The Kyoto University Graduate School of Medicine determined that a dual-socket Intel Xeon E5-2699v3 (Haswell architecture) chipset delivers better performance than an NVIDIA K40 GPU using 16-bit arithmetic (which doubles GPU performance) when training deep learning neural networks for computational drug discovery using the Theano framework. Theano is a Python library that lets researchers transparently run deep learning models on CPUs and GPUs. It does so by generating C++ code from the Python script for the destination architecture. The generated C++ code can also call optimized math libraries. The Kyoto University team recognized that the performance of the open source Theano C++ multi-core code could be significantly improved. They worked with Intel to improve Theano multicore performance using a dual-socket Intel Xeon processor based system as the next generation Intel Xeon Phi processors were not available at that time. The optimized performance improvement turned out to be significant and demonstrated that a dual-socket Haswell processor chipset can outperform an NVIDIA K40 GPU on deep learning training tasks. Read more at http://insidehpc.com/2016/07/superior-performance-commits-kyoto-university-to-cpus-over-gpus/
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