The new workstations are designed for heavy workloads that need huge memory and capable of enhancing performance of AI applications
Leadtek Research, a leading global provider of graphics, multimedia and communications technologies solutions, announced the launch of a series of WinFast RTX deep learning workstations that are designed for office desktop environment.
The latest workstations are developed for deep learning model training for natural language processing (NLP), image recognition and voice recognition. The workstations are powered by the latest NVIDIA Turing GPU architecture and the revolutionary RTX platform.
Focused on meeting the artificial intelligence (AI) and deep learning demands, these new workstations are incorporated with RT core that is designed for ray tracing and Tensor core for acceleration of AI. This provides flexible CPU and GPU configuration to allow the developer in speedily acquiring the required computing power.
Benefits for developers
Commenting on the development, Alan Wu, Product Manager, Leadtek said, “Leadtek has been actively involved in design and promotion of AI products. The workstations (WS1030, WS830 and WS730) launched this time are AI workstations designed for office desktop environment and cater to users that require different levels of computing power.”
“Its all-in-one Ubuntu software platform including popular deep learning frameworks such as NVIDIA DIGITS, Pytorch, Chainer and TensoFlow and workstation-level hardware integration, allows data scientists, AI researchers and developers to focus on the development of AI application systems without worrying about the compatibility of hardware and software, effectively improving productivity,” Wu added.
The new workstations are designed for heavy workloads that need huge memory and capable of enhancing performance of applications like AI model training, video and graphics analysis and high-performance computing.
The highly flexible design of the workstations offers choices of different computing processors such as Quadro RTX 4000, RTX 5000, RTX 6000 and RTX 8000, depending on the needs. The system is equipped with deep learning development environment and is preloaded and authenticated with required deep learning software components.