NVIDIA TESLA | | High Performance Computing - Supercomputing with NVIDIA Tesla GPUs | | Experience the NVIDIA® Tesla™ 20-series family of GPUs, the fastest parallel processors for HPC. Based on the "Fermi" GPU computing architecture, NVIDIA Tesla GPUs are designed from the ground up for high performance computing (HPC) to deliver up to 10X higher application performance and are ideal for seismic processing, biochemistry simulations, weather and climate modeling, signal processing, computational finance, CAE, CFD, and data analysis. | NVIDIA Tesla Workstation Solutions | | NVIDIA Tesla 20-series GPU computing processors turn standard PCs and workstations into personal supercomputers. Based on the NVIDIA CUDA GPU architecture codenamed "Fermi", Tesla 20-series GPUs feature more than 500 gigaflops of double precision performance, 1 teraflop of single precision performance, ECC memory error protection, and L1 and L2 caches. Tesla 20-series GPGPU processors for workstations deliver cluster level performance right at your desk. | | | Key Features | Applications | |  | | High performance, large memory Fermi-based GPGPU
* 448 CUDA cores, 6 GB memory | | | > Reservoir simulation
> CAE (structural analysis)
> Molecular dynamics
> Numerical Analytics
> Computational Visualization (ray tracing) | | | | | | | Key Features | Applications | | | | High performance, large memory Fermi-based GPGPU
* 448 CUDA cores, 6 GB memory | | | > Reservoir simulation
> CAE (structural analysis)
> Molecular dynamics
> MATLAB | | | | | | | Key Features | Applications | |  | | High performance Fermi-based GPGPU
* 448 CUDA cores, 3 GB memory | | | > Bio-informatics
> Data analytics
> Application development |
| | | | | | Key Features | Applications | |  | | NVIDIA CUDA Technology
* 240 processor cores, 4 GB memory | | | > Fluid dynamics
> Molecular dynamics
> Financial analysis | | | | | | | | | NVIDIA Tesla Server Solutions | NVIDIA Tesla 20-series GPGPU processors deliver equivalent performance to a quad-core CPU at 1/10th the cost and 1/20th the power consumption. Based on the NVIDIA CUDA™ GPU architecture codenamed "Fermi", Tesla 20-series GPUs feature up to 665 gigaflops of double precision performance, 1 teraflop of single precision performance, ECC memory error protection, and L1 and L2 caches.
There are two ways to deploy Tesla GPGPUs:
• Integrated GPU-CPU servers with embedded Tesla M-class GPU modules ( M2090/ M2070 / M2050 )
• Tesla S2050 1U system with 4 Tesla M2050 GPUs that connects to a host CPU server. | | | Key Features | Applications | |  | | Highest performance Fermi-based
GPGPU
* 512 CUDA cores, 6 GB memory
* Highest memory bandwidth |
| | > Seismic processing
> CFD, CAE
> Supercomputing | | | | | | | Key Features | Applications | | | | Highest performance Fermi-based
GPGPU
* 512 CUDA cores, 6 GB memory
* 515 GFlops Peak DP |
| | > Seismic processing
> CFD, CAE
> Supercomputing
> Satellite imaging, GIS
> Weather modeling | | | | | | | Key Features | Applications | | | | High performance, large memory
Fermi-based GPGPU
* 448 CUDA cores, 6 GB memory |
| | > Seismic processing
> CFD, CAE
> Supercomputing
> Satellite imaging, GIS
> Weather modeling |
| | | | | | Key Features | Applications | | | | High performance Fermi-based
GPGPU
* 448 CUDA cores, 3 GB memory |
| | > Computational Finance
> Bio-informatics
> Molecular dynamics
> Data analysis | | | | | | | | | | Key Features | Applications | |  | | 1U system with 4 Tesla M2050s that can connect to existing CPU host servers
* Augment existing cluster with GPUs
* Increase GPU to CPU ratio (GPU density) | | | > Computational Finance
> Bio-informatics
> Molecular dynamics | | | | | | | | | |