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Product Info
- Main
- What is GPU Computing?
- Why Choose Tesla
- Tesla Software Features
- Tesla Workstation Solutions
- Tesla Data Center Solutions
- Tesla RS Solutions
- Tesla BIO Workbench
- CUDA-Accelerated Applications
- CUDA Training and Consulting Services
- CUDA on ARM Development Kit
- Tesla Case Studies
- Product Literature
- Compatible Platforms
- Contact Us
- Where to Buy
Software and Applications
- Software Development Tools
Programming CUDA-enabled GPUs
- Industry Software Solutions
- GPU Cloud Computing Service Providers
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CUDA / Tesla Supercomputing Newsletter
Subscribe to the CUDA / Tesla Supercomputing Newsletter to receive regular updates about NVIDIA’s general purpose parallel computing architecture – how to leverage the GPU to solve many complex computational problems in a fraction of the time required on a CPU - as well as breaking news on NVIDIA’s Tesla Computing Solutions, and how they scale to solve the world’s most important computing challenges.
Relevant Links
Tesla Data Center Solutions
Tesla GPU Computing Solutions for Data Centers
Accelerate your science with NVIDIA® Tesla™ 20-series GPUs. A companion processor to the SPU in a server, Tesla GPUs speed up HPC applications by 10x. 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 in the data center:
Accelerate your science with NVIDIA® Tesla™ 20-series GPUs. A companion processor to the SPU in a server, Tesla GPUs speed up HPC applications by 10x. 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 in the data center:
- Integrated GPU-CPU servers with embedded Tesla M-class GPU modules (M2050 / M2070Q / M2070 / M2075 / M2090)
- Tesla S2050 1U system with 4 Tesla M2050 GPUs that connects to a host CPU server. See specifications document to learn how S2050 connects to host servers.
SELECTING THE RIGHT TESLA GPU
| Key Features | Applications | Where to Buy | |
| TESLA M2090 | |||
 Product brief
Download (412 KB PDF) |
Highest performance Fermi-based GPGPU
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| TESLA M2070/M2075 | |||
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Product brief
Download (412 KB PDF) |
High performance, large memory Fermi-based GPGPU
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| TESLA M2070Q | |||
Product brief
Download (412 KB PDF) |
Designed for remote graphics visualization and high performance computing in the data center
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Visualization Applications
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| TESLA M2050 | |||
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Product brief
Download (412 KB PDF) |
High performance Fermi-based GPGPU
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| TESLA S2050 | |||
Product brief
Download (435 KB PDF) |
1U system with 4 Tesla M2050s that can connect to existing CPU host servers
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SOFTWARE AND DRIVERS
NVIDIA recommends getting drivers for M-class products from system OEMs. Please visit the NVIDIA Driver Downloads page for the latest Tesla S2050 and M-class drivers.
Tesla M-class and S2050 products are supported under- Windows Server 2008 and 2008 R2 (all editions), 64-bit
- 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
Click here to learn more about drivers and cluster management software tools for Tesla data center products.
Click here to learn more about C, C++, Fortran, and OpenCL software development tools for Tesla GPUs.
PRODUCT SPECIFICATIONS
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* Note: With ECC on, 12.5% of the GPU memory is used for ECC bits. For example, 3 GB total memory yields 2.625 GB of user available memory with ECC on.
LEGACY PRODUCTS
Tesla 10-series products:- Tesla S1070-400 and Tesla S1070-500 1U systems (Product Brief)
- Tesla M1060 GPU module
- Tesla S870 1U system (System Specification Document)