Deep Learning Workstations

Deep Learning Workstations by 3XS can be evaluated online as a Proof of Concept

Deep Learning 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 GPU accelerators, Deep Learning 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.

Data Science Workstations support NVIDIA-optimised versions of popular DL and AI frameworks. This makes them software compatible with NVIDIA’s DGX range, providing a seamless workflow from model development to training at scale.

Integrated with GPU-Accelerated Software

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.

AI Ideation Workshops with Scan & NVIDIA

Join us for a day long workshop to evaluate your current AI strategy, goals and needs

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Cutting Edge Hardware

3XS Deep Learning Workstations are powered by NVIDIA RTX GPU-accelerators, ensuring rapid processing and accuracy in your model development and training.

GeForce RTX 3080

Based on the Ampere architecture the high-end RTX 3080 has 8704 CUDA cores, 272 Tensor cores, 68 RT cores plus 10GB of memory.

GeForce RTX 3090

Based on the Ampere architecture the ultra-high-end RTX 3090 has 10496 CUDA cores, 328 Tensor cores, 82 RT cores plus 24GB of memory enabling you to work with larger datasets.

RTX A6000

Based on the Ampere architecture the workstation RTX A6000 GPU has 10,752 CUDA cores, 336 Tensor cores, 84 RT cores plus 48GB of GDDR6 ECC memory.

The NVIDIA GPU Cloud

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, and NVIDIA optimises the complete software stack to take maximum advantage of NVIDIA Volta and Turing powered GPUs. The containers are tuned, tested, and certified by NVIDIA to run on select NVIDIA TITAN and NVIDIA Quadro GPUs, NVIDIA DGX Systems, and supported NVIDIA GPUs on Amazon EC2, Google Cloud Platform, Microsoft Azure, and Oracle Cloud Infrastructure.

NVIDIA Data Science Workstation Partner

Scan is an Elite Solution Provider for NVIDIA DGX Systems and has a dedicated AI team including data scientists to support our Data Science Workstations.