httpv://www.youtube.com/watch?v=sbmOsSS2fyg
In this video from the Adaptive Computing booth at SC12, Gabriel Mateescu from Virginia Tech presents: Using Moab Node-sets to Improve Job Scheduling.
…today’s situation is clear: HPC is struggling with reliability at scale. Well over 10 years ago, Google proved that commodity hardware was both cheaper and more effective for hyperscale processing when controlled by software-defined systems, yet the HPC market persists with its old-school, hardware-based paradigm. Perhaps this is due to prevailing industry momentum or working within the collective comfort zone of established practices. Either way, hardware-centric approaches to storage resiliency need to go.
Firms of all sizes are leveraging workstations as part of their artificial intelligence (AI) workflows. In the past, many firms relied on highly-scaled servers in data centers or private/public cloud infrastructure to run their AI applications. However, the results of a recent survey commissioned by Dell and executed by Forrester summarized in this white paper have indicated a quarter of firms are actually using workstations today to run core AI business applications and are experiencing the benefits that workstations can offer.
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