Matt Hess
7730b6993f
- Create assembly/vm.ts with full RandomX VM implementation
- 256 instructions, 2048 iterations per hash
- Native u64/f64 operations in WebAssembly
- Full mode dataset lookups (2GB pre-computed)
- Update miner to use WASM VM for full mode
- mining-worker-asm.js uses pre-compiled WASM
- ~32 H/s per thread (4x faster than light mode)
- 8 threads achieves ~260 H/s
- Clean up redundant code
- Remove mining-worker-full.js (old JIT approach)
- Consolidate 'asm' mode into 'full' mode
85 lines
2.5 KiB
JavaScript
85 lines
2.5 KiB
JavaScript
/**
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* Benchmark: Interpreted VM vs Vendored JIT
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*/
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import { randomx_init_cache, randomx_create_vm } from '../src/randomx/vendor/index.js';
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import { RandomXVM } from '../src/randomx/vm.js';
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import { RandomXCache } from '../src/randomx/dataset.js';
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import { blake2b } from '../src/blake2b.js';
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const TEST_SEED = Buffer.from('33d64e8899b07bcc1234567890abcdef1234567890abcdef1234567890abcdef', 'hex');
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const TEST_INPUT = Buffer.from('This is a test input for RandomX hashing benchmark');
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async function benchmarkVendored(numHashes) {
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console.log(`\n=== Vendored JIT (${numHashes} hashes) ===`);
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const cache = randomx_init_cache(TEST_SEED);
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const vm = randomx_create_vm(cache);
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const start = performance.now();
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for (let i = 0; i < numHashes; i++) {
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const input = Buffer.concat([TEST_INPUT, Buffer.from([i])]);
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vm.calculate_hash(input);
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}
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const elapsed = performance.now() - start;
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console.log(`Time: ${elapsed.toFixed(2)}ms`);
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console.log(`Per hash: ${(elapsed / numHashes).toFixed(2)}ms`);
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console.log(`Hashrate: ${(numHashes / (elapsed / 1000)).toFixed(2)} H/s`);
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return elapsed;
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}
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async function benchmarkInterpreted(numHashes) {
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console.log(`\n=== Interpreted JS (${numHashes} hashes) ===`);
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// Initialize cache using the proper RandomXCache class
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const cache = new RandomXCache();
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console.log('Initializing cache (this may take a moment)...');
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const cacheStart = performance.now();
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cache.init(TEST_SEED);
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console.log(`Cache init: ${(performance.now() - cacheStart).toFixed(0)}ms`);
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const vm = new RandomXVM(cache);
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const start = performance.now();
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for (let i = 0; i < numHashes; i++) {
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const input = Buffer.concat([TEST_INPUT, Buffer.from([i])]);
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// Generate seed from input
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const seed = blake2b(input, 64);
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vm.initScratchpad(seed);
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vm.run(seed);
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const hash = vm.getFinalResult();
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}
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const elapsed = performance.now() - start;
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console.log(`Time: ${elapsed.toFixed(2)}ms`);
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console.log(`Per hash: ${(elapsed / numHashes).toFixed(2)}ms`);
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console.log(`Hashrate: ${(numHashes / (elapsed / 1000)).toFixed(2)} H/s`);
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return elapsed;
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}
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async function main() {
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console.log('RandomX VM Benchmark');
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console.log('====================');
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const numHashes = 5;
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try {
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await benchmarkVendored(numHashes);
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} catch (err) {
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console.log('Vendored error:', err.message);
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}
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try {
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await benchmarkInterpreted(numHashes);
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} catch (err) {
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console.log('Interpreted error:', err.message);
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}
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}
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main().catch(console.error);
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