Slides from my talk at JSOxford on compiling performant C++ to JS for machine learning.

1. From C++ to JavaScript with Emscripten
Tom Nickson

2. asm.js
• Subset of JavaScript - so portable
• Predictable high performance
• Assembly code for the web

3. Emscripten
• Adds an asm.js backend to LLVM
• Any LLVM supported language can now target JS
• C++ supported by Clang

4. DEAR GOD WHY

5. ML = numerics
• Optimisation
• Linear algebra
• Other depres^H^H important things

6. LOOK AT THIS CODE
for (auto i = 0; i < 10000000; ++i) {
acc = acc + v[i] * v[i];
}
cout << acc << endl;
for (i=0; i<10000000; ++i) {
acc = acc + x[i] * x[i]
}
console.log(acc);

7. Benchmark: Sum numbers
• JS: 1 second
• Emscripten JS: 0.5 seconds
• C++ default: 0.1seconds

8. Matrix Multiplication
• Naïve algorithm has complexity O(n3)
• Order of memory access has major effect on speed
• Why write code when you don’t have to

9. ALSO THIS CODE
for (var r = 0; r < n; r++) {
for (var c = 0; c < m; c++) {
for (var i = 0; i < m; i++) {
v3[c*m + r] += v1[c*m + i] * v2[i*n + r];
}
}
}
for (auto r = 0; r < n; ++r) {
for (auto c = 0; c < m; ++c) {
for (auto i = 0; i < m; ++i) {
v3[r*m + c] += v1[r*m + i] * v2[i*n + c];
}
}
}

10. THAT CODE SUCKED
matrix<double> m3 = m1 * m2;
var matrix3 = matrix1.multiply(matrix2);

11. Benchmark: Matrix Multiplication
• Naïve JS: 25 Seconds
• Naïve Emscripten: 10.5 Seconds
• Sylvester JS: 46 Seconds
• dlib Emscripten: 7 Seconds

12. WHY SHOULD YOU CARE

13. Right tool for the job
• Better optimisers
• More and faster libraries
• Better debugging

14. complete
tom@osculate.it
@lordoftheengine