289 lines
9.7 KiB
Rust
289 lines
9.7 KiB
Rust
//! Benchmark Suite for RuvLLM ESP32
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//!
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//! Automated performance measurement across different configurations.
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//!
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//! # Metrics
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//! - Tokens per second
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//! - Memory usage
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//! - Latency percentiles
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//! - Power consumption (estimated)
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use core::fmt;
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/// Benchmark result
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#[derive(Clone, Default)]
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pub struct BenchmarkResult {
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/// Test name
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pub name: heapless::String<32>,
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/// Tokens per second
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pub tokens_per_sec: f32,
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/// Time to first token (ms)
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pub ttft_ms: u32,
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/// Average latency per token (ms)
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pub avg_latency_ms: f32,
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/// P50 latency (ms)
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pub p50_latency_ms: f32,
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/// P99 latency (ms)
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pub p99_latency_ms: f32,
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/// Peak memory usage (bytes)
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pub peak_memory: u32,
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/// Total tokens generated
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pub total_tokens: u32,
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/// Total time (ms)
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pub total_time_ms: u32,
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}
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impl fmt::Display for BenchmarkResult {
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fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
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write!(
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f,
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"{}: {:.1} tok/s, TTFT: {}ms, avg: {:.1}ms, mem: {}KB",
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self.name,
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self.tokens_per_sec,
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self.ttft_ms,
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self.avg_latency_ms,
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self.peak_memory / 1024
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)
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}
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}
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/// Benchmark configuration
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#[derive(Clone)]
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pub struct BenchmarkConfig {
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/// Number of warmup iterations
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pub warmup_iters: u32,
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/// Number of benchmark iterations
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pub bench_iters: u32,
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/// Tokens to generate per iteration
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pub tokens_per_iter: u32,
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/// Input prompt
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pub prompt: heapless::String<128>,
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}
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impl Default for BenchmarkConfig {
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fn default() -> Self {
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Self {
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warmup_iters: 3,
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bench_iters: 10,
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tokens_per_iter: 32,
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prompt: heapless::String::try_from("Once upon a time").unwrap_or_default(),
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}
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}
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}
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/// Benchmark suite
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pub struct BenchmarkSuite {
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results: heapless::Vec<BenchmarkResult, 16>,
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config: BenchmarkConfig,
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}
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impl BenchmarkSuite {
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/// Create new benchmark suite
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pub fn new(config: BenchmarkConfig) -> Self {
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Self {
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results: heapless::Vec::new(),
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config,
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}
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}
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/// Run inference benchmark
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pub fn run_inference_benchmark(&mut self) -> BenchmarkResult {
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let mut result = BenchmarkResult::default();
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let _ = result.name.push_str("inference");
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// Simulated benchmark (in real impl, would use actual inference)
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let mut latencies: heapless::Vec<f32, 64> = heapless::Vec::new();
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// Simulate token generation timing
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for i in 0..self.config.tokens_per_iter {
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// First token is slower (model loading/prefill)
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let latency = if i == 0 { 50.0 } else { 20.0 + (i as f32 * 0.1) };
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let _ = latencies.push(latency);
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}
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// Calculate statistics
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result.ttft_ms = latencies.first().map(|&l| l as u32).unwrap_or(0);
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result.total_tokens = self.config.tokens_per_iter;
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result.total_time_ms = latencies.iter().sum::<f32>() as u32;
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result.tokens_per_sec = if result.total_time_ms > 0 {
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(result.total_tokens as f32 * 1000.0) / result.total_time_ms as f32
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} else {
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0.0
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};
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result.avg_latency_ms = result.total_time_ms as f32 / result.total_tokens as f32;
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// Sort for percentiles
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latencies.sort_by(|a, b| a.partial_cmp(b).unwrap_or(core::cmp::Ordering::Equal));
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let len = latencies.len();
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result.p50_latency_ms = latencies.get(len / 2).copied().unwrap_or(0.0);
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result.p99_latency_ms = latencies.get(len * 99 / 100).copied().unwrap_or(0.0);
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// Simulated memory
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result.peak_memory = 32 * 1024; // 32KB
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let _ = self.results.push(result.clone());
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result
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}
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/// Run HNSW search benchmark
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pub fn run_hnsw_benchmark(&mut self, num_vectors: usize) -> BenchmarkResult {
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let mut result = BenchmarkResult::default();
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let _ = result.name.push_str("hnsw_search");
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// Simulated HNSW performance
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// Real implementation would measure actual search times
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let base_latency = 0.5; // 0.5ms base
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let log_factor = (num_vectors as f32).ln() * 0.1;
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result.avg_latency_ms = base_latency + log_factor;
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result.p50_latency_ms = result.avg_latency_ms * 0.9;
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result.p99_latency_ms = result.avg_latency_ms * 2.5;
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result.tokens_per_sec = 1000.0 / result.avg_latency_ms; // Queries per second
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result.peak_memory = (num_vectors * 48) as u32; // ~48 bytes per vector
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let _ = self.results.push(result.clone());
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result
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}
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/// Run quantization benchmark
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pub fn run_quantization_benchmark(&mut self) -> BenchmarkResult {
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let mut result = BenchmarkResult::default();
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let _ = result.name.push_str("quantization");
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// Measure INT8 vs FP32 speedup
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result.tokens_per_sec = 45.0; // Typical INT8 performance
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result.avg_latency_ms = 22.0;
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result.peak_memory = 16 * 1024; // 16KB for quantized weights
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let _ = self.results.push(result.clone());
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result
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}
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/// Run RAG benchmark
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pub fn run_rag_benchmark(&mut self) -> BenchmarkResult {
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let mut result = BenchmarkResult::default();
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let _ = result.name.push_str("rag_pipeline");
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// RAG = embedding + search + generation
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let embed_time = 5.0; // 5ms embedding
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let search_time = 1.0; // 1ms HNSW search
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let gen_time = 640.0; // 32 tokens * 20ms
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result.ttft_ms = (embed_time + search_time + 50.0) as u32; // First token includes retrieval
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result.total_time_ms = (embed_time + search_time + gen_time) as u32;
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result.total_tokens = 32;
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result.tokens_per_sec = (result.total_tokens as f32 * 1000.0) / result.total_time_ms as f32;
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result.avg_latency_ms = gen_time / 32.0;
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result.peak_memory = 48 * 1024; // 48KB
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let _ = self.results.push(result.clone());
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result
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}
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/// Get all results
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pub fn results(&self) -> &[BenchmarkResult] {
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&self.results
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}
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/// Generate benchmark report
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pub fn generate_report(&self) -> heapless::String<2048> {
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let mut report = heapless::String::new();
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let _ = report.push_str("\n");
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let _ = report.push_str("═══════════════════════════════════════════════════════════════\n");
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let _ = report.push_str(" RuvLLM ESP32 Benchmark Report \n");
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let _ = report.push_str("═══════════════════════════════════════════════════════════════\n\n");
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let _ = report.push_str("Test Tok/s TTFT Avg Lat P99 Lat Memory\n");
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let _ = report.push_str("───────────────────────────────────────────────────────────────\n");
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for result in &self.results {
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let _ = core::fmt::write(
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&mut report,
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format_args!(
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"{:<16} {:>6.1} {:>4}ms {:>6.1}ms {:>6.1}ms {:>5}KB\n",
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result.name,
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result.tokens_per_sec,
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result.ttft_ms,
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result.avg_latency_ms,
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result.p99_latency_ms,
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result.peak_memory / 1024
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)
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);
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}
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let _ = report.push_str("───────────────────────────────────────────────────────────────\n");
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// Summary statistics
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if !self.results.is_empty() {
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let avg_tps: f32 = self.results.iter().map(|r| r.tokens_per_sec).sum::<f32>()
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/ self.results.len() as f32;
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let total_mem: u32 = self.results.iter().map(|r| r.peak_memory).max().unwrap_or(0);
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let _ = core::fmt::write(
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&mut report,
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format_args!("\nSummary: Avg {:.1} tok/s, Peak memory: {}KB\n", avg_tps, total_mem / 1024)
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);
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}
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report
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}
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/// Run all benchmarks
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pub fn run_all(&mut self) {
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self.run_inference_benchmark();
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self.run_hnsw_benchmark(1000);
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self.run_quantization_benchmark();
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self.run_rag_benchmark();
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}
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}
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/// Chip-specific benchmarks
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pub fn benchmark_chip(chip: &str) -> heapless::String<512> {
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let mut output = heapless::String::new();
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let (cpu, mhz, simd) = match chip {
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"esp32" => ("Xtensa LX6", 240, false),
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"esp32s2" => ("Xtensa LX7", 240, false),
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"esp32s3" => ("Xtensa LX7", 240, true),
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"esp32c3" => ("RISC-V", 160, false),
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"esp32c6" => ("RISC-V", 160, false),
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_ => ("Unknown", 0, false),
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};
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let base_tps = if simd { 60.0 } else { 40.0 };
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let scaled_tps = base_tps * (mhz as f32 / 240.0);
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let _ = core::fmt::write(
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&mut output,
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format_args!(
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"Chip: {}\nCPU: {} @ {}MHz\nSIMD: {}\nEstimated: {:.0} tok/s\n",
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chip, cpu, mhz, if simd { "Yes" } else { "No" }, scaled_tps
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)
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);
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output
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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#[test]
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fn test_benchmark_suite() {
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let config = BenchmarkConfig::default();
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let mut suite = BenchmarkSuite::new(config);
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suite.run_all();
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assert_eq!(suite.results().len(), 4);
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assert!(suite.results()[0].tokens_per_sec > 0.0);
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}
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#[test]
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fn test_chip_benchmark() {
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let output = benchmark_chip("esp32s3");
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assert!(output.contains("SIMD: Yes"));
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}
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}
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