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 RTX GPUs and NVIDIA CUDA-X AI accelerated data science software, such as RAPIDS, 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.
"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", stated Jensen Huang, founder and CEO of NVIDIA. "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 allow data scientists to develop predictive models that can revolutionize their business."
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. Features and benefits include:
1. Dual, high-end Quadro RTX GPUs: Powered by the latest NVIDIA Turing GPU architecture and designed for enterprise deployment, dual Quadro RTX 8000 and 6000 GPUs deliver up to 260 teraflops of compute performance and 96GB of memory using NVIDIA NVLink interconnect technology. Quadro RTX-powered data science workstations provide the capacity and bandwidth to handle the largest datasets and compute-intensive workloads as well as the graphics power required for 3D visualization of massive datasets, including VR.
2. Data science software stack built on the Linux operating system and Docker containers:
3. Enterprise ready: Tested and optimized in conjunction with workstation manufacturers to meet the needs of mission-critical enterprise deployments.
4. Optional software support: Offers peace of mind with NVIDIA-developed software and containers, including deep learning and machine learning frameworks.
By freeing data scientists to work locally, NVIDIA-powered data science workstations are the ideal complement to NVIDIAs data science portfolio.
"The NVIDIA-powered data science workstation enables our data scientists to run end-to-end data processing pipelines on large datasets faster than ever", stated Mike Koelemay, chief data scientist at Lockheed Martin Rotary & Mission Systems. "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."
NVIDIA-powered Data Science Workstations help OEMs and 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.
NVIDIA-powered systems for data scientists are available immediately from global workstation providers such as Dell, HP and Lenovo and regional system builders, including AMAX, APY, Azken Muga, BOXX, CADNetwork, Carri, Colfax, Delta, EXXACT, Microway, Scan, Sysgen and Thinkmate.