Files
wifi-densepose/vendor/ruvector/examples/rvf-kernel-optimized/src/main.rs

98 lines
3.0 KiB
Rust

//! CLI demo: build kernel -> embed -> verified ingest -> query -> report.
use anyhow::Result;
use rvf_runtime::{QueryOptions, RvfOptions, RvfStore};
use tracing::info;
fn main() -> Result<()> {
tracing_subscriber::fmt()
.with_max_level(tracing::Level::INFO)
.with_target(false)
.init();
let config = rvf_kernel_optimized::VerifiedRvfConfig::default();
info!("RVF Kernel-Optimized Example");
info!(
" dim={}, vectors={}, ebpf={}",
config.dim, config.vec_count, config.enable_ebpf
);
info!(" cmdline: {}", rvf_kernel_optimized::KERNEL_CMDLINE);
// Create temp store
let dir = tempfile::tempdir()?;
let store_path = dir.path().join("optimized.rvf");
let options = RvfOptions {
dimension: config.dim as u16,
..RvfOptions::default()
};
let mut store = RvfStore::create(&store_path, options)
.map_err(|e| anyhow::anyhow!("create store: {e:?}"))?;
// Stage 1: Embed kernel + eBPF
info!("--- Stage 1: Kernel + eBPF Embedding ---");
let kernel_result = rvf_kernel_optimized::kernel_embed::embed_optimized_kernel(
&mut store,
rvf_kernel_optimized::KERNEL_CMDLINE,
config.enable_ebpf,
config.dim as u16,
)?;
info!(
" kernel: {} bytes, eBPF: {} programs",
kernel_result.kernel_size, kernel_result.ebpf_programs
);
// Stage 2: Verified ingest
info!("--- Stage 2: Verified Vector Ingest ---");
let (stats, store_size) = rvf_kernel_optimized::verified_ingest::run_verified_ingest(
&mut store,
&store_path,
config.dim,
config.vec_count,
42, // deterministic seed
)?;
info!(" vectors: {}", stats.vectors_verified);
info!(" proofs: {}", stats.proofs_generated);
info!(" arena hit rate: {:.1}%", stats.arena_hit_rate * 100.0);
info!(
" cache hit rate: {:.1}%",
stats.conversion_cache_hit_rate * 100.0
);
info!(
" tiers: reflex={}, standard={}, deep={}",
stats.tier_distribution[0], stats.tier_distribution[1], stats.tier_distribution[2]
);
info!(" attestations: {}", stats.attestations_created);
info!(" time: {} us", stats.total_time_us);
// Stage 3: Query
info!("--- Stage 3: Query ---");
let query_vec: Vec<f32> = (0..config.dim as usize)
.map(|i| (i as f32) * 0.001)
.collect();
let results = store
.query(&query_vec, 5, &QueryOptions::default())
.map_err(|e| anyhow::anyhow!("query: {e:?}"))?;
for (i, r) in results.iter().enumerate() {
info!(" #{}: id={}, distance={:.4}", i + 1, r.id, r.distance);
}
// Summary
info!("--- Summary ---");
info!(" store size: {} bytes", store_size);
info!(
" kernel hash: {:02x}{:02x}{:02x}{:02x}...",
kernel_result.kernel_hash[0],
kernel_result.kernel_hash[1],
kernel_result.kernel_hash[2],
kernel_result.kernel_hash[3]
);
store.close().map_err(|e| anyhow::anyhow!("close: {e:?}"))?;
info!("done");
Ok(())
}