Cirrascale GB5600 / GB5400/ Multi-GPU Server Platform

Cirrascale GB5600 Multi-GPU Server Platform
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Cirrascale GB5600 / GB5400 Multi-GPU Blade Server

GPU-accelerated computing is enabling various scientific, analytics, engineering, consumer, and enterprise applications worldwide. GPU accelerators now power energy-efficient datacenters in government labs, universities, enterprises, and small-and-medium businesses around the world. The Cirrascale GB5600 / GB5400 Series servers are designed to provide near-linear scaling of GPUs for these applications enabling up to eight GPU accelerators to communicate peer-to-peer on just one PCIe root hub, such as the NVIDIA® Tesla® K80 Dual-GPU Accelerator cards and the new Tesla M40 GPU accelerators designed specifically for deep learning applications.

Product Features and Benefits

  • Maximum performance with the Intel® Xeon® processor E5-2600 v2/v3 product families.
  • Utilizes the Cirrascale SR3514 PCIe switch riser to maximize PCIe bandwidth while reducing intercard latency.
  • Supports up to eight PCIe Gen 3.0 compatible devices, including the latest NVIDIA® Tesla® K80 Dual-GPU Accelerators and NVIDIA Telsa M40 GPU Accelerators.

Cirrascale GB5600 / GB5400 Multi-GPU Server Overview

The GB5600/GB5400 Series servers are different from other GPU supporting hardware implementations. Most of the hardware configurations available today only provide maximum performance between specific pairs of GPUs; and since GPUs are paired up, jobs requiring communication between arbitrary GPUs experience a performance impact. Additionally, there can be a significant performance impacts with trying to scale more than four GPUs on multi-socket systems. These have been persistent problems for customers who are pushing the limits of GPUs with large, complex data-sets and calculations, or where data must be streamed between GPUs. Cirrascale has been able to overcome these issues, and achieve near linear performance scaling with its design.

Maximize PCIe Bandwidth

Cirrascale is a strong believer in utilizing a technology to its fullest potential whenever possible and GPUs and GPU Accelerators are no exception. If the GPU has a PCIe Gen3 x16 link, then it should use it when communicating with other GPUs — any other GPUs. Our switch riser technology allows us to scale and peer multiple PCIe x16 Gen3 cards on a single root hub ensuring that the maximum PCIe bandwidth is available utilized for inter-card communication.

Minimize Intercard Latency and Obtain Consistent Performance Between GPUs

Our switch riser allows GPUs to communicate as if they are all on the same bus... because they are. Gone are the days of needing a bounce-buffer in host memory, or leaving GPU DMA engines unused because they couldn't address other devices in the system. This reduces intercard latency while helping to maintain a consistent performance level between GPUs.

Enable GPU-Centric Development and Usage

Since most all of the GPU traffic is passed between the GPUs directly via the Cirrascale SR3415 switch riser, a very negligible amount of host resources are needed to perform GPU work. Additionally, with a single address space and simultaneous inter-card communication at full PCIe x16 Gen3 speeds, software can spend more time doing work than thinking about when to schedule data copies.

Supports the Largest Number of GPU Offerings

We work closely with our technology partners to ensure you're given the broadest offerings for your application. The Cirrascale GB5400 Series supports both professional and consumer cards from the leading manufacturers including ground-breaking GPU accelerators, such as the NVIDIA® Tesla® K80 Dual-GPU Accelerators and the new Tesla M40 GPU accelerators designed specifically for deep learning applications.

With the consistent advances in technology, Cirrascale engineering and development teams are constantly testing and deploying the latest technical specifications being offered by our technology partners. We make every effort to provide the below specifications error-free and up-to-date. However, we always encourage our customers to contact us to discuss Cirrascale's latest improvements to its products. This product's specifications are as follows:

GB5600 Multi-GPU Server Specifications

Processor
  • Options include two Intel® Xeon® processor E5-2600 v3 product family
Chipset
  • Intel C612 PCH
Memory
  • Supports up to 1TB DDR4 Memory
  • 16 RDIMM Slots - 2133/1866/1600MHz
Storage
  • 10 x SATA III 6Gb/s ports
  • 1 x M.2 socket 3
Networking
  • 2 x GbE LAN Ports (Intel® I210-AT)
  • 1 x Management LAN
GPU / Add-In Support
  • Supports 8 GPU Graphics Cards or other PCIe Gen 3 compatible devices in dedicated PCIe x16 Gen 3 slots utilizing Cirrascale's SR3514 PCIe Riser Switch
Expansion Slots
  • 4 x PCIe x16 Gen3.0 x 16 throughput
  • 2 x PCIe x16 Gen3.0 x 8 throughput
Integrated Graphics
  • VGA Integrated in ASPEED 2400
Management and Monitoring
  • Complete remote server management with IPMI 2.0-compliant ASMB8-iKVM module and ASWM Enterprise
Supported Operating Systems
  • Windows® Server 2003 and later
  • Windows® 7 64-bit and later
  • RedHat Enterprise Linux 6 and later
  • CentOS 6 and later
  • Ubuntu 12.04 and later
  • Please Call for Other Support

With the consistent advances in technology, Cirrascale engineering and development teams are constantly testing and deploying the latest technical specifications being offered by our technology partners. We make every effort to provide the below specifications error-free and up-to-date. However, we always encourage our customers to contact us to discuss Cirrascale's latest improvements to its products. This product's specifications are as follows:

GB5400 Multi-GPU Server Specifications

Processor
  • Options include two Intel® Xeon® processor E5-2600 v2 product family
Chipset
  • Intel C602 (Patburg-A)
Memory
  • Supports up to 512GB DDR3 Memory
  • 16 DIMM Slots DDR3 1066/1333 UDIMM/RDIMM ECC
Storage
  • 8 x SAS 3Gb/s
  • 2 x SATA 6Gb/s Hard Drives
Networking
  • Intel Powerville I350 Network Controller (Dual GbE ports) with Management LAN
GPU Support
  • Supports 8 GPU Graphics Cards in Dedicated PCIe x16 Gen 3 slots utilizing Cirrascale's SR3514 PCIe Riser Switch
Expansion Slots
  • 1 x PCIe x16 Gen3.0 x 16 throughput
  • 1 x PCIe x16 Gen3.0 x 8 throughput
  • 2 x PCIe x8 Gen3.0 x 4 throughput
  • 1 x PCIe x8 Gen2.0 x 1 throughput
Standard Interfaces
  • 6 x USB 2.0 (4 external / 2 internal)
  • On Management LAN
  • 2 x RJ-45 LAN 1GbE
  • 1 x VGA
  • 1 x COM
Integrated Graphics
  • VGA Integrated in ASPEED 2300
Management and Monitoring
  • IPMI 2.0 using ASPEED 2300
Supported Operating Systems
  • Windows® Server 2003 and later
  • Windows® 7 64-bit and later
  • RedHat Enterprise Linux 6 and later
  • CentOS 6 and later
  • Ubuntu 12.04 and later
  • Please Call for Other Support

Cirrascale GB5400 / GB5600 Series Available Resources

The below links provide access to the detailed data sheets and other resources related to this and potentially several other Cirrascale products and solutions. If you can not find the information you are trying to locate, please contact us directly at (888) 942-3800 or email us at info@cirrascale.com:

Product Literature

PDF Cirrascale GB5600 Product Data Sheet - 775kB
PDF Cirrascale GB5400 Product Data Sheet - 774kB

Application Guides

PDF GPU-Accelerated Applications Catalog - NVIDIA - 1742kB

Deep Learning Case Study

Read about how NYU researchers take on bigger challenges and create deep learning models that let computers do human-like perceptual tasks for research projects and educational programs at the NYU Center for Data Science.

Download Our Case Study on
NYU Center for Data Sciences
Cirrascale's peer to peer technology allows us to unlock the true power of NVIDIA GPUs for scientific computation. This is the first platform of its kind and provides the unprecedented bandwidth needed to scale an individual molecular dynamics simulation with AMBER across all the GPUs within a node. This previously unattainable performance will have impact on many fields.
Ross Walker
Associate Research Professor, SDSC and
Adjunct Associate Professor, UCSD

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