HPC Processors

HPC Processors – Greater Performance over Traditional CPUs

HPC Processors - GPU Servers, GPU Clusters, GPU Computing As the need for more GPU computing power changes every day, more researchers are trying to make use of different HPC Processors and general purpose GPUS (GPGPU) to improve the performance of their code. In the early years, the “GRAPE” special purpose “computer” was developed by the University of Tokyo in 1989. Since then, the MD-GRAPE cards have won multiple Gordon Bell prizes.

The biggest problem with these cards were the price. When graphics processors began supporting floating point operations, people began running matrix and vector calculations on GPUs which were less expensive and more available. Today, many vendors such as Intel, NVIDIA and AMD have furthered this technology, and many researchers have ported their code to run on these processors to gain performance in the HPC market.

NVIDIA has been at the forefront of accelerator computing with their GPGPUs. By creating the CUDA library, NVIDIA was able to jump ahead of their competition in the accelerated GPU server space. In the past, the GPU performance was bottlenecked by the PCIe interconnect. Today, NVIDIA’s Pascal architecture uses SMX2 which enables NVLink interconnect for a high-speed bidirectional bandwidth which is five times faster than PCIe.

AMD FirePro and Epyc Series

AMD FirePro GPU clusters

AMD FirePro

Monstrous Compute Power at Your Fingertips.
AMD EPYC

AMD EPYC 7001 (1st Gen)

Dual Socket Performance in a Single Socket
AMD EPYC

AMD EPYC 7002 (2nd Gen)

First 7nm, 64 Core x86 Processor
Dedicated Security Processor

Intel Xeon Processor Scalable Family

Cascade Lake Intel Xeon Scalable Processors

Intel Xeon Cascade Lake

Advanced Features Are Designed into the Silicon.
Skylake Intel Xeon Scalable Processors

Intel Xeon Skylake

Advanced Features Are Designed into the Silicon.
Nvidia GPU servers

Nvidia GPU

The World Leader in Visual Computing.