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GPU computing offers unprecedented accelerated performance by offloading portions of compute-intensive applications to the GPU (Graphics Processing Unit), while the remainder of the code runs on the CPU. By harnessing the processing power of both the CPU and GPU, applications run significantly faster.|
Silicon Mechanics GPU servers and (High-Performance Computing) HPC systems are optimized with the latest GPU accelerator technology from NVIDIA, providing scalability and breakthrough power efficiency across a wide array of applications. Our configurable systems enable seamless integration of GPU computing for the world's most complex computational problems.
Now Featuring NVIDIA Tesla K40 GPU Accelerators!
Silicon Mechanics GPU servers and HPC Systems now feature Tesla K40 GPUs, the newest addition to the NVIDIA Tesla GPU family and the world's fastest accelerator!
Tesla K40 GPUs feature 12GB of memory, 2880 CUDA cores, and a new GPUBoost¹ feature. With the GPUBoost feature, users can select a sustained accelerated GPU Clock speed to convert power headroom into performance acceleration. Tesla K40 GPUs offer up to 40 percent higher performance compared to Tesla K20X GPUs and are the best solution for tackling the most demanding big data and HPC challenges.
Silicon Mechanics GPU Products|
Maximize your HPC performance with the NVIDIA Tesla family of GPUs, built on
NVIDIA Kepler™ compute architecture and the CUDA parallel computing platform. 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.
|Peak double-precision floating point
|Peak single-precision floating point
|Number of GPUs
||1 x GK110B
||1 x GK110
||2 x GK104
|Number of CUDA cores
||2 x 1,536
|Memory size per board (GDDR5)
|Memory bandwidth for board (ECC off)³
||SMX, Dynamic Parallelism, Hyper-Q
||Servers and Workstations
||Servers and Workstations
Take a Free Test Drive with Silicon Mechanics!
|The innovative Kepler compute architecture design includes the
following powerful technology features:
- SMX (streaming multiprocessor) - Delivers up to 3x more performance per watt than the SM in previous-generation
NVIDIA Fermi™ GPUs.
- Dynamic Parallelism - Enables GPU threads to automatically pawn new threads. By adapting to the data without going back to the CPU, this feature greatly simplifies parallel programming.
- Hyper-Q - 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.
» More about NVIDIA Tesla GPU computing
» More about NVIDIA CUDA programming
» More about GPU Applications
1. For details on GPUBoost refer to the K40 Board spec on www.nvidia.com/object/tesla_product_literature.html | 2. Tesla K10 specifications are shown as aggregate of two GPUs. | 3. With ECC on, 6.25% of the GPU memory is used foe ECC bits. So, for example, 6GB total memory yields 5.625 GB of user available memory with ECC on.