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Get your own supercomputer

Tesla GPU Computing Solutions for Data Centers
Supercharge your cluster with the Tesla family of GPU computing solutions. Deploy 1U systems from NVIDIA or hybrid CPU-GPU servers from OEMs that integrate NVIDIA® Tesla™ GPU computing processors.

When compared to the latest quad-core CPU, Tesla 20-series GPU computing processors deliver equivalent performance at 1/20th the power consumption and 1/10th the cost. Each Tesla GPU features hundreds of parallel CUDA cores and is based on the revolutionary NVIDIA® CUDA™ parallel computing architecture with a rich set of developer tools (compilers, profilers, debuggers) for popular programming languages APIs like C, C++, Fortran, and driver APIs like OpenCL and DirectCompute.

NVIDIA’s partners provide turnkey easy-to-deploy Preconfigured Tesla GPU clusters that are customizable to your needs. For 3D cloud computing applications, our partners offer the Tesla RS clusters that are optimized for running RealityServer with iray.

Available Tesla Products for Data Centers:
    - Tesla S2050/S2070
    - Tesla S1070
    - Tesla M1060

High Density GPU Systems
  
Integrated HYBRID CPU-GPU Servers
High Density GPU Systems   Integrated HYBRID CPU-GPU Servers
Tesla 1U Systems with 4 Tesla GPUs
  
OEM Servers with Integrated Tesla GPUs

SUPERCOMPUTING PERFORMANCE
– Revolutionary CUDA Architecture
– Up to 960 cores, and 4 Teraflops in a 1U. Massively    parallel processing
– 30x the compute performance of a standard    cluster
LOW POWER and LOW COST
– Supercomputing performance from a    small cluster
– Smaller cluster needs less power and    less cooling
READY FOR DEPLOYMENT
– Turnkey, ready to power up cluster with    software installed
– Program in C for Windows or Linux
– Available from resellers worldwide

The World’s Fastest 1U Server! Click here to learn more.

BUY A Tesla Preconfigured Cluster TODAY
Look for Tesla Preconfigured Clusters from the following NVIDIA Tesla
Preferred Providers and OEMs.

"GPUs have evolved to the point where many real-world applications are easily implemented on them and run significantly faster than on multi-core systems. Future computing architectures will be hybrid systems with parallel-core GPUs working in tandem with multi-core CPUs."

Prof. Jack Dongarra
Director of the Innovative Computing Laboratory
The University of Tennessee