Community Benchmark Dashboard -- compare ANE performance across Apple Silicon chips

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Built a community benchmark system and live dashboard to help compare Apple Neural Engine performance across different Apple Silicon chips (M1, M2, M3, M4, M5).

**Live Dashboard:** https://web-lac-sigma-61.vercel.app

**Fork with benchmark tooling:** https://github.com/dev-erik/ANE

# What it measures:

Benchmark | What it tells us |
|-----------|-----------------|
| **SRAM probe** | ANE SRAM capacity -- where weight spilling starts on your chip |
| **Peak TFLOPS** | Maximum achievable ANE compute via programmatic MIL |
| **Training (CPU cls)** | End-to-end training perf with CPU classifier |
| **Training (ANE cls)** | End-to-end training perf with ANE-offloaded classifier |

How to contribute your results:
```
# Run the benchmark (takes ~5 min)
bash scripts/run_community_benchmark.sh

# Or skip training if you don't have training data
bash scripts/run_community_benchmark.sh --skip-training
```
This outputs a JSON file in community_benchmarks/. Submit it via PR or paste it in an issue using the "Benchmark Submission" template.

We'd love to see results from M1, M2, M3, and M5 chips to build a cross-generation comparison of ANE capabilities.

See [`community_benchmarks/README.md`](https://github.com/dev-erik/ANE/blob/main/community_benchmarks/README.md) for full details on the JSON schema and submission process.

Start with community_benchmarks/README.md to review the JSON schema and submission process. Run bash scripts/run_community_benchmark.sh, or use --skip-training when training data is unavailable. Done means submitting the generated JSON from community_benchmarks/ through a pull request or the Benchmark Submission issue template.

Written by the indexing model from the issue text.