Advanced Clustering Announces Release of eQUEUE

December 12, 2013

KANSAS CITY, Kansas, Dec. 12 — Advanced Clustering Technologies, Inc., announces the release of eQUEUE, an intuitive web-based front-end job submission tool.  It was developed as a way to increase cluster utilization by making it easier to run jobs on a cluster. This allows users to run jobs on clusters from any web browser and has the added value of virtually eliminating errors through these pre-defined job submission scripts.

eQueue is the latest software developed by Advanced Clustering Technologies, a leading provider of high performance computing (HPC) clusters.  It is an intuitive web-based front-end job submission tool and management portal that increases cluster usage, potentitially leading to more innovation and discovery. Its user-friendly interface means there is no need to learn Linux or command line scripting to get jobs to run as access is available via a user’s web browser. The genesis for eQUEUE was, according to Kyle Sheumaker, CTO of Advanced Clustering and co-developer, “It began with conversations with HPC directors and system administrators of clusters telling us their systems were underutilized. The most common refrain was that there are tens or hundreds or more of users that could easily run their jobs on a cluster but are unfamiliar with Linux or command line scripting so instead they ran them on their desktop or laptop. That is inefficient in two ways: first, it leaves a massive resource, built for this type of computationally intensive work, severely underutilized; and second, it ties up the user’s personal computer to where they can’t do anything with it until it’s done running their job.”

Feature-rich, eQUEUE allows system administrators to automate job submission scripts for virtually unlimited appications that cross scientific and engineering disciplines. Whether it is computational fluid dynamics, molecular modeling, 3D visualization, or oil and gas exploration, eQUEUE provides administrators the tools to easily establish pre-defined input variables to get jobs scheduled to run. The result: elimination of job submission errors and a more efficient cluster available to many more users.

eQUEUE includes other tools that allow for better understanding how jobs are performing, such as how long they ran, how much memory they used, and how many processing cores were needed. It also includes an accounting log analysis which provides insight on how the cluster is being used.  This analysis is done at the user, group, or queue level and shows quantity of jobs, average run times, memory utilization, node counts, core counts, and more.  This tool also allows segmenting users into custom sets of categories (such as department or user type) for better analysis.  This information is displayed in easy-to-read charts and tables and makes it easier to adjust the input variables so that what is needed is only what is allocated. By freeing up more resources, the cluster is available to more users.

Another key element of eQUEUE is its remote visualization component. This allows users to remotely access interactive GUI applications which is perfect for visualizing large complex datasets. By moving this capability to the cluster, this opens up the resource to every user who has a need for it and allows them to collaborate from any location through their web browser.

About Advanced Clustering Technologies, Inc.

Formed and incorporated in 2001, Advanced Clustering Technologies is a premier provider of Apex Computing Clusters, Linux-based Pinnacle servers and Horizon workstations. With its powerful and innovative technology, Advanced Clustering provides solutions for organizations involved in all types of research including biotechnology, chemical modeling, weather forecasting, oil and gas exploration, and visualization. Through its product lines, Advanced Clustering builds some of the fastest clusters and systems in the world.

Learn more about Advanced Clustering’s eQUEUE by calling 866-802-8222 or visiting www.advancedclustering.com/equeue.

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Source: Advanced Clustering Technologies, Inc.

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