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User Manual for NVIDIA Tesla Kepler K20 GPU Accelerator for Server Click to enlarge the picture
Contents of the user manual for the NVIDIA Tesla Kepler K20 GPU Accelerator
- Product category: Server Graphic Cards NVIDIA
- Brand: NVIDIA
- Description and content of package
- Technical information and basic settings
- Frequently asked questions – FAQ
- Troubleshooting (does not switch on, does not respond, error message, what do I do if...)
- Authorized service for NVIDIA Server Graphic Cards
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User manual for the NVIDIA Tesla Kepler K20 GPU Accelerator contain basic instructions
that need to be followed during installation and operation.
Before starting your appliance, the user manual should be read through carefully.
Follow all the safety instructions and warnings, and be guided by the given recommendations.
User manual is an integral part of any NVIDIA product,
and if it is sold or transferred, they should be handed over jointly with the product.
Following the instructions for use is an essential prerequisite for protecting
health and property during use, as well as recognition of liability on the part of the manufacturer
for possible defects should you make a warranty claim. Download an official NVIDIA user manual in which you will find instructions on how to install, use, maintain and service your product.
And do not forget – unsuitable use of a NVIDIA product will considerably shorten its lifespan!
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Product description The Tesla Kepler K20 GPU Accelerator for Server from nVIDIA is based on the nVIDIA Kepler compute architecture and powered by CUDA. It includes innovative technologies like Dynamic Parallelism and Hyper-Q that boost performance as well as power efficiency and deliver record application speeds for seismic processing, biochemistry simulations, weather and climate modeling, image, video and signal processing and more. - SMX (Streaming Multiprocessor)
- Telsa K20 features SMX technology which delivers up to three times more performance per watt compared to the SM in Fermi. It also delivers one petaflop of computing in just ten server racks.
- Dynamic Parallelism
- Dynamic Parallelism capability enables GPU threads to automatically spawn new threads. By adapting to the data without going back to the CPU, it greatly simplifies parallel programming. Additionally, it enables GPU acceleration of a broader set of popular algorithms like adaptive mesh refinement (AMR), fast multi-pole method (FMM) and multi-grid methods.
- Hyper-Q Technology
- The Hyper-Q feature enables multiple CPU cores to simultaneously utilize the CUDA cores on a single Kepler GPU. This dramatically increases GPU utilization, slashes CPU idle times and advances programmability-ideal for cluster applications that use MPI.
- ECC Memory Error Protection
- ECC memory meets the critical requirement for computing accuracy and reliability in data centers and super-computing centers. Both external and internal memories are ECC protected in Tesla K20.
- System Monitoring Feature
- Integrates the GPU subsystem with the host system's monitoring and management capabilities such as IPMI or OEM-proprietary tools. IT staff can now manage the GPU processors in the computing system using widely used cluster/grid management solutions.
- L1 and L2 Caches
- Accelerates algorithms such as physics solvers, ray-tracing and sparse matrix multiplication where data addresses are not known in advance.
- Asynchronous Transfer with Dual DMA Engines
- Turbo-charges system performance by transferring data over the PCIe bus while the computing cores are executing other data.
- Flexible Programming Environment with Broad Support for Programming Languages and APIs
- Choose OpenACC, CUDA toolkits for C, C++ or FORTRAN to express application parallelism and take advantage of the innovative Kepler architecture.
- GPU Computing Applications
- With more than one teraflop peak double precision performance, the GPU accelerator is ideal for the most aggressive high-performance computing workloads including climate and weather modeling, CFD, CAE, computational physics, biochemistry simulations, and computational finance.
In the Box NVIDIA Tesla Kepler K20 GPU Accelerator for Server 3-Year Limited Warranty Table of Contents
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Technical parametersNVIDIA K20 Specs | | | GPU | Kepler GK110 | | Interface | PCIe Gen2 ×16 | | CUDA Cores | 2496 | | Double Precision Floating Point | 1.17 Teraflops | | Single Precision Floating Point | 3.52 Teraflops | | | | Memory Type | GDDR5 | | Memory Size | 5 GB With ECC on, 12.5% of the GPU memory is used for ECC bits. So, for example, 6 GB total memory yields 5.25 GB of user available memory with ECC on. | | Memory Bandwidth | 208 Gb/s (ECC off) | | Memory Clock | 2.6 GHz | | Memory I/O | 320-bit | | Memory Configurations | 20 pieces of 64M ×16 | | | | Power Connectors | 8-pin PCIe
6-pin PCIe | | | | Board Power | 225 W | | Idle Power | 25 W | | Applications | CFD, CAE, financial computing, computational chemistry and physics, data analytics, satellite imaging, weather modeling | | System | Server and Workstations | | | | OS Supported | Windows Server 2012, 2008 R2 and 2008 64-bit (all editions)
Linux 64-bit
RHEL 5.4 Server
Ubuntu 9.10 Server
RHEL 4.8 Server
SLES 11 | | | | Package Weight | 2.35 lb | | Box Dimensions (LxWxH) | 11.9 x 7.0 x 3.0" |
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