Adaptive Computing Creates All Spark Cube to Demonstrate Cloud and HPC Workload Management Software

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The All Spark Cube will be displayed at the Mini Maker Faire in Salt Lake City.

All Spark Cube

the IT industries’ top minds were mesmerized by its unique effects.

Adaptive Computing, the largest provider of private cloud management and High-Performance Computing (HPC) workload management software, today announced The All Spark Cube, a 16x16x16 full color LED Cube, which was designed to demonstrate its Cloud and HPC workload management software. The Cube debuted at VMWorld in San Francisco last month and will be on display at the Mini Maker Faire in Library Square, Salt Lake City on October 6th.

The All Spark Cube, named in honor of the device that provides life-giving force to the “Transformers” (a 2007 Live Action Film), is a large scale, full color LED Cube -- essentially a 3-dimensional display monitor. It contains 4,096 LEDs organized into a 2” wide grid. It took over 1500 volunteer man-hours to design, build, and test the All Spark Cube. Over 3000 feet of buss wire and 17,000 solder connections interconnect the LEDs in a 3D matrix, and 16 custom designed circuit boards control visual effects from inside a custom cabinet. The entire structure is almost 4 feet square and 6 feet tall with a clear acrylic protective box over the LEDs.

“Adaptive Computing needed a way to demonstrate its software products and drive traffic to our trade show booth at events. In its debut appearance at VMworld, the IT industries’ top minds were mesmerized by its unique effects,” comments Jill King, Adaptive Computing’s director of marketing communications. She continues, “People wanted their picture taken with the cube. I heard comments that this was the best display on the show floor. It exceeded our expectations.”

The All Spark Cube was created by a group of engineers and IT Specialists from Adaptive Computing. The team consisting of:

  •     Kevin Yackley, Lead Designer and Developer - Entrepreneur and Friend of Adaptive Computing
  •     Ian Nate, Cube Construction and Scene Designer - Community Marketing Manager at Adaptive Computing
  •     Spencer Owen, Software Developer – Tech Support Manager of Adaptive Computing
  •     Thomas Bennett, Cube Constructions and Website – IT Specialist at Adaptive Computing
  •     Kevin King, Solderer and Debugger – High School Student and Friend of Adaptive Computing

For more information about the cube, its makers and its construction, please visit

The All Spark Cube was created by volunteers at Adaptive Computing. “It’s a great place to work. We have very creative, wildly talented minds working here at Adaptive so we do cool projects such as the Cube,” says Ian Nate, Community Marketing Manager at Adaptive Computing. Adaptive Computing is currently hiring and seeking talented people with Cloud and HPC experience. For open positions, visit:

About Adaptive Computing
Adaptive Computing is the largest provider of High-Performance Computing (HPC) workload management software and manages the world’s largest cloud computing environment with Moab, a self-optimizing dynamic cloud management solution and HPC workload management system. Moab®, a patented multi-dimensional intelligence engine, delivers policy-based governance, allowing customers to consolidate and virtualize resources, allocate and manage applications, optimize service levels and reduce operational costs. Adaptive Computing offers a portfolio of Moab cloud management and Moab HPC workload management products and services that accelerate, automate, and self-optimize IT workloads, resources, and services in large, complex heterogeneous computing environments such as HPC, data centers and cloud. Our products act as a brain on top of existing and future diverse infrastructure and middleware to enable it to self-optimize and deliver higher ROI to the business with its:

Moab Cloud Suite for self-optimizing cloud management
Moab HPC Suite for self-optimizing HPC workload management

For more information, call (801) 717-3700 or visit

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Jill King
Adaptive Computing
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