graph : remove redundant GDN state transposes (llama/20443)

graph : remove redundant GDN state transposes (llama/20443)

* ggml : transpose fused GDN state access for coalesced memory reads (llama/20436)

The fused Gated Delta Net kernel accessed the [S_v, S_v] state matrix
column-wise on row-major storage, causing strided reads (stride S_v =
128 floats = 512 bytes) that waste GPU cache bandwidth. This produced a
39% regression on Qwen3.5-9B (Metal, M4 Max) compared to the unfused
path.

Transpose the state indexing so threads read contiguously:
- Metal: s_ptr[is*S_v] -> s_ptr[is] (stride 1 vs S_v)
- CUDA:  curr_state[i*S_v+col] -> curr_state[col*S_v+i] (coalesced)
- CPU:   restructured loops for row-wise transposed access

Also add --fused-gdn [on|off|auto] CLI flag (mirrors --flash-attn) so
users can control fused GDN independently of auto-detection.

All GATED_DELTA_NET backend-ops tests pass.

Co-Authored-By: Claude Opus 4.6 <redacted>
* ggml : use SIMD dot products in CPU GDN kernel, couple AR/chunked fused flags

- Replace scalar inner loops with ggml_vec_dot_f32 for SIMD-optimized
  dot products in the CPU fused GDN kernel (delta and attention output)
- Couple fused_gdn_ar and fused_gdn_ch flags in auto-detection: if one
  path lacks device support, disable both to prevent state layout mismatch
  between transposed (fused) and non-transposed (unfused) formats

Co-Authored-By: Claude Opus 4.6 <redacted>
* llama : rever fgdn argument changes

* graph : remove GDN state transposes

* vulkan : adapt

* cuda : remove obsolete smem code

---------

Co-authored-by: Paul Flynn <redacted>
Co-authored-by: Claude Opus 4.6 <redacted>
Co-authored-by: Oliver Simons <redacted>