Matt Hess
714721874e
- Full RandomX implementation (light mode + full mode) - WASM-accelerated Argon2d cache init (37x faster than pure JS) - WASM-accelerated SuperscalarHash with SIMD support - Parallel dataset generation using worker threads (8 workers) - Light mode: ~4s init, Full mode: ~8min init - Mining utilities (difficulty calculation, block construction) - Progress callbacks for long-running operations Performance targets 2023+ platforms (WASM SIMD: Chrome 91+, Firefox 89+, Safari 16.4+, Node 16.4+)
45 lines
1.4 KiB
JavaScript
45 lines
1.4 KiB
JavaScript
#!/usr/bin/env node
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/**
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* Test RandomX light mode (cache only)
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*
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* Usage:
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* bun test/parallel-randomx.js
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* bun test/parallel-randomx.js --full # Full 2GB dataset mode
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*/
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import { LightDataset, ParallelDataset, getCpuCount } from '../src/randomx/parallel.js';
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const args = process.argv.slice(2);
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const fullMode = args.includes('--full');
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console.log(`CPU cores available: ${getCpuCount()}`);
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console.log(`Mode: ${fullMode ? 'Full (2GB dataset)' : 'Light (256MB cache)'}\n`);
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const key = new TextEncoder().encode('test key for randomx');
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const dataset = fullMode ? new ParallelDataset() : new LightDataset();
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try {
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const startTime = Date.now();
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await dataset.init(key);
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const elapsed = (Date.now() - startTime) / 1000;
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console.log(`\nInitialization completed in ${elapsed.toFixed(1)}s`);
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// Test that dataset items are accessible
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console.log('\nTesting dataset item access...');
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const item0 = dataset.getItem(0);
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const item1000 = dataset.getItem(1000);
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console.log(`Item 0: ${Array.from(item0.slice(0, 16)).map(b => b.toString(16).padStart(2, '0')).join('')}...`);
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console.log(`Item 1000: ${Array.from(item1000.slice(0, 16)).map(b => b.toString(16).padStart(2, '0')).join('')}...`);
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console.log('\nRandomX test complete!');
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} catch (err) {
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console.error('\nError:', err.message);
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console.error(err.stack);
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process.exit(1);
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} finally {
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dataset.destroy();
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}
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