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A TURNKEY, RACK-SCALE SOLUTION FOR HIGHER EDUCATION

GigaIO Engineered Solution For Universities, Powered by AMD

Centralize, standardize, share, and optimize infrastructure across the varied workflows required by a university — both classroom and research settings.

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“AMD is excited to enter the composable computing space through our partnership with GigaIO. Our recent joint deployments of composable infrastructure at SDSC at the University of California San Diego and TACC at the University of Austin, Texas, demonstrate the promise of composability to solve complex computational problems.”

“AMD is excited to enter the composable computing space through our partnership with GigaIO. Our recent joint deployments of composable infrastructure at SDSC at the University of California San Diego and TACC at the University of Austin, Texas, demonstrate the promise of composability to solve complex computational problems.”

— Brock Taylor, Global HPC Solutions Director, AMD

Providing Turnkey, Multi-tenancy Workflows for Higher Education

Professors who teach students about real-world workloads such as CAE, CFD, and generative design have limited options when tied to the fixed infrastructure of their academic institution. Traditional IT architecture means limited configurations, poor resource utilization for varied types of tasks, and difficulty reconfiguring for different types of workloads.

A new composable architecture is emerging that promises to break the scalability limits of server hardware. Composability delivers the agility and flexibility of cloud computing while lowering total cost of ownership.

The GigaIO Engineered Solution for Universities, Powered by AMD is a flexible environment for heterogeneous compute that can easily accommodate the different workloads required for teaching, professor research, and grad-student research. It is a complete, future-proofed composable infrastructure solution that facilitates dynamic workflows and is simple to deploy and manage.

GigaIO FabreXTM

GigaIO’s FabreX is a universal dynamic memory fabric that transforms static infrastructure into software-defined hardware for advanced scale workflows by seamlessly composing an entire rack of resources into a unified compute platform, without proprietary architecture lock-in.

More on FabreX Software

Download GigaIO’s Composability Primer

AMD Accelerators and CPUs

AMD EPYCTM processors and InstinctTM accelerators can tackle the world’s most complex and critical workloads. Using the highest performing technical and general computing infrastructure means that workloads are run faster and less infrastructure, power, and cooling are needed.

More on AMD Processors

More on AMD Accelerators

NVIDIA Bright Cluster Manager

NVIDIA Bright Cluster Manager reduces the time, skills, effort, risk, and complexity of building clustered infrastructure. Quickly build and manage heterogeneous high-performance Linux clusters that host HPC, machine learning, and analytics applications from core-to-edge-to-cloud.

Read more at NVIDIA.com

How it Works

The GigaIO Engineered Solution for Universities combines NVIDIA Bright Cluster Manager’s ability to easily build and manage clusters with GigaIO’s ability to connect AMD accelerators, servers, and other devices in a seamless dynamic fabric. FabreX: How it Works

Ease of use is at the forefront of this design, as its goal is to be used in a class/lab setting without requiring dedicated IT expertise.

  • Easy-to-deploy, turnkey for Higher Education
  • Centralize, standardize, share, and optimize infrastructure
  • Handle varied types of workloads across departments

Native integration with Bright Cluster Manager allows the owner to easily assign configurations prior to use, dividing hardware among students to allow them the experience of running actual simulation workloads on the same compute infrastructure they will utilize upon graduation.

Disaggregating resources outside of servers enables each department to share them. Each department can now compose systems precisely tuned to the needs of the applications they need to run.

Key Advantages

The GigaIO Engineered Solution for Universities supplies students with access to equipment they will use in the real world, so they will be better prepared for the job market.

Flexibility and composability means that systems don’t remain idle while not being used for teaching — they can instead be reconfigured for actual simulation work and swapped back into teaching mode as needed. And of course the inherent benefit of using composable infrastructure is the ability to build heterogeneous configurations for varied types of workloads and trainings.

Other benefits include:

  • Easy to deploy and maintain
  • Short time to value
  • Lower Total Cost of Ownership (TCO)
  • Lower Research Cost of Ownership (RCO)
  • Efficient
  • Future-proofed
  • Cloud-like agility

Configurations

The GigaIO Engineered Solution for Universities, Powered by AMD, is offered in three configurations. Compute Condo 1 is the perfect entry point and is preconfigured for easy expansion. Compute Condo 2 is essentially two Compute Condo 1s in a single system. When you need the ultimate in compute power, choose the Compute Condo 3.

GigaIO Composability Appliance, EDU Edition, Powered by AMD, Spec Page Thumbnail
Download the Specs

Resources:

GigaIO & AMD Engineered Solutions for Universities Solution Brief

Download the PDF

Download the PDF

GigaIO & AMD Press Release

Download the PDF

Download the PDF

From Engineering.com: There is an Easy and Affordable Way to Improve HPC Performance

Read the Article

Read the Article

AMD and GigaIO: Bringing Cloud Flexibility to On Premise

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Watch the Video

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Niraj Mathur

Niraj has over 20 years of industry experience in strategic and product marketing, product management, business development, customer applications and advanced silicon engineering. He has held senior leadership roles and led global, cross-functional teams to support these disciplines. Niraj was instrumental in driving numerous successful networking products at Nortel Networks, Quake Technologies, AppliedMicro, Snowbush, Gennum, Semtech and Rambus. He has defined, developed and supported carrier grade hardware and software for the world’s leading telecom, enterprise and cloud customers. His past projects include Ethernet PHYs, core Internet switches, metro optical routers, high-speed silicon IPs and PCI Express products. Niraj holds a Bachelor of Computer Engineering from McGill University and an MBA from Cornell University.

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