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The New Zealand eScience Infrastructure (NeSI) is about to hit the road, touring a National High Performance Computing Roadshow through the country in September.

NeSi ties together the major high-performance computing available for research in New Zealand and the expertise and services needed to best utilise them.

Details of the day-long sessions are on their website.

Tim McNamara has pointed out that,

“There are two purposes of the roadshow. The first is to increase awareness of NeSI, ultimately to drive adoption. The second is to deepen connections within research communities. Part of each day will include splitting into sector-specific groups of researchers to discuss applying computation to their field.”

It’s not just about getting resources for yourself, but also sharing with others that use these resources.

The roadshow is on the week of Monday September 10th through to Friday 14th, with one day each at (in order) Dunedin, Christchurch, Wellington, Hamilton and Auckland.

NeSI provides access to three major computing centres (at The University of Auckland, Canterbury University, and NIWA) within the country and assistance making the best use of these.

The next call for proposals opens today and closes Friday, 21 September 2012. The eligibility for these resources is broad. Both academic and commercial operations are open to use them, research being a key element. (Or teaching in the case of the tertiary institutions.)

For laughs – I think it’s a pity it’s not NeSi (lowercase ‘i’): then it’d be silicon (think computers) with bright shining lights (neon)!

Don’t forget to offer your nominations for the inaugural NZ Open Science Award.

Footnotes

If you really want to knock yourself out, you can read the investment case for NeSI – PDF file, 82 pages. (I’ll confess I only got as far as checking how many pages it was…! Others might be interested in the background, however, hence the link.)


Other articles in Code for life:

Bioinformatics — computing with biotechnology and molecular biology data.

The software developer’s generalisation dilemma

Computational biology: Natural history v. explanatory models

Retrospective–The mythology of bioinformatics

Reproducible research and computational biology 

Developing bioinformatics methods: by who and how

External (bioinformatics) specialists: best on the grant from the onset