20 Mar 2019
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NVIDIA introduces a new breed of high-performance workstations

By Jacques-Pierre (JP) Dumas

NVIDIA has teamed with the world’s leading OEMs and system builders to deliver powerful new workstations designed to help millions of data scientists, analysts and engineers make better business predictions faster and become more productive.

Purpose-built for data analytics, machine learning and deep learning, the systems provide the extreme computational power and tools required to prepare, process and analyze the massive amounts of data used in fields such as finance, insurance, retail and professional services.

NVIDIA-powered workstations for data science are based on a powerful reference architecture made up of dual, high-end NVIDIA Quadro RTXTM GPUs and NVIDIA CUDA-X AITM accelerated data science software, such as RAPIDSTM, TensorFlow, PyTorch and Caffe.

CUDA-X AI is a collection of libraries that enable modern computing applications to benefit from NVIDIA’s GPU-accelerated computing platform.

NVIDIA CEO Jensen Huang says, “Data science is one of the fastest growing fields of computer science and impacts every industry. Enterprises are eager to unlock the value of their business data using machine learning and are hiring at an unprecedented rate data scientists who require powerful workstations architected specifically for their needs.

“With our partners, we are introducing NVIDIA-powered data science workstations, made possible by our new Turing Tensor Core GPUs and CUDA-X AI acceleration libraries, that allows data scientists to develop predictive models that can revolutionize their business.”

NVIDIA GPU-Accelerated Data Science Workstation

Data science problems involve data on a massive scale and require large-scale processing capabilities. NVIDIA-powered data science workstations make it easy for scientists to wrangle, prep, train and deploy models quickly and accurately. 

Broad Ecosystem Support and Adoption

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 exploration.

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