small
shapes (fewer sync barriers, denser MFMA per math wave).

JIRA ID : ROCM-21620