Caffe-MPI version Released to Speedup Deep Learning

Sponsored Content by Inspur Recently, the historic battle of “Google AlphaGo vs Lee Se-dol” put Deep Learning under the spotlight. Caffe is a Deep Learning Framework, nowadays one of the fastest Convolutional Neural Networks (CNN) architectures. The high-performance MPI cluster version of Caffe was released by Inspur. The company also gave out the open source code to provide Deep Learning users a more convenient and efficient means of application. The original Caffe framework within a computing node plus a GPU was developed by UC Berkeley for the purpose of CNN training. Traditionally, CNN methods are utilized to import specific data pool for layer-by-layer training. Using this method, the machine can acquire the specific ability that is necessary. However, the imported data generally have massive volume, which requires dozens of days…


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