Exxact TensorEX 2U Server - 1x NVIDIA Grace CPU Superchip - TS2-120709051
The TensorEX TS2-120709051 is a 2U rack mountable server supporting 1x NVIDIA Grace CPU Superchip, up to 480 GB onboard LPDDR5X ram, and up to 4x PCI-E 5.0 x16 Double-Wide cards.
Training, building, and deploying Deep Learning and AI models can solve complex problems with less coding. Whether it's data collection, annotation, training, or evaluation, leverage the immense parallelism GPUs offer to parse, train, and evaluate at extremely high throughput. Process massive datasets faster with multi-GPU configurations to develop AI models that surpass any other form of computing.
Facilitate any stage of Scientific research, from data preparation and 2D Image Processing to conducting complex MD simulations. Leverage GPUs to speed up calculations and research and encourage the use of AI to solve complex problems Protein Folding, building new molecules, and exponentially accelerating genome sequencing.
Engineering and Product Design applications are notorious for their compute-intensive requirements. Your system should never hold you back from designing the next big thing. Leverage high core count CPUs, ample RAM, and the top-of-the-line GPUs to enable the most enjoyable design experience in CAD applications like Solidworks and simulation applications like ANSYS.
3D design, rendering, and real-time engines have solidified their place in media and entertainment, manufacturing, and architectural design. As digital assets get larger and more complex so should your system. Exxact curates the most competent workstation or server so you can focus on being creative with your designs.
NVIDIA's First Data Center ARM CPU
The NVIDIA Graceâ„¢ CPU delivers high performance, power efficiency, and high-bandwidth connectivity that can be used in diverse configurations for different data center needs. Built with 72 ARM Neoverse V2 CPU cores and 480GB of LPDDR5 memory, Grace delivers 53% more bandwidth at one-eighth the power per GB/s for optimal energy efficiency and bandwidth compared to traditional x86 CPUs.
About
The TensorEX TS2-120709051 is a 2U rack mountable server supporting 1x NVIDIA Grace CPU Superchip, up to 480 GB onboard LPDDR5X ram, and up to 4x PCI-E 5.0 x16 Double-Wide cards.
Training, building, and deploying Deep Learning and AI models can solve complex problems with less coding. Whether it's data collection, annotation, training, or evaluation, leverage the immense parallelism GPUs offer to parse, train, and evaluate at extremely high throughput. Process massive datasets faster with multi-GPU configurations to develop AI models that surpass any other form of computing.
Facilitate any stage of Scientific research, from data preparation and 2D Image Processing to conducting complex MD simulations. Leverage GPUs to speed up calculations and research and encourage the use of AI to solve complex problems Protein Folding, building new molecules, and exponentially accelerating genome sequencing.
Engineering and Product Design applications are notorious for their compute-intensive requirements. Your system should never hold you back from designing the next big thing. Leverage high core count CPUs, ample RAM, and the top-of-the-line GPUs to enable the most enjoyable design experience in CAD applications like Solidworks and simulation applications like ANSYS.
3D design, rendering, and real-time engines have solidified their place in media and entertainment, manufacturing, and architectural design. As digital assets get larger and more complex so should your system. Exxact curates the most competent workstation or server so you can focus on being creative with your designs.
NVIDIA's First Data Center ARM CPU
The NVIDIA Graceâ„¢ CPU delivers high performance, power efficiency, and high-bandwidth connectivity that can be used in diverse configurations for different data center needs. Built with 72 ARM Neoverse V2 CPU cores and 480GB of LPDDR5 memory, Grace delivers 53% more bandwidth at one-eighth the power per GB/s for optimal energy efficiency and bandwidth compared to traditional x86 CPUs.