NVIDIA Tesla K80 GPU 24GB DDR5 Kepler CUDA PCIe x16: Accelerated Machine Deep Learning Artificial Intelligence Video Finance Oil Gas CAD Research IoT


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Ideal for your Advanced Digital Transformation Applications : Video Processing, Big Data, Hyperconverged Appliances, Internet of Things (IoT), In-Memory Analytics, Machine Learning (ML), Artificial Intelligence (AI) and intensive Data Center or Hyperscale Infrastructure Applications. The NVIDIA Tesla GPUs are very suitable for autonomous cars, molecular dynamics, computational biology, fluid simulation etc and even for advanced Virtual Desktop Infrastructure (VDI) applications.

The NVIDIA Tesla K80 GPU Accelerator is built on the NVIDIA Kepler™ technology and is designed for the most demanding computational tasks, combining 24 GB of memory with blazing-fast memory bandwidth and leading compute performance for single and double precision workloads. Equipped with the latest NVIDIA GPU Boost™ technology, the Tesla K80 intelligently monitors GPU usage to maximize throughput1 and outperforms CPUs by up to 10x.

Key Features

  • Sold and supported by NVIDIA
  • 4992 NVIDIA CUDA cores with a dual-GPU design
  • Up to 2.91 Teraflops double-precision performance with NVIDIA GPU Boost
  • Up to 8.73 Teraflops single-precision performance with NVIDIA GPU Boost
  • 24 GB of GDDR5 memory
  • 480 GB/s aggregate memory bandwidth
  • ECC protection for increased reliability
  • Server-optimized to deliver the best throughput in the data center

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The NVIDIA® Tesla® K80 graphics processing unit (GPU) is a PCI Express, dual-slot computing module in the Tesla (267 mm length) form factor comprising of two Tesla K80 GPUs. The Tesla K80 GPU Accelerator is designed for servers and offers a total of 24 GB of GDDR5 on-board memory (12 GB per GPU) and supports PCI Express Gen3. The Tesla K80 is only available with a passive heat sink, which requires externally generated airflow for cooling. The Tesla K80 GPU Accelerator boards ship with ECC enabled by default protecting the register files, cache and DRAM. With ECC enabled, some of the memory is used for the ECC bits, so the user available memory is reduced by ~6.25%. On the Tesla K80 the total available memory with ECC turned on will be ~22.5 GB.

NVIDIA GPU Boost on Tesla K80

The NVIDIA GPU Boost™ feature makes use of any power headroom by raising the core clock to a higher frequency. When an application is being run and the GPU has thermal headroom, the driver will automatically raise the clocks to ensure maximum utilization and performance. The Tesla K80 ships with Autoboost enabled by default. Autoboost mode means that when the end user starts using the Tesla K80 for the first time, the GPUs will start at base clock and raise the core clock to higher levels automatically as long as the boards stays within the 300 W power limit. If the end user does not want the Tesla K80 clocks to boost automatically, the end-user can disable this feature and lock the module to a clock supported by the GPU. Having the boards boost automatically will be useful in scenarios where the workloads have a lot of headroom, as each GPU works independently and is not required to run in lock step with all the GPUs in the cluster.

Experience 10x faster application performance.

Accelerate your most demanding single and double precision workloads in scientific computing, seismic processing, and data analytics applications by upgrading to the NVIDIA Tesla K80 dual-GPU accelerator. It delivers up to 2.2x faster performance than the Tesla K20X, up to 2.5x faster performance than the Tesla K10, and up to 10x faster performance than CPUs on real-world applications. The Tesla K80 features: > Up to 2.91 Teraflops of double precision performance with NVIDIA GPU Boost™ > Up to 8.74 Terfalops of single precision performance with NVIDIA GPU Boost > 24 GB of GDDR5 memory (12 GB per GPU) > 480 GB/sec memory bandwidth per board > 2x application throughput with the two onboard GPUs As the latest addition to the Tesla Accelerated Computing Platform, the Tesla K80 leverages a rich software, hardware, and support eco-system to accelerate the most demanding workloads in the datacenter.

CUDA Ready

CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs.

In GPU-accelerated applications, the sequential part of the workload runs on the CPU – which is optimized for single-threaded performance – while the compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions in the form of a few basic keywords.

The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.

Mfr Model & Part # NVIDIA Tesla K80
Core Clocks Base clock: 560 MHz •Boost clocks: 562 – 875 MHz
Number of GPU 2× Tesla GK210B
Memory Clock 2.5 GHz
Memory size/board 24 GB (per board) •12 GB (per GPU)
Memory I/O 384-bit GDDR5
Memory bandwidth 480 GB/s (per board) •240GB/s (per GPU)
Memory Configuration 48 pieces of 256M × 16 GDDR5 SDRAM
Display Connectors None
Power Connectors 8-pin CPU power connector (ships with a 2× 8-pin PCIe to single 8-pin CPU convertor)
Board Power 300W
Power cap level 150 W per GPU •300 W per board
BAR1 Size 16 GB (per GPU)
Extender Straight extender or long offset extender
Idle Power TBD
Thermal Cooling Passive heat sink
MTBF Controlled environment: 151377.2164 hours at 35 °C

Additional information

Weight 8 lbs


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