Inspur Incorporates Artificial Intelligence to Offer Real-time Object Detection Capability for Enterprises
SALT LAKE, UT: Inspur announces the release of D1000 with deep learning capability to confer high-performance computing solution in enterprises. D1000, powered by NVIDIA Tesla GPU, is capable of recognising face, picture and object with its artificial intelligence feature.
D1000 is built with Caffe-MPI and 6 node designs with each node configuring two CPUs and four Tesla M40 GPUs. It can achieve efficiency of 2000 images per second with GoogLeNet training and helps to increase
the network efficiency to 78 percent.
Caffe-MPI is an open-source deep learning framework that supports distributed cluster expansion and incorporates higher computational efficiency. It further support programming for Python, MATLAB, and other interfaces. The node efficiency of Caffe-MPI increases to 72 percent with high scalability in the deep learning process.
"Inspur provides customers with out of the box deep learning solutions and consistent service from beginning to end," says Mr. Zhang. The Inspur D1000 provides easy operation of product deployment by integrating Inspur's optimized high-performance computing cluster hardware, Caffe-MPI parallel computing framework and dependency library, fully tested OS and CUDA environment and Inspur ClusterEngine (which is a cluster management and dispatching platform). TheD1000 can achieve the integration of hardware and software in the production line installation and configuration.