|Processor frequency||745 MHz|
|Graphics processor||Tesla K40|
|Graphics processor family||NVIDIA|
|Graphics adapter memory type||GDDR5|
|Memory bus||384 bit|
|Memory clock speed||3000 MHz|
|Discrete graphics adapter memory||12 GB|
|Windows operating systems supported||Windows 7 Home Basic x64,Windows 7 Home Premium x64,Windows 7 Professional x64,Windows 7 Starter x64,Windows 7 Ultimate x64,Windows Vista Business x64,Windows Vista Enterprise x64,Windows Vista Home Basic x64|
|Linux operating systems supported|
|Ports & interfaces|
|Interface type||PCI Express x16|
|Weight & dimensions|
|Power consumption (typical)||235 W|
|Energy Star certified|
|TV tuner integrated|
TESLA K40 GPU COMPUTING ACCELERATOR
Solve your most demanding High-Performance Computing (HPC) challenges with NVIDIA Tesla family of GPUs. They’re built on the NVIDIA Kepler™ compute architecture and powered by NVIDIA CUDA®, the world’s most pervasive parallel computing model.
This makes them 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
Tesla K40 GPU Accelerator
Equipped with 12 GB of memory, the Tesla K40 GPU accelerator is ideal for the most demanding HPC and big data problem sets. It outperforms CPUs by up to 10x 2 and includes a Tesla GPUBoost3 feature that enables power headroom to be converted into usercontrolled performance boost.
The innovative design of the Kepler compute architecture includes:
SMX (streaming multiprocessor)
Delivers up to 3x more performance per watt than the SM in last-generation NVIDIA Fermi GPUs.
Enables GPU threads to automatically spawn new threads.
By adapting to the data without going back to the CPU, this greatly simplifies parallel programming.
Allows multiple CPU cores to simultaneously use the CUDA cores on a single Kepler GPU.
This dramatically increases GPU utilization and slashes CPU idle times.