Background and Motivation

Clumsy Origins

• Many new uses
  • Servers
  • Robotics
  • Game Dev
  • Running Linux
  • Presentations... :)

Current Javascript Uses

Performance

• asm.js
  • high performing subset of JS
• WebCL
  • GPU access in browser
• node-cuda
  • GPU access in NodeJS
• Typed Arrays

New Performance Requirements

var first = 5;
//By using a bitwise 
//operator, we make sure 
//that the value is 32-bit integer
var second = first | 0;

// Unsigned int array
var arr = new Uint32Array([21,31]);
console.log(arr[1]); // 31

// Float 32 bit array
var arr = new Float32Array([21,31]);
console.log(arr[1]); // 31

Speed

... but is it fast enough?

Is it good enough for number crunching?

• Represent patterns of numerical computations
  • Sparse Linear Algebra
  • N-body methods
  • Map Reduce
  • Dynamic Programming
  • Combinatorial logic
  • etc

Thirteen Dwarfs

Sequential Performance

Driving Questions

• Is performance of Javascript competitive with C?
• Do typed arrays improve the performance of Javascript?
• Does asm.js offer performance improvements over handwritten Javascript?

Configuration

• Native code 
  • C (compiled with gcc)

• Javascript
  • Handwritten
  • Typed arrays
  • asm.js
    • Transpiled from C using Emscripten

Browser Comparisons

JS and asm.js vs C - Chrome

16 out of 24 have a slowdown below 2x

No tests are more than 3x slower than C

Lavamd is 4x faster than C

Slowdowns are 1.62 and 1.35 for JS and asm.js, respectively

JS and asm.js vs C - Firefox

Only one asm.js benchmark has a slowdown higher than 2x

In 4 tests, at least one JS benchmark outperforms C

Slowdowns are 1.65 and 1.17 for JS and asm.js, respectively

JS and asm.js vs C - IE

Worse performance than other browsers

crc is 35x slower than C

Average slowdown is 3.11 and 2.18 for JS and asm.js in IE

JS and asm.js vs C - Safari

Suggests a performance optimization missed by Safari's JIT compiler

Average slowdown is 2.69 and 2.15 for JS and asm.js, respectively

crc and fft have a severe penalty in JS at 17x and 10x

Typed Arrays

Typed Arrays vs untyped (js-nota)

Speed up about 2x on average

back-prop speedup is over 16x

Multiple speed ups over greater than 4x

fft is slower.

Overall, speedups are similar across browsers

Observations

• Browser choice is significant in program speed
• When running numerical computation in the browser, also consider how the app will affect the browser overall
  • Chrome - one process per tab will have a minimal affect on other tabs
  • Firefox - long running Javascript computation can freeze the entire browser until it has finished

Parallel Performance

Comparing Parallelization performance boosts using OpenCL and WebCL

Background

• OpenCL
  • Parallel computing framework for C
• WebCL 
  • Standard bringing OpenCL to web
  • Allows for direct CPU/GPU access with JS

Driving Questions

• Does WebCL provide performance improvements in JS?
• Are the improvements with JS congruent with improvements of OpenCL (vs C)?

WebCL Speed up (Firefox)

OpenCL Speed up

WebCL vs OpenCL

Conclusions

• Asm.js and WebCL make Javascript competitive for numerical computation
• Performance can still vary a lot between browsers and JS interpreter implementations
• Performance optimizations
  • Using typed arrays provided a performance boost of about 2x across browsers
  • Asm.js further improved this by 15-30%
  • WebCL improvements are incongruent with OpenCL
  • WebCL still provides significant improvements over native JS

References

Khan, F., Foley-Bourgon, V., Kathrotia, S., Lavoie, E., & Hendren, L. (2014, October). Using JavaScript and WebCL for numerical computations: a comparative study of native and web technologies. In Proceedings of the 10th ACM Symposium on Dynamic languages (pp. 91-102). ACM.