Learning to Share

Autor/in	Raths, David
Titel	Learning to Share
Quelle	In: Campus Technology, 23 (2010) 7, S.32-39 (8 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1553-7544
Schlagwörter	Stellungnahme; Educational Finance; Researchers; Information Technology; Competition; Computer Uses in Education; Energy; Resource Allocation; Computer Centers; Data Processing; Politics of Education; Coordination; Sharing Behavior; Attitude Change; Models; Participation; Professional Autonomy; Cluster Grouping; Georgia; Indiana; Massachusetts; Rhode Island; Texas; Washington + Suchen Sie Ihr Suchwort? Bildungsfonds; Researcher; Forscher; Informationstechnologie; Wettkampf; Computernutzung; Energie; Ressourcenallokation; Datenverarbeitung; Educational policy; Bildungspolitik; Koordination; Attitudinal change; Einstellungsänderung; Analogiemodell; Teilnahme; Berufsfreiheit; Eingruppierung; Master-Studiengang
Abstract	In the tug-of-war between researchers and IT for supercomputing resources, a centralized approach can help both sides get more bang for their buck. As 2010 began, the University of Washington was preparing to launch its first shared high-performance computing cluster, a 1,500-node system called Hyak, dedicated to research activities. Like other research universities, UW had learned the hard way that having faculty members purchase and run their own high-performance computing nodes in multiple small data centers scattered across campus is inefficient and expensive. But IT leaders at UW and other research universities say that leading the transition from scattered small research nodes to larger, centrally managed, shared resources is a tricky political process. It often requires CIOs to invest their own discretionary funds, to understand the needs and working styles of researchers, and to sell the concept to others on campus. It involves studying different business models and governance structures to determine which one would work best on a particular campus. Finally, it may require calling for some shared sacrifice. University CIOs can make a good case for investing in shared high-performance computing clusters. The systems make computing cycles less expensive, and researchers have the ability to run jobs beyond their allotment when other researchers' computing resources are idle. The cluster approach also gives universities an advantage when recruiting top faculty. The author stresses that a high-performance cluster model saves money, drives efficiencies, and forges stronger bonds between IT and research communities. (ERIC).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10