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  • Tesla K20X
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Tesla K20XTesla K20X
Part No. TCSCK20X-PB


Where To Buy For More Information
  • Overview

    Tesla K20X is ideal for delivering record acceleration and more efficient compute performance for big data applications in fields including seismic processing; computational biology and chemistry; weather and climate modeling; image, video and signal processing; computational finance, computational physics; CAE and CFD; and data analytics.
    Designed for double-precision applications across the broader supercomputing market, the Tesla K20X delivers over 1.31 TFlops peak double-precision.


    Kepler based Tesla GPU Accelerators are also available for workstations.
    PNY provides unsurpassed service and commitment to its professional graphics customers offering: 3 year warranty, pre- and post-sales support, dedicated Quadro Field Application engineers and direct tech support hot lines.

  • Specifications
    TESLA K20X - PRODUCT SPECIFICATIONS
       
    CUDA Parallel Processing Cores 2688
    Interface 320-bit
    Frame Buffer Memory 6 GB GDDR5
    Memory Bandwidth 250 GBytes/sec
    Displau Connectors None
    Max. Power Consumption 225 W
    Power Connectors (2) x 6-pin PCI Express power connectors  
    Graphics Bus PCI Express 2.0 x16
    Form Factor 110 mm (H) x 265 mm (L) - Dual Slot
    Thermal Solution Passive
    Peak double precision floating point performance (board) 1.31 teraflops
    Peak single precision floating pointperformance (board) 3.95 teraflops
    Number of GPUs 1 x GK110
    GPU computing applications CFD, CAE, financial computing, computational chemistry and physics, data analytics, satellite imaging, weather modeling
    Architecture features SMX, Dynamic Parallelism, Hyper-Q
    System Servers only
    ECC Memory Error Protection Meets a critical requirement for computing accuracy and reliability in datacenters and supercomputing centers.
    External and internal memories are ECC protected in Tesla K20X.
    System Monitoring Features Integrates the GPU subsystem with the host system’s monitoring and management capabilities such as IPMI or OEM-proprietary tools. IT staff can thus 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 beforehand
    Asynchronous Transfer with dual DMA engines Turbocharges system performance by transferring data over the PCIe bus while the computing cores are crunching other data.
    Flexible programming environment with
    broad support of 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.
  • Resources

    Click here for the latest FAQs, Help & Tutorials, Downloads, and Brochures & Manuals.

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