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  • CUDA AND GPU COMPUTING
  • GPU APPLICATIONS
  • GPUS FOR SERVERS AND WORKSTATIONS

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Tesla Server Solutions
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WHY CHOOSE TESLA

TESLA SERVER SOLUTIONS

TESLA WORKSTATION SOLUTIONS
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BUY TESLA GPUS

TESLA SERVER GPU ACCELERATORS

Accelerate your scientific and technical computing with NVIDIA® Tesla® GPUs Accelerators. Now developers and researchers can enjoy faster performance and more accessibility with the latest generation of Tesla GPUs based on NVIDIA Kepler™, the world's fastest and most efficient high performance computing architecture. Try the NVIDIA® Tesla K20 GPU accelerators and speed up your application by up to 10X. Learn more by reading the K20-K20X Benchmark Report. (PDF 503KB) K20-K20X Benchmark Report

 

NVIDIA Tesla K20 GPU

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SELECTING THE RIGHT TESLA GRAPHICS CARD

Features Tesla K20X Tesla K20 Tesla K10 Tesla M2090 Tesla M2075
Number and Type of GPU 1 Kepler GK110 2 Kepler GK104s 1 Fermi GPU 1 Fermi GPU
GPU Computing Applications Seismic processing, CFD, CAE, Financial computing, Computational chemistry and Physics, Data analytics, Satellite imaging, Weather modeling Seismic processing, signal and image processing, video analytics Seismic processing, CFD, CAE, Financial computing, Computational chemistry and Physics, Data analytics, Satellite imaging, Weather modeling
Peak double precision floating point performance 1.31 Tflops 1.17 Tflops 190 Gigaflops
(95 Gflops per GPU)		 665 Gigaflops 515 Gigaflops
Peak single precision floating point performance 3.95 Tflops 3.52 Tflops 4577 Gigaflops
(2288 Gflops per GPU)		 1331 Gigaflops 1030 Gigaflops
Memory bandwidth
(ECC off)		 250 GB/sec 208 GB/sec 320 GB/sec
(160 GB/sec per GPU)		 177 GBytes/sec 150 GBytes/sec
Memory size (GDDR5) 6 GB 5 GB 8 GB
(4 GB per GPU)		 6 GB 6 GB
CUDA cores 2688 2496 3072
(1536 per GPU)		 512 448
 

* Note: With ECC on, 12.5% of the GPU memory is used for ECC bits. For example, 6 GB total memory yields 5.25 GB of user available memory with ECC on.

 
 

TESLA GPU SOFTWARE AND DRIVERS

NVIDIA recommends getting drivers for Tesla products from system OEMs. Please visit the NVIDIA Driver Downloads page for Tesla drivers.

Tesla products are supported under

  • Windows Server 2012, 2008 R2 and 2008 64-bit (all editions)
  • Windows 7 Support (Tesla M2070Q Only)
  • Linux 32-bit and 64-bit
    • RHEL 5.4 Server
    • Ubuntu 9.10 Server
    • RHEL 4.8 Server
    • SLES 11

TESLA GPU HARDWARE SUPPORT

Knowledgebase
NVIDIA knowledgebase available online 24x7x365 and contains answers to the most common questions and issues.

User Forums
Discuss Tesla products, talk about CUDA development, and share interesting issues, tips and solutions with your fellow NVIDIA Tesla users on the GPU computing forums.

RMA Requests
For RMA requests, replacements and warranty issues regarding your NVIDIA based product, please contact the OEM or reseller that you purchased it from.

 
 
Tesla 20-series GPUs Tesla 10-series GPUs Tesla 8-series GPUs
Tesla M2070 GPU module (PDF 413 KB) Adobe PDF icon Tesla S1070-400 system (PDF 258 KB) Adobe PDF icon Tesla S870 1U system (PDF 13.4 MB) Adobe PDF icon
Tesla M2050 GPU module (PDF 413 KB) Adobe PDF icon Tesla S1070-500 1U system (PDF 259 KB) Adobe PDF icon  
  Tesla M1060 GPU module  
 
 
CUDA and GPU Computing

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Tesla News and Reviews

Tesla GPUs for
Servers for Workstations

Why Choose Tesla
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CUDA on ARM Development Kit
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