feat(kernels): add GPU family fatbin support for custom_kernels

[cliu1003]

Support gfx115X-all as a multi-slice HIP_ARCHITECTURES family, with LlvmIrJit falling back from per-arch to family DLLs at runtime. Update Windows CI to build with --hip_arch gfx115X-all.

[github-actions]

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[github-actions]

L2 Accuracy Results (EP vs CPU)

Model	Combined L2	Total Elems	Skipped NaN/Inf
conv_test_hybrid	4.8668E-07	64	0
GroupQueryAttention_seq256	25.2366	2621440	0
MatMulNBits_o_seq128	259.906	368640	0
QMoE_seq128	34.957	368640	0

Threshold: 0.01 | Run: 4005 - Commit: 663d870

[github-actions]

MorphiZen EP Performance Results

Model	QPS	Session (s)	1st Infer (ms)	CPU%	Mem (MB)
full_model_seq128	7.50	6.37	364	3	1242
GroupQueryAttention_seq128	4436.76	1.73626	11	6	312
matmul_down_seq128	526.28	2.47	73	3	354

EPContext Export Performance

Model	QPS	Session (s)	1st Infer (ms)	CPU%	Mem (MB)
full_model_seq128	7.53	45.28	361	3	15590

EPContext Import Performance

Model	QPS	Session (s)	1st Infer (ms)	CPU%	Mem (MB)
full_model_seq128	7.53	9.64	362	3	15759

OGA Benchmark Results

Model	Warmup	Reps	Prompt Len	Gen Tokens	TTFT (ms)	TPS	Peak Mem (GB)	GPU Mem (GB)
gpt-oss-20b-webgpu-int4-rtn-block-32	1	5	128	128	160.1	80.6	1.33	13.56
Llama-3.1-8B-awq-g128-int4-asym-fp16-onnx-dml	1	5	128	128	239.9	43.0	1.22	6.43

OGA Wheel Smoke (Python benchmark_e2e.py)

Model	TTFT (ms)	TPS
Llama-3.1-8B-awq-g128-int4-asym-fp16-onnx-dml	196	42.1

Run: 4005 - Commit: 663d870