feat: add Moore Threads multi-GPU Suite E and Suite B results

[Keke946]

Summary

• Add and validate multi-chip Suite E support for the Moore Threads vLLM-MUSA runner.
• Submit MTT S4000 Suite E scaling results across 1, 2, 4, and 8 GPUs.
• Add a four-GPU Suite B result for Meta-Llama-3-70B-Instruct.
• Add successor runner moorethreads_vllm_musa_6607740b, fixing MUSA chip-count detection when pymtml is unavailable.

Suite E results

GPUs	Best output throughput	Speedup vs. 1 GPU	Scaling efficiency
1	409.71 tok/s	1.00x	100.0%
2	498.36 tok/s	1.22x	60.8%
4	570.06 tok/s	1.39x	34.8%
8	530.78 tok/s	1.30x	16.2%

The four-GPU configuration gives the highest throughput; at eight GPUs, communication and synchronization overhead outweigh the added compute.

Suite B four-GPU result

• Hardware: 4 x MTT S4000 48 GB
• Model: Meta-Llama-3-70B-Instruct
• Precision: FP16
• Runner: moorethreads_vllm_musa_6607740b
• Run ID: 91e1cc05
• Accuracy: 0.33, valid
• Offline output throughput: 148.00 / 147.71 / 147.51 tok/s at client concurrency 8 / 32 / 128
• Online QPS 2, 5, 10, and 25 completed; all missed the 1 s TTFT p99 SLA, so max_valid_qps is 0

Validation

• Suite E completed at 1x, 2x, 4x, and 8x tensor parallel configurations.
• Suite B accuracy, offline, and online scenarios completed successfully.
• The Suite B submission passes validate_submission.py.
• Power telemetry is unavailable, so tokens/sec/watt is not reported.