June 2007 01

HPC gets green

http://www.hpcwire.com/hpc/1587852.html

I’ve spoken with a number of companies recently who proudly talk about their initiatives to reduce the long-term Total Cost of Ownership (TCO) associated with their HPC platforms. But many others seem hesitant to talk about TCO, feeling it is an older term that has seen its day. And while everyone acknowledges that power efficiency has become a serious topic at all levels of the computing infrastructure, a number of small and mid-size companies don’t want to be associated with the topic of ‘Green Computing,’ saying that it takes away from their real message of performance leadership.

Marketing folks, take note. The fact is, in HPC there is a growing awareness and a strong economic argument for paying attention to Green Computing. The discussion comes from two perspectives — environmental consciousness and economic responsibility.

HPC has always represented the edge of the computing envelope, and I can remember the underlying theme of many branding campaigns as “performance at any cost.” But, the reality today is that larger and larger clusters of PCs, workstations and servers are driving the energy consumption costs right through the roof, forcing IT directors, data center managers, and CIOs to start including power consumption and cooling requirements as critical evaluation criteria for future purposes.
The message for the system vendors and integrators serving the HPC ecosystem is clear. Green is good. You need to put more emphasis on the economics of your hardware solutions. The days of buying performance at any cost are quickly fading into the past.

Great HPC have joined the Green gird, this should help companies see how deploying high performance computing solutions doesn’t mean they need to have high energy requirements.

Does this mean we’ll start looking at desktop grid as opposed to server grid?  We’ll see, I wonder if this doesn’t mean we’re going to tier grid solutions? Switch to a more HPC orientated way of doing things, evaluating the performance requirements and coupling that with existing capacity/energy constraints.

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