Viewing profile — kkjkok
kkjkok
HN member- Joined
- Fri, Jun 07, 2013, 1:58 AM UTC
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About kkjkok
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Recent public activity
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Comment #7078476
The most interesting part of that is the WHO of spread spectrum... Hedy Lamarr (movie star) and George Antheil (composer). Very fascinating that two major Hollywood players were ab…
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Comment #7065890
To be fair, the FFTW/CUDA thing is due to fundamentally different hardware architectures which drove design constraints for these types of libraries. FFTW was never meant to run on…
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Comment #6858952
I was (and still am) trying to use an already trained CIFAR10 net in a similar manner to DeCAF/ImageNet. Because CIFAR10 operates on 32x32 color images, I did the same thing for th…
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Comment #6857090
Check out this discussion - it may help you decide what card to get. There was also an email somewhere about how TITAN is currently not any faster than a 580, though no hard number…
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Comment #6857065
From what I understand, it is due to the programming specifics of the training algorithms, primarily being focused on exploiting certain registers and architecture features specifi…
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Comment #6856468
Question: do you/will you plan to support converting GPU nets to CPU, perhaps by keeping weights and architecture definition separate from PyCUDA dependent structures during serial…
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Comment #6856414
There is also DeCAF, which actually includes a way to load a pretrained ImageNet network based on cuda-convnet. I have had pretty recent success using this blob as preprocessing fo…
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Comment #6856393
The convolutional neural network code that pylearn2 and the Toronto group use is specifically tuned for GTX580 cards - users have reported factors of 2x-10x slowdown using Kepler s…
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Comment #6737219
Check out this paper: Practical recommendations for gradient-based training of deep architectures, Y. Bengio http://arxiv.org/abs/1206.5533 There is a section on weight initializat…
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Comment #6685201
Nope - the amount of numbers is in fact identical. The discrete Fourier transform has redundant information in bins above NFFT/2 (where NFFT is the size of the transform/number of …