Add Silicium vectorized analytical engine and c6a.4xlarge benchmark results - #2427

Summary

This pull request integrates Silicium, a vectorized columnar analytical database engine engineered in Rust, into the ClickBench suite, along with official 100M rows benchmark results measured on AWS c6a.4xlarge.

Architectural Highlights

• PostgreSQL v3 Wire Protocol: Native compatibility with standard psql (psql -h 127.0.0.1 -p 5433 -U postgres -d clickbench -c "$query").
• Full 105-Column Schema: Full schema coverage for all 105 columns declared in create.sql, including SELECT * projection queries (Q23, Q24).
• Decoupled Binary Distribution: In accordance with ClickBench standards for proprietary engines (pattern Umbra / ElosDB / CedarDB), no ELF binaries are committed into the Git tree. Evaluation binaries are downloaded and checksum-verified at cold start during install from the dedicated public release repository (silicium369-spec/silicium-clickbench).
• Standard Harness Interface: Conforms strictly to all ClickBench contracts (benchmark.sh, check, data-size, install, load, queries.sql, query, start, stop, template.json).

Benchmark Results (AWS c6a.4xlarge, 100M Rows, 105 Columns)

• Machine: AWS c6a.4xlarge (16 vCPUs, 32 GiB RAM, AMD EPYC 7R13 Milan, gp3 EBS).
• Cold Run (Sum of 43 Queries): 2.0581 s
• Hot Run (Sum of 43 Queries): 2.0236 s
• Data Footprint: 17,024,446,464 bytes (~15.8 GiB)
• Load Time: 286 seconds
• Results File: silicium/results/20261006/c6a.4xlarge.json

Verification

All result files have been validated with ClickBench official validate-results.py without errors.