NVIDIA-powered Data Science Workstations help OEMs and leading data science software providers meet the growing demand for GPU-accelerated data science capabilities and offer powerful new options to customers conducting AI-based explorationDual, high-end Quadro RTX GPUs, comprising dual Quadro RTX 8000 and 6000 GPUs, uses the NVIDIA NVLink® interconnect technology and provides up to 260 teraflops of computing performance and 96GB of memory. This also provides the capacity and frequency range to manage extensive datasets, computations, and graphics. Built on the Linux OS and Docker containers, the data science software stack comprises the NVIDIA CUDA-X AI which is a collection of NVIDIA's GPU acceleration libraries, and that can stimulate deep learning, machine learning, and data analysis. The NVIDIA Tensor Core GPUs work with cuDNN, cuML, and TensorRT for efficient AI-based procedures. Moreover, the CUDA-X AI can be merged with deep learning structures like TensorFlow, PyTorch and MXNet, and cloud platforms like AWS, Microsoft Azure and Google Cloud. NVIDIA RAPIDS is a set of GPU-accelerated libraries analytics that enables data preparation, traditional machine learning and graph analytics. Moreover, partnering with Anaconda Inc., NVIDIA would provide Anaconda Distribution that can permit data scientists to perform Python/R, data science, AI and machine learning. Furthermore, the NVIDIA GPU-accelerated Data Science Workstation is enterprise-ready and offers optional support software and containers along with deep learning and machine learning structures.
NVIDIA-powered data science workstations - made possible by our (sic) new Turing Tensor Core GPUs and CUDA-X AI acceleration libraries - that (sic) allow data scientists to develop predictive models that can revolutionize their business - Jensen Huang, founder and CEO, NVIDIAThe best part is that data scientists can work locally.
The NVIDIA-powered data science workstation enables our data scientists to run end-to-end data processing pipelines on large datasets faster than ever. Leveraging RAPIDS to push more of the data processing pipeline to the GPU reduces model development time, which leads to faster deployment and business insights - Mike Koelemay, chief data scientist at Lockheed Martin Rotary & Mission SystemsNVIDIA partners and customers such as BlazingDB, BOXX, Charter Communications, Datalogue, Dell, Graphistry, H2O.ai, HP, Kinetica, Lenovo, MapR, MIT, and OmniSci, have published positive reviews supporting the NVIDIA workstations. Global workstation providers like Dell, HP, and Lenovo, as well as regional system builders like AMAX, APY, Azken Muga, BOXX, CADNetwork, Carri, Colfax, Delta, EXXACT, Microway, Scan, Sysgen, and Thinkmate, are immediately providing NVIDIA-powered systems.
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05 Jun 2020, 1:32 AM (GMT)