[Perf] Remove +silu_and_mul from custom op list

[tjtanaavllm]

Purpose

This is to pick the best setup for silu_and_mul kernel and set it as default.

We have tested three kernels:

• torch inductor compiled silu_and_mul
• aiter.silu_and_mul
• vllm custom op silu_and_mul

Test Plan

Evaluate the performance on max concurrency 64 and large number of requests.

Test Result

max concurrency 64

Metric	aiter's	vLLM custom ops	torch inductor	Best
Request throughput (req/s)	1.78	1.77	1.78	aiter's / torch
Output token throughput (tok/s)	207.32	206.51	207.28	aiter's
Total token throughput (tok/s)	375.10	373.48	374.75	aiter's
Mean TTFT (ms)	3938.11	3714.86	4254.20	vLLM
Median TTFT (ms)	2386.74	2204.05	1977.58	torch
P99 TTFT (ms)	24368.01	24284.53	29484.65	vLLM
Mean TPOT (ms)	295.16	297.56	285.95	torch
Median TPOT (ms)	286.63	287.77	287.71	aiter's
P99 TPOT (ms)	527.57	462.26	491.60	vLLM

large number of requests

Metric	torch inductor	aiter's	Best
Benchmark duration (s)	372.85	372.47	aiter's
Request throughput (req/s)	2.68	2.68	Tie
Output token throughput (tok/s)	313.84	313.71	torch
Total token throughput (tok/s)	566.82	566.96	aiter's
Mean TTFT (ms)	132,404	132,119	aiter's
Median TTFT (ms)	119,012	119,541	torch
P99 TTFT (ms)	351,168	355,388	torch
Mean TPOT (ms)	2,034	2,042	torch
Median TPOT (ms)	2,113	2,156	torch
P99 TPOT (ms)	4,089	4,032	aiter's

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[zejunchen-zejun]

Great work @tjtanaavllm and we are also wondering which backends has the best performant fusion kernel. Your experiment helps a lot.
@xytpai You can discuss with tunjian for the performance of the fusion kernel here.