impressive in terms of creating this supercomputing industry.” What exactly is the prize on offer,

though, is perhaps the most invit- ing question. In a fast-approaching age of automation, global megacor- porations are precipitiously close to being able to use data in such a way that machines will soon be able to perform far above and beyond the skill level of humans; in the US, there are already algorithms that have outperformed cancer doctors in being able to detect tumours and Google can now predict what you are going to write in search queries with terrifying accuracy (even if it struggles with gender pronouns). Health, insurance, law, professional services generally, not to men- tion precision manufacturing and genomics, are all human fields that stand to be aided (replaced, even) by the rapidity of technological development, the likes of which exascale computing will only serve to enhance.

year that the world is currently producing 2.5 quintillion bytes of data every day, and the US and China are driving a supercomput- ing “arms race” to try and make sense of it all. Both countries are expected to reach the 1,000-pet- aflop ‘exascale’ within the next couple of years – in what will be considered a ‘new age’ of com- puting performance (the exascale is a billion-billion calculations per second, for those keeping count). For Parson’s money, the US has the upper hand with its Oak Ridge, Tennessee, facility; although the Chinese surprised the world by developing the first 100 petaflop system, he says it has proved “very difficult” to programme. “Te Americans are certainly better at producing use- able systems,” he explains. “But the Chinese have been extremely

Demand for the exascale is also coming from industry partners who use ARCHER, with Rolls Royce and the Met Office among existing users who would ben- efit from even faster processing time, says Parsons. Rolls Royce is moving more of its extremely expensive engine certification tests to the ‘virtual’ space; instead of testing physical engines to the point of destruction (blades that shear off in the process have to be contained within engine casings in order for an engine to be ‘certi- fied’), the aerospace company will instead rely on supercomputer- generated modelling techniques to replace disaster testing methods. Steel pouring in foundries can be made more efficient by supercom- puter simulations, and sails on a ship can be improved by model- ling wind flow. When people talk about moving data into the cloud, Parsons could quite legitimitely raise the prospect of moving the ‘cloud into the data’; such is the advance in weather forecasting in the next few years that his super- computer is expected to be able to model the behaviour of individual clouds. Government data, too, is likely

to be pushed more and more into the supercomputer’s telescopic

education, too. Te intention is that his facility will be accessible by “every child that goes to state school” and it will play its part in the training of 100,000 data scientists over the next 10 years. “We’re going to go out and

“Te computer just works nowadays; it’s always data that causes the headaches” Mark Parsons

gaze. Much of the City Region Deal’s focus is around the creation of a ‘World Class Data Infrastruc- ture’ (WCDI) for the region, and Scotland more widely. In fact Parsons stresses computing power alone is not the only story of the government-backed funding programme; the ability to store and move around large data sets, for their use by the likes of the five data institutes that will benefit from the Deal; the Edinburgh Futures Institute, the new Bayes Centre, the Usher Institute, Ro- botarium and Easter Bush campus – are all University of Edinburgh affiliates which will be supported by the wraparound WCDI facility. Data Driven Innovation (DDI) actually makes up £600m of the total spend of the £1.3bn pro- gramme, and is therefore a huge investment by government in the transformative power of data to stimulate the creation of new knowledge and future industries. Parsons has a role to play in

work with hundreds, if not thousands, of companies to help adopt data driven innovation in their business,” says Parsons. “I think some of those projects will use my computers and some won’t but the important thing is everything will be driven by the data that we hold; I think the biggest challenge we have in the world right now is dealing with data deluge. One of the things that ARCHER has struggled with is moving large amounts of data around. And the next ARCHER and all the modern supercomput- ers will be much better at moving data around. It has to become bet- ter at that. All of my problems as a supercomputing centre director relates to the data that we store, not the computer. Te computer just works nowadays; it’s always data that causes the headaches.” And asked whether the DDI

revolution is going to phase out all our jobs, Parsons refers back to the prescience of economists like JK Galbraith. “As the world be- came richer, things would become automated and we would work less [he predicted],” he says. “Tis is the challenge to policy-makers, which is if we get into the position with AI and robotics that we need to work less because we’ve got machines doing more for us then we need to ensure that we have a fair society. I think it’s a very interesting discussion that society needs to have with itself.” l



Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36