[ET-VK][matmul] Re-implement fp32/fp16 matmul and linear with tiled compute and blocked weight packing

Pull Request resolved: #18171

Replace all existing matmul/linear operator implementations with new ones built
from the ground up using a tiled compute approach. Delete all legacy
implementations (MatMulLegacy.cpp, LinearLegacy.cpp, addmm_optimized.glsl,
addmm_naive_*.glsl).

New matmul (mm/bmm/addmm):
- Single matmul.glsl shader handles mm, bmm, and addmm using FPInputTile,
  FPWeightTile, FPOutTile infrastructure from SDPA
- Adaptive tile size selection (TILE_M=4/2/1) based on GPU occupancy
- When mat2 is a constant tensor, automatically routes through the linear
  path for blocked weight packing

New linear:
- Custom 4OC×4IC blocked weight prepacking via pack_fp_linear_weight.glsl
  for optimal cache line utilization during tiled matmul
- Supports both transposed [N,K] and non-transposed [K,N] weights with
  batch dimension support
- Separate texture2d weight storage with automatic buffer fallback for
  large dimensions

Performance on Adreno 750 (fp16, vs legacy):
- Linear [4096,1024]x[256,1024]: 1.33x faster (texture)
- Linear [4096,64]x[128,64]: 2.67x faster (texture)
- BMM [1,4096,256]x[1,256,1024]: 1.63x faster (texture)

ghstack-source-id: 352051371
@exported-using-ghexport

Differential Revision: [D96488384](https://our.internmc.facebook.com/intern/diff/D96488384/)

Author: ssjia