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Leap Ahead of the Competition
with GPU-Accelerated Computing

Get faster time-to-results without the traditional equipment headaches

Get Ready for The Future with More Powerful, More Efficient Computing

Graphics processing unit (GPU)-accelerated computing occurs when you use a GPU in combination with a CPU, letting the GPU handle as much of the parallel process application code as possible. The GPU takes the parallel computing approach orders of magnitude beyond the CPU, offering thousands of compute cores. This can accelerate some software by 100x over a CPU alone. Plus, the GPU achieves this acceleration while being more power- and cost-efficient than a CPU.

Because the Penguin Computing team (2019 NVIDIA Partner of the Year) is experienced with building both CPU and GPU-based systems as well as the storage subsystems required for this level of data analytics, the outcome of moving to a GPU-accelerated strategy is superior performance by all measures, faster compute time, and reduced hardware requirements.

GPU-Accelerated Servers

19″ EIA Servers

Server

Processor

PCIe Slots

GPU(s) Supported

1U
Intel® Xeon® Scalable Processors
4x PCIe Gen3 x16 (GPU), 2x PCIe Gen3 x16 (LP-MD2)
V100/V100S-PCIe, A100-PCIe, Quadro RTX (Passive), T4
2U
Intel® Xeon® Scalable Processors
2x PCIe Gen3 x16 (GPU), 2x PCIe Gen3 x8 (LP), 2x OCP Mezz
V100/V100S-PCIe, A100-PCIe, Quadro RTX (Passive), T4
Intel® Xeon® Scalable Processors
4x PCIe Gen3 x16 (GPU), 1x PCIe Gen3 x16 (LP), 1x PCIe Gen3 x8 (LP)
V100/V100S-PCIe, A100-PCIe, Quadro RTX, T4
Intel® Xeon® Scalable Processors
8x PCIe Gen3 x16 (GPU), 2x PCIe Gen3 x16 (LP)
V100/V100S-PCIe, A100-PCIe, Quadro RTX, T4
AMD 7002 EPYC
4x PCIe Gen4 x16 (FHFL) and 2x PCIe Gen4 x16 (HHHL)
NVIDIA V100/S, NVIDIA T4, NVIDIA A100-PCIe
4U
Intel® Xeon® Scalable Processors
8x PCIe Gen3 x16 (GPU), 2x PCIe Gen3 x16 (LP)
V100/V100S-PCIe, A100-PCIe, Quadro RTX, T4
Intel® Xeon® Scalable Processors
8x NVIDIA SXM2 (GPU), 2x PCIe Gen3 x16 (LP)
V100-SXM2

21″ OCP Servers

Server

Processor

PCIe Slots

GPU(s) Supported

1OU
Intel® Xeon® Scalable Processors
4x PCIe Gen3 x16 (GPU), 2x PCIe Gen3 x16 (LP)
Nvidia Volta V100-PCIe
Intel® Xeon® Scalable Processors
4x NVIDIA SXM2 (GPU), 2x PCIe Gen3 x16 (LP)
Nvidia Volta V100-16GB-SXM2, Volta V100-32GB-SXM2
AMD 7000 EPYC
4x PCIe Gen3 x16 (FHFL) and 2x PCIe Gen3 x16 (LP)
Nvidia Volta V100 PCIe

Selected applications supported by NVIDIA-based Penguin Computing GPU servers:

  • Amber
  • ANSYS Fluent
  • Gaussian
  • Gromacs
  • LS-DYNA
  • NAMD
  • OpenFOAM
  • Simulia Abaqus
  • VASP
  • WRF

Selected deep learning frameworks supported by NVIDIA-based Penguin Computing GPU servers:

  • Caffe2
  • Microsoft Cognitive Toolkit
  • MXNET
  • Pytorch
  • TensorFlow
  • Theano

Benefits of GPU-Accelerated Computing

  • Computing Power/Speed A single GPU can offer the performance of hundreds of CPUs for certain workloads. In fact, NVIDIA, a leading GPU developer, predicts that GPUs will help provide a 1000X acceleration in compute performance by 2025.
  • Efficiency/Cost Adding a single GPU-accelerated server costs much less in upfront, capital expenses and, because less equipment is required, reduces footprint and operational costs. Using libraries also allows organizations to use GPU acceleration without in-depth knowledge of GPU programming, reducing the investment of time required to achieve results.
  • Flexibility The inherently flexible nature of GPU programmability allows new algorithms to be developed and deployed quickly across a variety of industries. According to Intersect360 Research, 70% of the most popular HPC applications, including 10 of the top 10, have built-in support for GPUs.
  • Long-Term Benefits Adding GPU-accelerated computing now prepares you for the artificial intelligence (AI) revolution, which also relies in GPU-accelerated computing. This inevitable increase on the reliance on GPUs means that early adopters will enjoy not only greater computing power over time but have a greater margin of difference over time than competitors who do not migrate to GPU-accelerated computing.

Learn More About GPU-Accelerators