Revolutionary NVIDIA® Tesla™ high performance computing (HPC) solutions arm scientists, engineers and other technical professionals with the power to solve previously unsolvable problems. A dedicated, high performance GPU computing solution, Tesla brings supercomputing power to any workstation or server and to standard, CPU-based server clusters.
Key elements include:
- Industry's first massively multi-threaded architecture with a 128-processor computing core
- World's only C-language development environment for the GPU
- A suite of developer tools (C-compiler, debugger, performance profiler, optimized libraries)
- Largest ISV development community for GPU Computing applications
- Seamlessly able to fit into existing HPC environments
Tesla C870 GPU Computing Processor
The GPU Computing Processor transforms a standard workstation into a personal supercomputer.
Tesla D870 Deskside GPU Computing System
The Deskside GPU Computing System attaches to a workstation through a PCI Express adapter to create an expandable HPC system that works in tandem with multi-core CPUs.
Tesla S870 GPU Computing System
The GPU Computing System seamlessly fits into enterprise server clusters and scales to solve the most complex computing problems.
Image Courtesy of Evolved Machines
Power to Solve Complex Problems
Scientists and researchers benefit from the power of the massively parallel, computing architecture in Tesla solutions. This availability of supercomputing will unlock the answers to previously unsolvable problems in systems ranging from a workstation to server clusters.
Massively Parallel Performance
A massively multi-threaded processor mines large datasets to extract information and reach answers fast. Key features available on Tesla GPUs include the Thread Execution Manager to coordinate the concurrent execution of thousands of parallel computing threads and the Parallel Data Cache to enable those threads to share data easily.
Developer Community
NVIDIA is the catalyst for the largest GPU computing developer community. NVIDIA's interactive, on-line GPU developer community provides access to forums, educational materials, and additional resources and tools.
C for the GPU
The world's only C-language development environment for the GPU, the NVIDIA® CUDA™ software development kit includes a standard C compiler, hardware debugger tools, and a performance profiler for simplified application development.
Image Courtesy of University of Illinois at Urbana-Champaign
Compatible Solutions
As an industry-standard solution, Tesla easily fits into existing HPC environments. Available products include a GPU for users to upgrade their existing workstation, a deskside GPU computing system to add additional performance alongside a workstation, and a 1U rackmount GPU computing system for deployment within an enterprise data center.
| 
