DP4MatMulNBits accuracy level 4 matmul for WebGPU EP

[sushraja-msft]

Description

This change implements accuracy level 4 - quantize A to int8 matmul for the WebGPU EP. The matmul kernel here uses DP4A for matrix multiplication, in order to keep the DP4A fed co-operative matrix multiplication is implemented which preloads the row/col into local variables before the multiplication operation.

Credits to @qjia7 for help with the quantizer shader.

Performance metrics on intel ADL/TGL GPU.

PS C:\onnxruntime> C:\model_benchmark\model_benchmark.exe -i C:\Phi-3.5-mini-instruct-onnx-web\Phi-3.5-mini-instruct-onnx-web -l 500
Batch size: 1, prompt tokens: 501, tokens to generate: 128
Prompt processing (time to first token):
        avg (us):       2.76762e+06
        **avg (tokens/s): 181.022**   <<< Prefill speed
        p50 (us):       2.74843e+06
        stddev (us):    41756.4
        n:              5 * 501 token(s)
Token generation:
        avg (us):       81500.7
        avg (tokens/s): 12.2698
        p50 (us):       81104.1
        stddev (us):    2961.31
        n:              635 * 1 token(s)
Token sampling:
        avg (us):       13.1836
        avg (tokens/s): 75851.9
        p50 (us):       12
        stddev (us):    6.47085
        n:              640 * 1 token(s)
E2E generation (entire generation loop):
        avg (ms):       13120
        p50 (ms):       13081.6
        stddev (ms):    114.689
        n:              5
Peak working set size (bytes): 5467533312
WebGPU device lost (2): Device was destroyed.

This kernel is 2.10x faster than its F16 counterpart for a 500 token prefill. Previous prefill record is 86tks/s.

In order to support devices with subgroup size 8/32, a no subgroup version of the same shader is included. Performance is slower than the subgroup version on ADL.

PS C:\onnxruntime> C:\model_benchmark\model_benchmark.exe -i C:\Phi-3.5-mini-instruct-onnx-web\Phi-3.5-mini-instruct-onnx-web -l 500 
Batch size: 1, prompt tokens: 501, tokens to generate: 128
Prompt processing (time to first token):
        avg (us):       4.11989e+06
        avg (tokens/s): 121.605
        p50 (us):       4.11847e+06
        stddev (us):    2147.48
        n:              5 * 501 token(s)
Token generation:
        avg (us):       81174.9
        avg (tokens/s): 12.3191
        p50 (us):       81301.1
        stddev (us):    2177.2
        n:              635 * 1 token(s)
Token sampling:
        avg (us):       14.7998
        avg (tokens/s): 67568.3
        p50 (us):       12.3
        stddev (us):    11.5481
        n:              640 * 1 token(s)
E2E generation (entire generation loop):
        avg (ms):       14431.1
        p50 (ms):       14433.8
        stddev (ms):    5.02473
        n:              5
Peak working set size (bytes): 5466480640
WebGPU device lost (2): Device was destroyed.

[guschmue]

perf and accuracy look good on Xe, NV and Metal