Optimize RWKV7 inference by fusing some graph operators

[MollySophia]

Summary

This PR optimizes RWKV7 inference by reducing graph-level operator overhead
across CUDA and Vulkan, with CPU fallback coverage for the new RWKV-specific
operators.

Although RWKV is architecturally more linear/recurrent than Qwen3.5-style
hybrid models, the current ggml graph for RWKV7 expands into many small
elementwise and reduction operators around WKV. In decode, these small ops
create significant launch/dispatch overhead. This PR makes the main RWKV7 hot
paths explicit ggml ops so backends do not need to rediscover RWKV semantics
through fragile graph-pattern fusion.

Changes

• Specialize RWKV7 WKV decode paths.

  • CUDA: optimized WKV7 decode kernel.
  • Vulkan: added specialized wkv7_t1 decode shader.

• Add explicit RWKV time-mix lerp op:

  • RWKV_LERP: cur + (x_prev - cur) * weight
  • CUDA and Vulkan call the existing specialized kernels directly.
  • CPU has a F32 fallback with a contiguous RWKV fast path.

• Fuse CUDA RWKV key-update pattern:

  • k + (a * ka - ka)

• Add explicit RWKV7 r_k correction op:

  • RWKV_RK: cur + reshape(v * sum_rows((k * r) * r_k))
  • CUDA: added standalone fused kernel.
  • Vulkan: added standalone rwkv_rk.comp shader.

• Work around a Vulkan CI correctness failure by disabling the specialized
  RWKV7 T=1 subgroup shader on Intel proprietary Windows. This is a separate
  commit from the RWKV op changes so it can be reverted independently if the
  driver-specific issue is resolved.

Performance

Hardware:

• GPU: NVIDIA GeForce RTX 5090
• CPU: AMD Ryzen 9 9950X
• CPU thread count: 16
• Baseline commit: 0eca4d490

RWKV7 1.5B

GPU model: rwkv7-g1g-1.5b-20260526-ctx8192-FP16.gguf

CPU model: rwkv7-g1g-1.5b-20260526-ctx8192-q4_0.gguf

Prefill

Backend	Model	Test	Baseline	Current	Delta
CUDA	RWKV7 1.5B F16	pp512	23092.43 +/- 1706.81	25148.17 +/- 2650.54	+8.9%
Vulkan	RWKV7 1.5B F16	pp512	16885.02 +/- 37.00	20720.94 +/- 47.62	+22.7%
CPU 16t	RWKV7 1.5B Q4_0	pp512	1112.15 +/- 2.48	1192.53 +/- 7.59	+7.2%

Decode

Backend	Model	Test	Baseline	Current	Delta
CUDA	RWKV7 1.5B F16	tg128	282.29 +/- 1.52	322.79 +/- 1.29	+14.3%
Vulkan	RWKV7 1.5B F16	tg128	244.56 +/- 0.60	287.48 +/- 0.97	+17.5%
CPU 16t	RWKV7 1.5B Q4_0	tg128	64.47 +/- 0.51	65.54 +/- 0.51	+1.7%

RWKV7 7.2B

Model: rwkv7-g1g-7.2b-20260523-ctx8192-F16.gguf

Prefill

Backend	Model	Test	Baseline	Current	Delta
CUDA	RWKV7 7.2B F16	pp512	8190.77 +/- 562.32	9336.82 +/- 648.37	+14.0%
Vulkan	RWKV7 7.2B F16	pp512	7289.55 +/- 11.08	8464.32 +/- 5.15	+16.1%

Decode

Backend	Model	Test	Baseline	Current	Delta
CUDA	RWKV7 7.2B F16	tg128	90.32 +/- 0.19	95.76 +/- 0.13	+6.0%
CUDA	RWKV7 7.2B F16	tg512	90.51 +/- 0.03	95.91 +/- 0.03	+6.0%
Vulkan	RWKV7 7.2B F16	tg128	83.84 +/- 0.01	90.10 +/- 0.02	+7.5%
Vulkan	RWKV7 7.2B F16	tg512	83.95 +/- 0.05	90.26 +/- 0.04	+7.5%

Validation

• Backend op smoke tests:
  • test-backend-ops test -o RWKV_WKV7 -b CUDA0 -j 1
  • test-backend-ops test -o RWKV_WKV7 -b Vulkan0 -j 1
• WikiText-2 perplexity is unchanged within noise:
  • 1.5B F16: 9.5497 -> 9.5503
  • 7.2B F16: 6.4011 -> 6.4013

Notes

The largest gains come from reducing small graph operators and backend launches
around RWKV decode. On larger models, decode gains are smaller because mat-vec
work dominates more strongly, but both CUDA and Vulkan still show consistent
positive improvements.

TODO

• [] SYCL/Metal fused kernels

[ggml-gh-bot]

Hi @MollySophia, thanks for your contribution!

Per our contribution guidelines, the automated PR checker found the following issue(s) that need your attention:

• Multiple backend changes in one PR: When adding support for a new model or feature, focus on CPU support only in the initial PR. Add support for other backends like CUDA in follow-up PRs. If you have a good reason to modify multiple backends in one PR, please explain it.

• Large PR: Large changes require prior discussion (e.g. an issue or RFC) and maintainers may not be able to review this PR as-is. Consider splitting it into smaller, focused PRs.

---

Please note that maintainers reserve the right to make final decisions on PRs. If you believe there is a mistake, please comment below.

[MollySophia]

Hi @MollySophia, thanks for your contribution!

Per our contribution guidelines, the automated PR checker found the following issue(s) that need your attention:

• Multiple backend changes in one PR: When adding support for a new model or feature, focus on CPU support only in the initial PR. Add support for other backends like CUDA in follow-up PRs. If you have a good reason to modify multiple backends in one PR, please explain it.
• Large PR: Large changes require prior discussion (e.g. an issue or RFC) and maintainers may not be able to review this PR as-is. Consider splitting it into smaller, focused PRs.

Please note that maintainers reserve the right to make final decisions on PRs. If you believe there is a mistake, please comment below.

Regard PR flags:

1 & 2: This PR makes changes on the existing RWKV7 path, rather than support a new model or feature. The WKV7 op has some semantic changes so that all the supported backends need to be modified at once.