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  • Which GPU(s) to Get for Deep Learning - timdettmers. com
    NVIDIA’s standard libraries made it very easy to establish the first deep learning libraries in CUDA, while there were no such powerful standard libraries for AMD’s OpenCL This early advantage combined with strong community support from NVIDIA increased the size of the CUDA community rapidly
  • Tim Dettmers — Making deep learning accessible.
    Which GPU(s) to Get for Deep Learning: My Experience and Advice for Using GPUs in Deep Learning 2019-04-03 by Tim Dettmers 1,080 Comments Deep learning is a field with intense computational requirements and the choice of your GPU will fundamentally determine your deep learning experience
  • Which GPU(s) to Get for Deep Learning: My Experience and . . .
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  • Picking a GPU for Deep Learning – Slav
    Nvidia has been focusing on Deep Learning for a while now, and the head start is paying off Their CUDA toolkit is deeply entrenched It works with all major DL frameworks — Tensoflow, Pytorch, Caffe, CNTK, etc As of now, none of these work out of the box with OpenCL (CUDA alternative), which runs on AMD GPUs
  • Which GPU(s) to Get for Deep Learning | Hacker News
    tensor 11 months ago The problem is that a month of GPU time on a cluster can buy you the hardware itself If you are doing serious deep learning work it's just not cost effective at this point If the costs come down by half or more, it may start looking viable for people who need a lot of resources
  • [D] Which GPU(s) to Get for Deep Learning: My Experience . . .
    gpu's support some framework so that their computation power can be used for generic computing, OpenCL and CUDA are the popular ones, of these two CUDA is more popular and matured in deep learning field, as more DL libraries support CUDA and CUDA is from NVIDIA, AMD cards don't support it
  • Mesin Belajar: Which GPU for Deep Learning
    Excited by what deep learning can do with GPUs I plunged myself into multi-GPU territory by assembling a small GPU cluster with InfiniBand 40Gbit s interconnect I was thrilled to see if even better results can be obtained with multiple GPUs
  • [D] Which GPU(s) to Get for Deep Learning : MachineLearning
    I think the problem here is that there's a mix of timeless advice (why GPUs are so good for deep learning's big matrix multiplications, calculating number of parameters in a convolutional net, the basic tradeoffs of performance, the key requirements of fast IO between the GPU and CPU beyond just raw FLOPS, why Nvidia is the only game in town for the past 7 years the foreseeable future, what the total cost of ownership is including electricity costs, what sort of hardware expenses one has


















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