Supercomputing 2014: Laissez les bon temps rouler!

Gabor Samu | 2014-11-26 13:36:33.0 | Tags:  management platform scheduling lsf ibm openpower workload hpc cluster energy grid data systems centric aware | 0 Comments

BAM! As the say in New Orleans, let the good times roll!  Looking back at Supercomputing 2014, there is much to be excited about in the world of high performance computing. Things started off with the significant announcement that the U.S. Department of Energy awarded IBM contracts to develop "data centric" supercomputers (...)


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Did you know you can cut costs by better managing your data transfers?

Gabor Samu | 2014-09-16 08:20:49.0 | Tags:  hpc platform ibm management data scheduling lsf hptc | 0 Comments

Are you transferring data efficiently? Or is valuable computing power sitting idle in your clustered environment, waiting for files to be moved back and forth—and costing you money?   For many organizations, critical workloads often take longer than necessary and use more resources than needed because the right data is not in (...)


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Docker for High Performance Computing

Gabor Samu | 2014-09-05 12:18:09.0 | Tags:  rh7 linux cgroup high ibm hat lxc computing hpc lsf red performance docker | 0 Comments

With the recent release of Docker 1.0 and the broad industry backing from organizations such as Red Hat and IBM, it's no wonder that interest in the use and application of this Linux container technology continues to grow. Docker is shipped with Red Hat Enterprise 7 and there exists a growing (...)


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Accelerated analytics with IBM Platform LSF

Gabor Samu | 2014-08-22 10:00:00.0 | Tags:  hpc beta workloadmanagement bigdata analytics accelerate big mapreduce lsf open data | 0 Comments

With the collision of big data & analytics with traditional High-Performance Computing (HPC), there is growing interest in leveraging the disciplines of HPC to perform analytics on the vast amounts of data being collected in many fields.  MapReduce is the de facto programming model for performing analysis on large volumes (...)


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