The Tesla platform includes comprehensive system management tools to simplify GPU administration, monitor health and other metrics, and improve resource utilization and efficiencies.
The Tesla Platform Provides Powerful System Management Features This means that you can develop high-performance applications that use CUDA on your GeForce laptop, or on an Apple iMac or Macbook Pro, and deploy them on the fastest Tesla GPUs running in high-end workstations or even on clusters and supercomputers. The CUDA parallel computing platform is supported by all NVIDIA GPUs, from our mobile Tegra K1 GPU to the fastest GeForce desktop GPU, to our high-end Quadro and Tesla GPUs. But you don’t need to install your own HPC facilities to run on Tesla GPUs cloud-based applications can use CUDA for acceleration on the thousands of Tesla GPUs available in the Amazon cloud. Tesla is the only platform for accelerated computing on systems based on all major CPU architectures: x86, ARM64, and POWER. Tesla is Available on All Server Platforms: x86, ARM & POWER Here’s what you need to know about the Tesla Platform. This post gives an overview of the broad range of technologies, tools, and components of the Tesla Accelerated Computing Platform that are available to application developers. Tesla-accelerated applications are powered by CUDA, NVIDIA’s pervasive parallel computing platform and programming model, which provides application developers with a comprehensive suite of tools for productive, high-performance software development. These enable HPC professionals to easily deploy and manage Tesla accelerators in the data center.
The Tesla Accelerated Computing Platform provides advanced system management features and accelerated communication technology, and it is supported by popular infrastructure management software. The combination of the world’s fastest GPU accelerators, the widely used CUDA parallel computing model, and a comprehensive ecosystem of software developers, software vendors, and data center system OEMs make Tesla the leading platform for accelerating data analytics and scientific computing.
But it’s not just the GPU boards that make Tesla a great computing solution. They are used for parallel scientific, engineering, and technical computing, and they are designed for deployment in supercomputers, clusters, and workstations. You may already know NVIDIA Tesla as a line of GPU accelerator boards optimized for high-performance, general-purpose computing.
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