[CAnet - news] Some excellent comments by Dan Reed on academic high performance computing

"Bill St.Arnaud" <[email protected]> Fri, 11 Jan 2008 09:49:07 -0500
Newsgroups gmane.culture.publications.news
Message-ID <00d901c85461$1e7d53f0$0221bdcd@amarillo>
For more information on this item please visit my blog at 
http://green-broadband.blogspot.com/ or http://billstarnaud.blogspot.com
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[It is astounding how much money granting councils continue to fund for the
purchase of stand alone computers and clusters by university researchers.
Much of this computation could be more easily done on virtual machines or
clouds as Dan Reed points out. Not only will this save significant dollars,
but it will also be a first step in addressing the challenges of global
warming caused by the power and cooling required for these machines. As well
the universities can save money in avoiding the significant costs of the
physical infrastructure to host these facilities. Some excerpts from Dan
Reed's commentary in HPCwire--BSA]

www.HPCwire.com
[...]  
  
  
  Outsourcing: Perhaps It Is Time?
  
  In late November, I briefed the NSF OCI advisory committee on the 
  PCAST report. The ensuing discussion centered on the rising academic 
  cost of operating research computing infrastructure. The combination 
  of rising power densities in racks and declining costs for blades 
  means computing and storage clusters are multiplying across campuses 
  at a stunning rate. Consequently, every academic CIO and chief 
  research officer (CRO) I know is scrambling to coordinate and 
  consolidate server closets and machine rooms for reasons of 
  efficiency, security and simple economics.
  
  This prompted an extended discussion with the OCI advisory committee 
  about possible solutions, including outsourcing research 
  infrastructure and data management to industrial partners. Lest this 
  seem like a heretical notion, remember that some universities have 
  already outsourced email, the lifeblood of any knowledge-driven 
  organization. To be sure, there are serious privacy and security 
  issues, as well as provisioning, quality of service and pricing 
  considerations. However, I believe the idea deserves exploration.
  
  Computing Clouds
  
  All of this is part of the still ill-formed and evolving notion of 
  cloud computing, where massive datacenters host storage farms and 
  computing resources, with access via standard web APIs. In a very real 
  sense, this is the second coming of Grids, but backed by more robust 
  software and hardware of enormously larger scale. IBM, Google, Yahoo, 
  Amazon and my new employer -- Microsoft -- are shaping this space, 
  collectively investing more in infrastructure for Web services than we 
  in the computational science community spend on HPC facilities.
  
  I view this as the research computing equivalent of the fabless 
  semiconductor firm, which focuses on design innovation and outsources 
  chip fabrication to silicon foundries. This lets each group -- the 
  designers and the foundry operators -- do what they do best and at the 
  appropriate scale. Most of us operate HPC facilities out of necessity, 
  not out of desire. They are, after all, the enablers of discovery, not 
  the goal. (I do love big iron dearly, though, just like many of you.)
  
  In the facility-less research computing model, researchers focus on 
  the higher levels of the software stack -- applications and 
  innovation, not low-level infrastructure. Administrators, in turn, 
  procure services from the providers based on capabilities and pricing. 
  Finally, the providers deliver economies of scale and capabilities 
  driven by a large market base.
  
  This is not a one size fits all solution, and change always brings 
  upsets. Remember, though, that there was a time (not long ago) when 
  deploying commodity clusters for national production use was 
  controversial. They were once viewed as too risky; now they are the 
  norm. Technologies change, and we adapt accordingly. 
  [...]
  

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