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Compute
Outside the Box
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More Science. Less Money.

GigaIO empowers organizations to leverage standard tools and components to dynamically configure infrastructure according to workload requirements, while driving optimal rates of utilization and efficiency.

Stop by the GigaIO booth (#539) to figure out how to do more science for less money! See demos of:

GigaIO’s New
Edge-to-Core
Solution

FabreXâ„¢ Remote
Shared Dynamic
Memory Fabric

FabreX Natively Integrated
into NVIDIA Bright Cluster Manager 9.2

Learn about GigaIO’s new rack-scale composability appliances for research, manufacturing, and life sciences, powered by AMD.

Infrastructure Without Compromise

Build impossible servers for HPC + AI workflows — from storage to accelerators to memory — at a fraction of cloud TCO, by optimizing the utilization and efficiency of your existing hardware. Run more workloads faster at lower cost through higher utilization of resources and more agile deployment.

Let your software define your hardware. GigaIO provides workload-defined infrastructure through its dynamic memory fabric, which seamlessly composes rack-scale resources and integrates natively into industry-standard tools.

GigaIO at SC22

Monday,
November 14th

  • GigaIO Lighthouse User Group (GLUG) meeting: 11–2pm at Hyatt Regency Dallas
  • SDSC Reception Celebrating Vendor Technology: 7–9pm at SDSC booth (#3025)
  • Beowulf Bash: 9pm at Gilley’s Dallas

Tuesday,
November 15th

  • SDSC National Research Platform (NRP) Panel: 11:00–11:30am at SDSC booth (#3025)
  • SC22 Panel: Smackdown! Does HPC Need Composable Infrastructures Now?: 1:30–3:00pm at room C147-148-154

Wednesday,
November 16th

  • How Composability Solves Problems for Customers: 11am at Silicon Mechanics booth (#1422)

Thursday,
November 17th

  • SC22 Exhibitor Forum: How GigaIO Memory Fabric Enables Dynamic Computing: 1:30–2:00pm (D171)

In GigaIO’s SC22 Booth (#539)

Tuesday,
November 15th

  • 12pm: Compose Using Your Existing Tools, (Alan Benjamin, GigaIO)
  • 1pm: Flexible, Composable, Powerful: GigaIO GigaPod Engineered Solutions, (Brady Black, AMD)
  • 3pm: Memory Today Through Memory Tomorrow, (Matt Demas, GigaIO)
  • 5pm: Optimizing Parallel Workflows Using a Memory Fabric, (Matt Demas, GigaIO)

Wednesday,
November 16th

  • 10am: Memory Today Through Memory Tomorrow, (Alan Benjamin, GigaIO)
  • 1:30pm: Prototype National Research Platform, (Frank Würthwein, SDSC)
  • 3pm: Time to Buy Into Composable Infrastructure, (Brock Taylor, CIQ)
  • 5pm: Preparing for Massively Distributed, Massively Heterogeneous Computing, (Eric Sindelar, Source Code)

Thursday,
November 17th

  • 10am: Optimizing Parallel Workflows Using a Memory Fabric, (Guy Adams, GigaIO)
  • 12pm: Theoretical or Usable FLOPs as Measure of Cluster Performance? (Matt Demas, GigaIO)
  • 2pm: Compose Using Your Existing Tools, (Alan Benjamin, GigaIO)

Are You an HPC Guru?

Take the quiz and be entered into a drawing to win one of several $100 prizes!

Take the Quiz

Snap a Pic of Giggy at SC22 to Win!

Pick up your Giggy at our booth (#539) to join the fun and enter a daily drawing to win a LEGO® Technic™ Airbus!

Learn More

Build Impossible Infrastructure With Ease

Easy to obtain
Easy to deploy
Easy to integrate with existing tools

Easy to get higher performance
Easy to save money
Easy to scale into the future

FabreX Remote Shared
Dynamic Memory Fabric

No longer is the server the basic unit of compute. With FabreX, multiple racks can be your server. Transform static infrastructure into software-defined hardware where resources communicate over a native PCIe memory fabric, just as they would if they were plugged directly into the server motherboard.

See demo at our booth.

GIO_System-Overview_v-5-2_Thumbnail-med
Learn More
Download the System Overview

GigaIO’s Edge-to-Core Solution:
GigaPod and GigaPod Xtreme

Our edge solution reduces time to results and eliminates stagnant intelligence. FabreX, GigaIO’s dynamic memory fabric, unifies edge-to-core infrastructures in order to dynamically deploy any mission application, for actionable real-time intelligence – anywhere. 

See demo at our booth.

GigaIO Edge to Core Solutions Brief
Learn More
Download the Solutions Brief

NVIDIA Bright Cluster Manager 9.2 Native Integration of FabreX

A complete solution for building and managing composable clustered infrastructure that combines Bright Cluster Manager’s ability to build and manage clusters with GigaIO’s ability to disaggregate and compose servers, accelerators, and devices within a seamless memory fabric. 

See demo at our booth.

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Learn More
Download the Solutions Brief
  • GigaIO Open Partner Ecosystem

    GigaIO relies on its growing network of technology and channel partners to deliver our composable infrastructure solutions with cloud agility and blazing performance. We innovate by ensuring our customers are not restricted to using hardware or software from a single vendor, avoiding vendor lock-in. This is only possible by staying clear of vendor-specific APIs and offering off-the-shelf software for managing composable systems. Both these strategies mean more profit potential for our channel partners, and more freedom of choice for end-users, within a carefully curated open standards ecosystem.

    Become a Partner

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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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