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NVIDIA Data Science Workstations

Designed to get results quick, develop and debug code on a comprehensive software stack

Data Science Workstations by 3XS

Organisations are increasingly investing in data science for deep learning and AI to improve their time to market, increase efficiency, provide a competitive edge and to unlock value from their combined data sets. Powered by high performance NVIDIA RTX professional GPU accelerators, Data Science Workstations by 3XS Systems have been created for data scientists to act as an entry-point for developing their data sets, prior to the requirement to graduate to enterprise-scale training hardware such as the DGX range of AI supercomputers.

NVIDIA-powered Data Science Workstations are tested and optimised with data science software built on NVIDIA CUDA-X AI, a collection of over 15 libraries that enable modern computing applications to benefit from NVIDIA’s GPU-accelerated computing platform. It includes RAPIDS data processing and machine learning libraries, NVIDIA optimised TensorFlow, PyTorch, Caffe and other leading data science software, providing enterprises with accelerated workflows for faster data preparation, model training and data visualisation.

Enterprise-Grade Hardware

NVIDIA Data Science Workstations are powered by enterprise-grade NVIDIA Quadro GPU-accelerators, ensuring
rapid processing and accuracy in your model development and training.

RTX A6000

Based on the Ampere architecture the RTX A6000 supports accelerated AI, real-time ray tracing and photorealistic VR. It features 10,752 CUDA cores, 336 Tensor cores and 84 RT cores, combined with 48GB of server-grade error code correcting (ECC) memory and PCIe 4 connectivity. Supporting four displays the RTX A6000 is a supremely powerful graphics card for specialist workstations.

Quadro GV100

Based on the previous generation Volta architecture the GV100 is specially engineered for high precision FP64 workloads. However, at lower levels of precision, i.e. FP32, FP16 and INT8 the newer RTX A6000 (see left) is far faster. The GV100 features 5,120 CUDA cores and 640 Tensor cores, combined with 32GB of server-grade error code correcting (ECC) memory


The NVIDIA GPU Cloud (NGC) provides researchers and data scientists with simple access to a comprehensive catalogue of GPU-optimised software tools for deep learning and high performance computing (HPC) that take full advantage of NVIDIA GPUs. The NGC container registry features NVIDIA tuned, tested, certified, and maintained containers for the top deep learning frameworks. It also offers third-party managed HPC application containers, NVIDIA HPC visualisation containers, and partner applications.

NGC empowers AI researchers with GPU-accelerated deep learning containers for TensorFlow, PyTorch, MXNet, TensorRT and more. The ready-to-run containers include the deep learning software, NVIDIA CUDA Toolkit, NVIDIA deep learning libraries and an operating system optimised for NVIDIA GPUs.

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Click the links below to view the range of RTX AI Development Workstations. We offer pre-configured systems that ready to go
or can custom build a system to your preferredspecification.

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