Accelerate major deep learning frameworks! Achieve performance improvement and cost reduction.
The NVIDIA A100 Tensor Core GPU achieves unprecedented acceleration at various scales for AI, data analytics, and HPC, enabling it to tackle challenging computing problems worldwide. To accelerate workloads of different sizes, it can efficiently scale up to thousands of GPUs or be divided into seven independent GPU instances using the new NVIDIA Multi-Instance GPU technology. The third generation of Tensor Core technology provides faster computational precision for diverse workloads, reducing the time to gain insights and the time to market. 【Features】 ■ Accelerates workloads of all sizes ■ Divides into smaller instances using MIG ■ Easily meets acceleration needs of various scales ■ Ensures IT administrators can maximize the use of all GPUs in the data center ■ Equipped with high bandwidth memory, cache, and compute cores *For more details, please refer to the PDF document or feel free to contact us.
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【Other Features】 ■ Ability to expand access for all users and applications ■ Achieves 312 teraflops of deep learning performance ■ Realizes 20 times Tensor FLOPS ■ Capable of interconnecting up to 16 GPUs at a maximum of 600 gigabytes/second ■ Maximizes application performance on a single server *For more details, please refer to the PDF document or feel free to contact us.
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Elza Japan Co., Ltd. has been consistently engaged in the sale of visualization-related products, including professional and consumer GPU-equipped graphics boards for PCs, for over 20 years since its establishment in 1997. In recent years, we have also focused on server equipment and high-performance workstations for big data analysis, AI, and machine learning, leveraging the exceptional computing power of GPUs, as well as PCs for streamers represented by VTubers and high-end HMDs for professional XR applications.
![[Data] EI Core Material Handling Table](https://image.mono.ipros.com/public/product/image/1d5/2000857679/IPROS11556079992131222279.png?w=280&h=280)
