WHAT IS GPU-ACCELERATED COMPUTING?
GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate deep learning, analytics, and engineering applications. Pioneered in 2007 by NVIDIA, GPU accelerators now power energy-efficient data centers in government labs, universities, enterprises, and small-and-medium businesses around the world. They play a huge role in accelerating applications in platforms ranging from artificial intelligence to cars, drones, and robots.
HOW GPUs ACCELERATE SOFTWARE APPLICATIONS
GPU-accelerated computing offloads compute-intensive portions of the application to the GPU, while the remainder of the code still runs on the CPU. From a user's perspective, applications simply run much faster.
Why Choose Tesla?
TESLA GPU ACCELERATORS FOR SERVERS
Accelerate your most demanding HPC, hyperscale, and enterprise data center workloads with NVIDIA® Tesla® GPU accelerators. Scientists can now crunch through petabytes of data up to 10x faster than with CPUs in applications ranging from energy exploration to deep learning. Plus, Tesla accelerators deliver the horsepower needed to run bigger simulations faster than ever before. For enterprises deploying VDI, Tesla accelerators are perfect for accelerating virtual desktops to any user, anywhere.
The NVIDIA Tesla P100 accelerators are the world's most advanced data center GPUs ever built, designed to boost throughput and save money for HPC and hyperscale data centers. Learn more
The NVIDIA Tesla K80 Accelerator dramatically lowers datacenter cost by delivering application performance with fewer, more powerful servers. Learn more
This accelerator is designed specifically for data centers that are virtualizing desktop graphics. It's a dual-slot PCI Express form factor for rack and tower servers capable of supporting 32 concurrent users. Find out more about GRID technology