NVidia Powered GPU Computing
Penguin Computing GPU supercomputing processing solutions
  • Applications run several orders of magnitude faster
  • Powered by NVidia Tesla GPUs
  • Custom server configurations
  • Linux support 'out of the box'
  • Consulting, training, and code migration services available

Talk to an Expert. Call (888) 736-4846

Or, choose a server below to configure

Model Key Features Processor RAM
Relion 1800GT » 3 GPUs in a 1U chassis
Supports processors up to 130W TDP
Dual Intel Xeon E5-2600/2600v2 DDR3-1866 ECC RAM up to 512GB
Relion 2800GT » 4 GPUs in a 2U chassis
8 3.5" drive bays
Dual Intel Xeon E5-2600/2600v2 DDR3-1866 ECC RAM up to 512GB
Relion 2808GT » 8 GPUs in a 2U chassis
8 2.5" drive bays
Dual Intel Xeon E5-2600/2600v2 DDR3-1866 ECC RAM up to 512GB
Altus 2750GT » 2 GPUs in a 2U chassis, additional
slot for IB or 10GbE HCA
Low-cost platform
Dual AMD Opteron 4300 DDR3-1333 ECC RAM up to 384GB
Altus 2850GTi » 2 GPUs in a 2U chassis, additional
slot for IB or 10GbE HCA
Dual AMD Opteron 6200 DDR3-1866 ECC RAM up to 512GB
Altus 2A20 » AMD Fusion APU series A10 AMD A10-5800K DDR3-1600 ECC RAM up to 576GB
Relion 4808GT » 8 GPUs in a 4U chassis
Up to 512GB of RAM
Dual Intel Xeon E5-2600/2600v2 DDR3-1866 ECC RAM up to 512GB
Niveus 5200 » 4 GPUs per workstation
Up to 512GB of RAM
Dual Intel Xeon E5-2600/2600v2 DDR3-1866 ECC RAM up to 512GB

What is GPU Computing?

GPU computing harnesses a graphics processing unit (GPU) to accelerate scientific and engineering applications. Learn More

What is GPU Computing?

GPU computing is the use of a GPU (graphics processing unit) together with a CPU to accelerate general-purpose scientific and engineering applications. GPU computing offers unprecedented application performance by offloading compute-intensive portions of the application to the GPU, while the remainder of the code still runs on the CPU. From a user's perspective, applications simply run significantly faster.

GPU Computing

CPU + GPU is a powerful combination because CPUs consist of a few cores optimized for serial processing, while GPUs consist of thousands of smaller, more efficient cores designed for parallel performance. Serial portions of the code run on the CPU while parallel portions run on the GPU. Most customers can immediately enjoy the power of GPU computing by using GPU-accelerated applications listed in our catalog, which highlights over one hundred, industry-leading applications. For developers, GPU computing offers a vast ecosystem of tools and libraries from major software vendors.

GPUs accelerate hundreds of popular applications such as:

Life sciences
AMBER
GROMACS
LAMMPS
NAMD

Engineering
ANSYS Mechanical
CST MIcrowave Studio
OpenFoam
Simulia Abaqus

Math & Physics
Chrome
Mathematica
MATLAB
MILC

What applications run on GPUs?

Case Studies

GPU background, case studies, research and applications

NVidia Tesla GPU Computing -
Revolutionizing High Performance Computing

Are GPUs a good fit for your application?

Speak to a GPU expert who can answer your questions: (888) 736-4846



Georgia Institute of Technology

The integrated solution provided by Penguin Computing worked out of the box and allowed us to use the GPUs in production right away--with performance gains from 3x to more than 20x.

Dr. John Sears
School of Chemistry and Biochemistry
Georgia Institute of Technology