Merge commit 'd803bfe2b1fe7f5e219e50ac20d6801a0a58ac75' as 'vendor/ruvector'

vendor/ruvector/examples/onnx-embeddings-wasm/test-parallel.mjs

@@ -0,0 +1,121 @@
+#!/usr/bin/env node
+/**
+ * Benchmark: Sequential vs Parallel ONNX Embeddings
+ */
+import { cpus } from 'os';
+import { ParallelEmbedder } from './parallel-embedder.mjs';
+import { createEmbedder } from './loader.js';
+
+console.log('🧪 Parallel vs Sequential ONNX Embeddings Benchmark\n');
+console.log(`CPU Cores: ${cpus().length}`);
+console.log('='.repeat(60));
+
+// Test data - various batch sizes
+const testTexts = [
+    "Machine learning is transforming technology",
+    "Deep learning uses neural networks",
+    "Natural language processing understands text",
+    "Computer vision analyzes images",
+    "Reinforcement learning learns from rewards",
+    "Generative AI creates new content",
+    "Vector databases enable semantic search",
+    "Embeddings capture semantic meaning",
+    "Transformers revolutionized NLP",
+    "BERT is a popular language model",
+    "GPT generates human-like text",
+    "RAG combines retrieval and generation",
+];
+
+async function benchmarkSequential(embedder, texts, iterations = 3) {
+    const times = [];
+    for (let i = 0; i < iterations; i++) {
+        const start = performance.now();
+        for (const text of texts) {
+            embedder.embedOne(text);
+        }
+        times.push(performance.now() - start);
+    }
+    return times.reduce((a, b) => a + b) / times.length;
+}
+
+async function benchmarkParallel(embedder, texts, iterations = 3) {
+    const times = [];
+    for (let i = 0; i < iterations; i++) {
+        const start = performance.now();
+        await embedder.embedBatch(texts);
+        times.push(performance.now() - start);
+    }
+    return times.reduce((a, b) => a + b) / times.length;
+}
+
+async function main() {
+    try {
+        // Initialize sequential embedder
+        console.log('\n📦 Loading model for sequential test...');
+        const seqEmbedder = await createEmbedder();
+        console.log('✅ Sequential embedder ready\n');
+
+        // Warm up
+        seqEmbedder.embedOne("warmup");
+
+        // Initialize parallel embedder
+        console.log('📦 Initializing parallel embedder...');
+        const parEmbedder = new ParallelEmbedder({ numWorkers: Math.min(4, cpus().length) });
+        await parEmbedder.init();
+
+        // Benchmark different batch sizes
+        for (const batchSize of [4, 8, 12]) {
+            const texts = testTexts.slice(0, batchSize);
+
+            console.log(`\n${'='.repeat(60)}`);
+            console.log(`📊 Batch Size: ${batchSize} texts`);
+            console.log('='.repeat(60));
+
+            // Sequential benchmark
+            console.log('\n⏱️  Sequential (single-threaded)...');
+            const seqTime = await benchmarkSequential(seqEmbedder, texts);
+            console.log(`   Time: ${seqTime.toFixed(1)}ms`);
+            console.log(`   Per text: ${(seqTime / batchSize).toFixed(1)}ms`);
+
+            // Parallel benchmark
+            console.log('\n⏱️  Parallel (worker threads)...');
+            const parTime = await benchmarkParallel(parEmbedder, texts);
+            console.log(`   Time: ${parTime.toFixed(1)}ms`);
+            console.log(`   Per text: ${(parTime / batchSize).toFixed(1)}ms`);
+
+            // Speedup
+            const speedup = seqTime / parTime;
+            const icon = speedup > 1.2 ? '🚀' : speedup > 1 ? '✅' : '⚠️';
+            console.log(`\n${icon} Speedup: ${speedup.toFixed(2)}x`);
+        }
+
+        // Verify correctness
+        console.log(`\n${'='.repeat(60)}`);
+        console.log('🔍 Verifying correctness...');
+        console.log('='.repeat(60));
+
+        const testText = "Vector databases are awesome";
+        const seqEmb = seqEmbedder.embedOne(testText);
+        const parEmb = await parEmbedder.embedOne(testText);
+
+        // Compare embeddings
+        let diff = 0;
+        for (let i = 0; i < seqEmb.length; i++) {
+            diff += Math.abs(seqEmb[i] - parEmb[i]);
+        }
+        const avgDiff = diff / seqEmb.length;
+        console.log(`\nEmbedding difference: ${avgDiff.toExponential(4)}`);
+        console.log(avgDiff < 1e-6 ? '✅ Embeddings match!' : '⚠️ Embeddings differ');
+
+        // Cleanup
+        await parEmbedder.shutdown();
+        console.log('\n✅ Benchmark complete!');
+
+    } catch (error) {
+        console.error('❌ Error:', error.message);
+        console.error(error.stack);
+        process.exit(1);
+    }
+}
+
+main();