This week NVIDIA has formally announced the PCI-Express add-on card version of its flagship Tesla V100 HPC accelerator, based on its next-generation “Volta” GPU architecture.
The new NVIDIA Tesla V100 PCI-Express HPC Accelerator is based on the advanced 12 nm “GV100” silicon. The GPU is a multi-chip module with a silicon substrate and four HBM2 memory stacks. This design allows for significant improvements in performance and efficiency, making it a powerful tool for high-performance computing (HPC) applications.
Key Features and Specifications
Other features of the Tesla V100 PCI-Express HPC Accelerator include a total of 5,120 CUDA cores. These cores are designed to handle complex computational tasks, making the Tesla V100 ideal for scientific simulations, data analysis, and other demanding applications. Additionally, the accelerator includes 640 Tensor cores, which are specialized CUDA cores that accelerate neural-net building, says NVIDIA. These Tensor cores are particularly useful for deep learning and artificial intelligence (AI) applications, where they can significantly speed up the training of neural networks.
The Tesla V100 offers GPU clock speeds of around 1370 MHz, providing robust performance for a wide range of tasks. It also features a 4096-bit wide HBM2 memory interface, with 900 GB/s memory bandwidth. This high memory bandwidth ensures that data can be quickly and efficiently transferred to and from the GPU, reducing bottlenecks and improving overall performance. The 815 mm² GPU has a massive transistor count of 21 billion, highlighting the advanced engineering and technology that has gone into its design.
Applications and Availability
NVIDIA is currently in the process of taking orders from institutions and is expected to make the Tesla V100 PCI-Express HPC Accelerator available sometime later this year. This accelerator is expected to be in high demand among research institutions, universities, and companies involved in fields such as climate modeling, genomics, and financial modeling, where high computational power is essential.
HPE is also creating three HPC rigs with the cards pre-installed, explains the Tech Power Up website. These pre-configured systems will make it easier for organizations to deploy high-performance computing solutions without the need for extensive setup and configuration. By offering these pre-installed rigs, HPE aims to streamline the adoption of advanced computing technologies and make them more accessible to a broader range of users.
In addition to its use in traditional HPC applications, the Tesla V100 is also expected to play a significant role in the development of AI and machine learning technologies. The combination of CUDA and Tensor cores makes it an ideal platform for training complex neural networks and running sophisticated AI algorithms. This could lead to breakthroughs in areas such as autonomous vehicles, natural language processing, and medical diagnostics.
Overall, the NVIDIA Tesla V100 PCI-Express HPC Accelerator represents a significant advancement in GPU technology. Its combination of high performance, advanced features, and versatility makes it a valuable tool for a wide range of applications. As more organizations adopt this technology, we can expect to see continued innovation and progress in fields that rely on high-performance computing.
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