News
Cycle Computing and Purdue power Condor pool at SC09

NOVEMBER 11, 2009

INSIDE HPC

Cycle Computing and Purdue University are previewing the Condor pool they’ll have up and running during SC09 this week. You’ll recall that Condor is a cycle-scavenging application that’s been around a while which allows users to run distributed applications on desktops and workstations that might otherwise sit idle (at night, for example)

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Pharma's Early Cloud Adopters

NOVEMBER 10, 2009

BIO-IT WORLD

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Cycle Computing and Varian Case Study: Amazon Web Services

SEPTEMBER 9, 2009

SEATTLE, WASHINGTON

Cycle Computing, a systems integrator specializing in cloud computing and high performance computing, has developed CycleCloud to address the growing need to rapidly deploy clusters for pay-as-you-go intensive computing needs. Cycle Computing supported Varian’s implementation of CycleCloud for scientific computing needs in the cloud.

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Cycle client wins Campus Technology Innovators Award 2009

JULY 28, 2009

CAMPUS TECHNOLOGY

Purdue University (IN) is the 2009 recipient of the Campus Technology Innovators Award for High-Performance Computing. "Now at more than 24,000 processors (and growing) across multiple campuses, the sheer size of the pool also sets DiaGrid apart. It provided more than 16 million hours of computation in 2008." Purdue's DiaGrid uses Cycle Computing's CycleServer to administer their Condor based pool.

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The New Computing Pioneers

MAY 25, 2009 - VOLUME 87, NUMBER 21

CHEMICAL & ENGINEERING NEWS

"With in-house information technology burdened to the breaking point, the traditionally conservative drug industry is putting cloud computing to the test"

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Schrödinger Partners with Cycle Computing to Provide Cloud Computing Solutions

APRIL 27, 2009

NEW YORK, NEW YORK

Schrödinger, LLC and Cycle Computing, LLC announced today that they will offer cloud computing solutions to run Schrödinger’s chemical simulation and molecular modeling software on elastic resources in the US and Europe. Cloud computing provides users timely access to computational resources as needed, without prohibitive upfront capital investment in, nor the burden of administering and maintaining, large computer clusters.

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