6 ms·

I can't see how the 'fast' claim is quantified.

toxicFork 11y ago
It's the .js port of FANN (Fast Artificial Neural Network) : http://leenissen.dk/fann/wp/ http://leenissen.dk/fann/wp/ > Fast (up to 150 times faster execution than other libraries)
- the8472 11y ago
  > up to
  - toxicFork 11y ago
    Sure, but the case for this prject isn't "Neural network implementation in javascript that's 'fast'". It's "FANN".js, where FANN expands to "Fast Artificial Neural Network", and the c implementation of FANN was probably the fastest when it was created. Conclusion: FANN.js is "the js port of FANN".
    - the8472 11y ago
      The F stands for Fast, and I don't even see any proof for their claim to fastness in the C version.
      - toxicFork 11y ago
        http://prdownloads.sourceforge.net/fann/fann_doc_complete_1.0.pdf?download http://prdownloads.sourceforge.net/fann/fann_doc_complete_1.... This one seems to have some information under "performance analysis". I'm not assuming it's correct, but go ahead and research further if you like, rather than quoting parts of my quote.
        the8472 11y ago
        Besides the fann library, I will benchmark Jet's Neural Library [Heller, 2002] (hereafter known as jneural) and Lightweight Neural Network [van Rossum, 2003] (hereafter known as lwnn). I have made sure that all three libraries have been compiled with the same compiler and the same compile-options. I have downloaded several other ANN libraries, but most of them had some problem making them difficult to use. Either they where not libraries, but programs [Anguita, 1993], [Zell, 2003], they could not compile [Software, 2002], or the documentation was so inadequate that is was not possible to implement the features needed in the benchmark [Darrington, 2003]. Even though I will only benchmark two libraries besides the fann library, I still think that they give a good coverage of the different libraries which are available. I will now briefly discuss the pros and cons of these two libraries. Yeah, so the author picked two simple, "easy to use" NN libraries to benchmark against, had trouble with others and just dropped them and then claimed it's fast because it performed "up to" 140 times faster than one of those two libraries. Seems kinda like a "get a paper out" work that is technically correct but doesn't measure up to real world standards. Real implementations would use vectorized math, math libraries with hand-optimized assembly or run straight on the GPU.
the8472 11y ago
Browsers don't support WebCL yet and their asm.js is single-threaded. And their auto-vectorization abilities also might be questionable. I don't see how it could possibly compete with things NNs running on a GPU. "Fast" might simply refer to efficient algorithms implemented in C?
- thomasfoster96 11y ago
  Browsers will probably never support WebCL.
  - ericjang 11y ago
    Why do you think so?
    - thomasfoster96 11y ago
      The WebCL spec has been finished for well over a year now, and was fairly stable for a while before that, yet no browsers have implemented it. Mozilla has publicly stated they aren't interested and are going with WebGL 2.0 instead.
onion2k 11y ago
The 'fast' in the title isn't really a claim about the JS version; it comes from the library that was emscriptened - http://leenissen.dk/fann/wp/ http://leenissen.dk/fann/wp/ - it's 'fast' in the sense that it uses efficient algorithms rather than it's actually fast.

It's the .js port of FANN (Fast Artificial Neural Network) : http://leenissen.dk/fann/wp/ http://leenissen.dk/fann/wp/ > Fast (up to 150 times faster execution than other libraries)

the8472 11y ago
> up to
- toxicFork 11y ago
  Sure, but the case for this prject isn't "Neural network implementation in javascript that's 'fast'". It's "FANN".js, where FANN expands to "Fast Artificial Neural Network", and the c implementation of FANN was probably the fastest when it was created. Conclusion: FANN.js is "the js port of FANN".
  - the8472 11y ago
    The F stands for Fast, and I don't even see any proof for their claim to fastness in the C version.
    - toxicFork 11y ago
      http://prdownloads.sourceforge.net/fann/fann_doc_complete_1.0.pdf?download http://prdownloads.sourceforge.net/fann/fann_doc_complete_1.... This one seems to have some information under "performance analysis". I'm not assuming it's correct, but go ahead and research further if you like, rather than quoting parts of my quote.
      - the8472 11y ago
        Besides the fann library, I will benchmark Jet's Neural Library [Heller, 2002] (hereafter known as jneural) and Lightweight Neural Network [van Rossum, 2003] (hereafter known as lwnn). I have made sure that all three libraries have been compiled with the same compiler and the same compile-options. I have downloaded several other ANN libraries, but most of them had some problem making them difficult to use. Either they where not libraries, but programs [Anguita, 1993], [Zell, 2003], they could not compile [Software, 2002], or the documentation was so inadequate that is was not possible to implement the features needed in the benchmark [Darrington, 2003]. Even though I will only benchmark two libraries besides the fann library, I still think that they give a good coverage of the different libraries which are available. I will now briefly discuss the pros and cons of these two libraries. Yeah, so the author picked two simple, "easy to use" NN libraries to benchmark against, had trouble with others and just dropped them and then claimed it's fast because it performed "up to" 140 times faster than one of those two libraries. Seems kinda like a "get a paper out" work that is technically correct but doesn't measure up to real world standards. Real implementations would use vectorized math, math libraries with hand-optimized assembly or run straight on the GPU.

the8472 11y ago

Browsers don't support WebCL yet and their asm.js is single-threaded. And their auto-vectorization abilities also might be questionable. I don't see how it could possibly compete with things NNs running on a GPU. "Fast" might simply refer to efficient algorithms implemented in C?

thomasfoster96 11y ago
Browsers will probably never support WebCL.
- ericjang 11y ago
  Why do you think so?
  - thomasfoster96 11y ago
    The WebCL spec has been finished for well over a year now, and was fairly stable for a while before that, yet no browsers have implemented it. Mozilla has publicly stated they aren't interested and are going with WebGL 2.0 instead.

onion2k 11y ago

The 'fast' in the title isn't really a claim about the JS version; it comes from the library that was emscriptened - http://leenissen.dk/fann/wp/ http://leenissen.dk/fann/wp/ - it's 'fast' in the sense that it uses efficient algorithms rather than it's actually fast.