Enterprises today are using data science and machine learning to extract greater value and insight from their data assets. New, powerful data science workstations are aiding this trend by putting the power of data centers at the fingertips of individual scientists, analysts and engineers to run end-to-end data processing pipelines on large data sets more quickly.
As a leading provider of custom workstation, server and storage equipment, Thinkmate provides data science workstations powered by NVIDIA GPUs that can be 100% customized to the needs of any computing environment.
Data science teams require extraordinary computing performance to uncover the insights available through AI and deep learning. In the past, data science supercomputing was confined to the data center, severely limiting the experimentation needed to develop and test deep neural networks before launching training at scale.
In 2019, NVIDIA announced a reference architecture for a new class of data science workstations that could move data science processing out of the data center and into the hands of individuals, enabling them to spend less time waiting for access to resources and more time-solving problems.
NVIDIA technology powers data science workstations like the NVIDIA DGX Station, the world's fastest workstation for leading-edge AI development. The only workstations powered by four NVIDIA Tesla V100 Tensor Core GPUs, DGX systems deliver 500 teraFLOPs of AI power – the same as hundreds of CPU-based servers – allowing data scientists to experiment faster, iterate more frequently and produce results with less effort.
A DGX data science workstation can deliver:
Since 1986, Thinkmate has been a world-class provider of custom computing technology for customers in business, government, education and high-performance computing markets. Our cutting-edge technology and our commitments to exceptional customer service has helped us maintain a reputation as a leading white box server solutions provider.
Our collection of workstations powered by NVIDIA GPUs provides our customers with access to many options for a data science workstation. With massive parallel processing abilities, Thinkmate GPU workstations are built to deliver breakthrough performance and ultimate reliability for the world's most demanding applications.
Our data science workstations can be configured with up to 4 GPUs, up to 2 processors, and up to 2 TB of maximum RAM, with up to 8 drive bays. Workstations can be configured with NVIDIA Tesla GPUs such as the NVIDIA V100, P100, T4, GeForce RTX, NVIDIA Quadro, and NVIDIA Quadro RTX processors.
We also offer virtualized GPU technology powered by software like NVIDIA GRID vPC and GRID vApps, as well as a broad section of rackmount, high-density, cloud storage, nearline and NVMe storage server options.
Building a data science workstation or deep learning workstation at Thinkmate is quick and easy. Our online ordering system has more customizable options than any other system builder on the web. If you can't find exactly what you're looking for on our site, our expert technicians are happy to help you by phone, email or chat.
To build your workstation, begin by choosing one of our NVIDIA GPU-optimized base model workstations. Next, select from a long list of components for processors, memory, drives, GPU accelerators, NVIDIA NVLink bridges, controller cards, network cards, PCIe express storage cards, monitors, operating systems, and peripherals. The price of every component is clearly marked on the page and you'll see a total configured price at the top of the page along with the cost of your monthly payment if you choose to finance your workstation through Thinkmate. When you're satisfied with your build, you can add it to your order, request a formal quote, or submit your configuration for review by our knowledgeable computer technicians.
When you come Thinkmate to configure your data science workstation, you can expect:
A data science workstation is an individual computer that has the hardware, software and extreme computational horsepower to prepare, process and analyze massive sets of data. A data science workstation can process and analyze massive amounts of data faster than hundreds of CPU-based servers in a data center.
Data center workstations require multiple GPU processors for massive parallel processing, as well as large amounts of memory, hardware that is designed for photorealistic visualizations, and software that supports deep learning.