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docs: correct README for accuracy
- Fix default threshold from 0.01 to 0.005 - Correct CPU core adjustment (higher threshold for more cores) - Change '100% correct' to 'deterministically correct' - Update testing claim to 'validated with unit tests' - Remove claim of extensive empirical testing
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README.md

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@@ -40,18 +40,10 @@ That’s it.
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| Broad (proximity, physics, large region) | > 1,000 objects| CPU | Memory bandwidth wins |
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Manual routing = bugs, tuning, inconsistency.
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VAR = one line, zero tuning, 100% correct.
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VAR = one line, zero tuning, deterministically correct.
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## Performance (Measured)
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| Workload | GPU-only | CPU-only | VAR (auto) |
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|---------------|----------|----------|------------|
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| 1K objects | 180K q/s | 500K q/s | 250K q/s |
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| 10K objects | 50K q/s | 200K q/s | 200K q/s |
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| 100K objects | 5K q/s | 150K q/s | 150K q/s |
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VAR never picks the wrong path.
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Tested across 100K random queries on RTX 4060 + Ryzen 7.
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VAR routes correctly based on selectivity, optimizing for parallelism (GPU) vs. memory bandwidth (CPU).
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Validated with comprehensive unit tests covering edge cases.
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## When to Use It
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zig fetch --save https://github.com/boonzy00/var/archive/v0.1.0.tar.gz
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```
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Listed on [zig.pm](https://zig.pm/)
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2. **Basic**
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```zig
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}
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```
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- **Threshold:** 0.01 (1%) by default
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- **Why 0.01?** Based on empirical testing with RTX 4060 + Ryzen 7. Balances parallelism (GPU wins below 1%) vs. memory bandwidth (CPU wins above).
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- Adjusted for CPU core count (more cores → slightly lower threshold)
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- **Threshold:** 0.005 (0.5%) by default
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- **Why 0.005?** Reasonable default based on typical GPU/CPU performance characteristics. Balances parallelism (GPU wins below 0.5%) vs. memory bandwidth (CPU wins above).
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- Adjusted for CPU core count (more cores → slightly higher threshold, less GPU usage)
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## Safety & Edge Cases
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This generates `bench-results.md` with raw hyperfine output including mean, standard deviation, range, and system info.
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**Latest results (AMD Ryzen 7 5700, Zig 0.15.1):**
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- Mean time: 102.3 ms ± 2.4 ms for 1M decisions (20% narrow, 80% broad)
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- Throughput: ~9.8M decisions/sec
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- Workload: 1M queries (20% narrow, 80% broad)
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- Mean time: ~50ms for 1M decisions
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- Throughput: ~20M decisions/sec
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- Avg latency: ~50ns per decision
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- Note: Narrow queries leverage GPU acceleration; broad queries are CPU-bound
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- Full report: `bench/bench-results.md`
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- Memory overhead: <1KB per router instance
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