Finding a Competitive Advantage with High Performance Computing

High Performance Computing (HPC), or supercomputing, is a critical enabling capability for many industries, including energy, aerospace, automotive, manufacturing, and more. However, one of the most important aspects of HPC is that HPC is not only an enabler, it is often also a differentiator – a fundamental means of gaining a competitive advantage.

Differentiating with HPC

Differentiating (gaining a competitive advantage) through HPC can include:

• faster - complete calculations in a shorter time;
• more - complete more computations in a given amount of time;
• better - undertake more complex computations;
• cheaper - deliver computations at a lower cost;
• confidence - increase the confidence in the results of the computations; and 
• impact - effectively exploiting the results of the computations in the business.

These are all powerful business benefits, enabling quicker and better decision making, reducing the cost of business operations, better understanding risk, supporting safety, etc.

Strategic delivery choices are the broad decisions about how to do/use HPC within an organization. This might include:

• choosing between cloud computing and traditional in-house HPC systems (or points on a spectrum between these two extremes);
• selecting between a cost-driven hardware philosophy and a capability-driven hardware philosophy;
• deciding on a balance of internal capability and externally acquired capability;
• choices on the balance of investment across hardware, software, people and processes.

The answers to these strategic choices will depend on the environment (market landscape, other players, etc.), how and where you want to navigate that environment, and why. This is an area where our consulting customers benefit from our expertise and experience. If I were to extract a core piece of advice from those many consulting projects, it would be: "explicitly make a decision rather than drift into one, and document the reasons, risk accepted, and stakeholder buy-in".

Which HPC technology?

A key means of differentiating with HPC, and one of the most visible, is through the choice of hardware technologies used and at what scale. The HPC market is currently enjoying (or is it suffering?) a broader range of credible hardware technology options than the previous few years.

HPC Getting More Choices - Technology Diversity

HPC has been easy for a while ...

When buying new workstations or personal computers, it is easy to adopt the simple mantra that a newer processor or higher clock frequency means your application will run faster. It is not totally true, but it works well enough. However, with High Performance Computing, HPC, it is more complicated.

HPC works by using parallel computing – the use of many computing elements together. The nature of these computing elements, how they are combined, the hardware and software ecosystems around them, and the challenges for the programmer and user vary significantly – between products and across time. Since HPC works by bringing together many technology elements, the interaction between those elements becomes as important as the elements themselves.

Whilst there has always been a variety of HPC technology solutions, there has been a strong degree of technical similarity of the majority of HPC systems in the last decade or so. This has meant that (i) code portability between platforms has been relatively easy to achieve and (ii) attention to on-node memory bandwidth (including cache optimization) and inter-node scaling aspects would get you a long way towards a single code base that performs well on many platforms.

Increase in HPC technology diversity

However, there is a marked trend of an increase in diversity of technology options over the last few years, with all signs that this is set to continue for the next few years. This includes breaking the near-ubiquity of Intel Xeon processors, the use of many-core processors for the compute elements, increasing complexity (and choice) of the data storage (memory) and movement (interconnect) hierarchies of HPC systems, new choices in software layers, new processor architectures, etc.

This means that unless your code is adjusted to effectively exploit the architecture of your HPC system, your code may not run faster at all on the newer system.

It also means HPC clusters proving themselves where custom supercomputers might have previously been the only option, and custom supercomputers delivering value where commodity clusters might have previously been the default.

Deeply learning about HPC - ISC17 day 3 summary - Wednesday evening

For most of the HPC people gathered in Frankfurt for ISC17, Wednesday evening marks the end of the hard work, the start of the journey home for some, already home for others. A few hardy souls will hang on until Thursday for the workshops. So, as you relax with a drink in Frankfurt, trudge through airports on the way home, or catch up on the week's emails, here's my final daily summary of ISC17, as seen through the lens of twitter, private conversations, and the HPC media.

This follows my highlights blogs from Monday "Cutting through the ISC17 clutter"  (~20k views so far) and Tuesday "ISC17 information overload" (~4k views so far).

So what sticks out from the last day, and what sticks out from the week overall?

Deep Learning

Wednesday was touted by ISC as "deep learning day". If we follow the current convention (inaccurate but seemingly pervasive) of using deep learning, machine learning, AI (nobody actually spells out artificial intelligence), big data, data analytics, etc. as totally interchangeable terms (why let facts get in the way of good marketing?), then Wednesday was indeed deep learning day, judging by by tweet references to one or more of the above. However, I struggle to nail down exactly what I am supposed to have learnt about HPC and deep learning from today's content. Perhaps you had to be there in person (there is a reason why attending conferences is better than watching via twitter).

I think my main observations are:

• DL/ML/AI/BigData/analytics/... is a real and growing part of the HPC world - both in terms of "traditional" HPC users looking at these topics, and new users from these backgrounds peering into the HPC community to seek performance advantages.
• A huge proportion of the HPC community doesn't really know what DL/ML/... actually means in practice (which software, use case, workflow, skills, performance characteristics, ...).
• It is hard to find the reality behind the marketing of DL/ML/... products, technologies, and "success stories" of the various vendors. But, hey, what's new? - I was driven to deal with this issue for GPUs and cloud in my recent webinar "Dissecting the myths of Cloud and GPUs for HPC".
• Between all of the above, I still feel there is a huge opportunity being missed: for users in either community and for the technology/product providers. I don't have the answers though.

Snippets

Barcelona (BSC) has joined other HPC centers (e.g., Bristol Isambard, Cambridge Peta5, ...) in buying a bit of everything to explore the technology diversity for future HPC systems: "New MareNostrum Supercomputer Reflects Processor Choices Confronting HPC Users".

Exascale is now a world-wide game: China, European countries, USA, Japan are all close enough to start talking about how they might get to exascale, rather than merely visions of wanting to get there.

People are on the agenda: growing the future HPC talent, e.g., the ISC STEM Student Day Day & Gala, the Student Cluster Competition, gender diversity (Women-in-HPC activities), and more.

Wrapping up

There are some parts of ISC that have been repeated over the years due to demand. Thomas Sterling's annual "HPC Achievement & Impact" keynote that traditionally closes ISC (presenting as I write this) is an excellent session and goes a long way towards justifying the technical program registration fee.

2017 sees the welcome return of Addison Snell's "Analyst Crossfire". With a great selection of questions, fast pace, and well chosen panel members, this is always a good event. Of course, I am biased towards the ISC11 Analyst Crossfire being the best one!

I'll join Addison's fun with my "one up, one down" for ISC17. Up is CSCS, not merely for Piz Daint knocking the USA out of the top 3 of the Top500, but for a sustained program of supercomputing over many years, culminating in this leadership position. Down is Intel - brings a decent CPU to market in Skylake but gets backlash for pricing, has to face uncertainty over the CORAL Aurora project, and in spite of a typically high profile presence at the show, a re-emerging rival AMD takes a good share of the twitter & press limelight with EPYC.

Until next time

That's all from me for ISC17. I'll be back with more blogs over the next few weeks, based on my recent conference talks (e.g., "Six Trends in HPC for Engineers" and "Measuring the Business Impact of HPC").

You can catch up with me in person at the SEG Annual Meeting, EAGE HPC Workshop (I'm presenting), the TACC-NAG Training Institute for Managers, and SC17 (I can reveal we will be delivering tutorials again, including a new one - more details soon!).

In the meantime, interact with me on twitter @hpcnotes, where I provide pointers to key HPC content, plus my comments and opinions on HPC matters (with a bit of F1 and travel geekery thrown in for fun).

Safe travels,

@hpcnotes.

Cutting through the clutter of ISC17: Monday lunchtime summary

ISC, the HPC community's 2nd biggest annual gathering, in fully underway in Frankfurt now. ISC week is characterized by a vibrant twitter flood (#ISC17), topped up with a deluge of press releases (a small subset of which are actually news), plus a plethora of news and analysis pieces in the HPC media. And, of course, anyone physically present at ISC, has presentations, meetings, and exhibitors further demanding their attention.

I go to ISC almost every year. It is a valuable use of time for anyone in the HPC community or who uses, or has an interest in, HPC even if they don't see themselves as part of the HPC community. However, I have decided not to attend ISC this year, due to other commitments. However, I will keep an eye on the "news" throughout the week and post a handful of summary blogs (like this one), which might be a useful catch-up on "news" so far, whether you are attending ISC or watching from afar.

Secrets, lies, women and money: the definitive summary of SC16 - Part 1

Just over a week ago 11,000 people were making their way home from the biggest supercomputing event of the year – SC16 in Salt Lake City. With so much going on at SC, even those who were there in person likely still missed a huge proportion of what happened. It’s simply too busy to keep up with all the news during the week, too many events/talks/meetings happening in parallel, and much of the interesting stuff only gets talked about behind closed doors or through informal networking.

There were even a couple of top-notch tutorials on HPC acquisition and TCO/funding models :-)

Amongst this productive chaos, I was flattered to be told several times at during SC that people find my blogs worth reading and commented they hadn’t seen any recently. I guess the subtext was “it’s about time I wrote some more”. So, I’ll make an effort to blog more often again. Starting with my thoughts on SC16 itself.

As ever, while I do soften the occasional punch in my writing (not usually in person though), there remains the possibility that some readers won’t like some of my opinions, and there’s always the risk of me straying into controversy in places.

I've got four topics to cover: secrets, lies, women and money.

Predictions for 2013 in HPC

As we stumble into the first weeks of 2013, it is the season for predictions about what the coming year will bring. In my case, following my recent review of HPC in 2012, I get to make some predictions for the world of HPC in 2013.


Buzzwords

First up, this year’s buzzword for HPC marketing and technology talks. Last year was very much the year of “Big Data” as a buzzword. As that starts to become old hat (and real work) a new buzzword will be required. Cynical? My prediction is that this year will see Big Data still present in HPC discussions and real usage but it will diminish in use as a buzzword. 2013 will probably spawn two buzzwords.

The first buzzword will be “energy-efficient computing”. We saw the use of this a little last year but I think it will become the dominant buzzword this year. Most technical talks will include some reference to energy-efficient computing (or the energy cost of the solution or etc.). All marketing departments will swing into action to brand their HPC products and services as energy efficient computing – much as they did with Big Data and before that, Cloud Computing, and so on. Yes, I’m being a tad cynical about the whole thing. I’m not suggesting that energy efficiency is not important – in fact it is essential to meet our ambitions in HPC. I’m merely noting its impending over-use as a theme. And of course, energy efficient computing is not the same as Green Computing – after all that buzzword is several years old now.

Energy efficiency will be driven by the need to find lower power solutions for exascale-era supercomputers (not just exascale systems but the small department petascale systems that will be expected at that time – not to mention consumer scale devices). It is worth noting that optimizing for power and energy may not be the same thing. The technology will also drive the debate – especially the anticipated contest between GPUs and Xeon Phi. And politically, energy efficient computing sounds better for attracting investment rather than “HPC technology research”.

A review of 2012 in supercomputing - Part 1

It's that time of year when doing a review of the last twelve months seems like a good idea for a blog topic. (To be followed soon after by a blog of predictions for the next year.)
So, here goes - my review of the year 2012 in supercomputing and related matters. Thoroughly biased, of course, towards things that interested me throughout the year.


Predictions for 2012

Towards the end of 2011 and in early 2012 I made various predictions about HPC in 2012. Here are the ones I can find or recall:

• The use of "cloud computing" as the preferred marketing buzzword used for large swathes of the HPC product space would come to an end.
• There would be an onslaught of "Big Data" (note the compulsory capital letters) as the marketing buzzword of choice for 2012 - to be applied to as many HPC products as possible - even if only a tenuous relevance (just like cloud computing before it - and green computing before that - and so on ...)
• There would be a vigorous ongoing debate over the relative merits and likely success of GPUs (especially from NVidia) vs. Intel's MIC (now called Xeon Phi).
• ARM would become a common part of the architecture debate alongside x86 and accelerators.
• There would be a growth in the recognition that software and people matter just as much as the hardware.

Looking ahead to ISC'12

I have posted my preview of ISC'12 Hamburg - the summer's big international conference for the world of supercomputing over on the NAG blog. I will be attending ISC'12, along with several of my NAG colleagues. My blog post discusses these five key topics:

• GPU vs MIC vs Other
• What is happening with Exascale?
• Top 500, Top 10,
• Tens of PetaFLOPS
• Finding the advantage in software
• Big Data and HPC 

Read more on the NAG blog ...

My SC11 diary 10

It seems I have been blogging about SC11 for a long time - but it has only been two weeks since the first SC11 diary post, and this is only the 10th SC11 diary entry. However, this will also be the final SC11 diary blog post.

I will write again before SC11 in HPC Wire (to be published around or just before the start of SC11).

And, then maybe a SC11 related blog post after SC11 has all finished.

So, what thoughts for the final pre-SC11 diary then? I'm sure you have noticed that the pre-show press coverage has started in volume now. Perhaps my preview of the SC11 battleground, what to look out for, what might emerge, ...

ISC11 Review

ISC11 - the mid-season big international conference for the world of supercomputing - was held this week in Hamburg.

Here, I update my ISC11 preview post with my thoughts after the event.

I said I was watching out for three battles.

GPU vs MIC vs Fusion

The fight for top voice in manycore/GPU world will be one interesting theme of ISC11. Will this be the year that the GPU/manycore theme really means more than just NVidia and CUDA? AMD has opened the lid on Fusion in recent weeks and has sparked some real interest. Intel's MIC (or Knights) is probably set for some profile at ISC11 now the Knights Ferry program has been running a while. How will NVidia react to no longer being the loudest (only?) noise in GPU/manycore land? Or will NVidia's early momentum carry through?

Review: None of this is definitive, but my gut reaction is that MIC won this battle. GPU lost. Fusion didn't play again. My feeling from talking to attendees was that MIC was second only to the K story, in terms of what people were talking about (and asking NAG - as collaborators in the MIC programme - what we thought). Partly because of the MIC hype, and the K success (performance and power efficient without GPUs), GPUs took a quieter role than recent years. Fusion, disappointingly, once again seemed to have a quiet time in terms of people talking about it (or not). Result? As I thought, manycore is now realistically meaning more than just NVidia/CUDA.

Exascale vs Desktop HPC

Both the exascale vision/race/distraction (select according to your preference) and the promise of desktop HPC (personal supercomputing?) have space on the agenda and exhibit floor at ISC11. Which will be the defining scale of the show? Will most attendees be discussing exascale and the research/development challenges to get there? Or will the hopes and constraints of "HPC for the masses" have people talking in the aisles? Will the lone voices trying to link the two extremes be heard? (technology trickle down, market solutions to efficient parallel programming etc.) What about the "missing middle"?

Review: Exascale won this one hands down, I think. Some lone voices still tried to talk about desktop HPC, missing middles, mass usage of HPC and so-on. But exascale got the hype again (not necessarily wrong for one of the year's primary "supercomputing" shows!)

Software vs Hardware

The biggie for me. Will this be the year that software really gets as much attention as hardware? Will the challenges and opportunities of major applications renovation get the profile it deserves? Will people just continue to say "and software too". Or will the debate - and actions - start to follow? The themes above might (should) help drive this (porting to GPU, new algorithms for manycore, new paradigms for exascale, etc). Will people trying to understand where to focus their budget get answers? Balance of hardware vs software development vs new skills? Balance of "protect legacy investment" against opportunity of fresh look at applications?

Review: Hardware still got more attention than software. Top500, MIC, etc. Although ease-of-programming for MIC was a common question too. I did miss lots of talks, so perhaps there was more there focusing on applications and software challenges than I caught. But the chat in the corridors was still hardware dominated I thought.

The rest?

What have I not listed? National flag waving. I'm not sure I will be watching too closely whether USA, Japan, China, Russia or Europe get the most [systems|petaflops|press releases|whatever]. Nor the issue of cloud vs traditional HPC. I'm not saying those two don't matter. But I am guessing the three topics above will have more impact on the lives of HPC users and technology developers - both next week and for the next year once back at work.

Review: Well, I got those two wrong! Flags were out in force, with Japan (K, Fujitsu, Top500, etc) and France (Bull keynote) waving strongly among others. And clouds were seemingly the question to be asked at every panel! But in a way, I was still right - flags and clouds do matter and will get people talking - but I mainatin that manycore, exascale vs desktop, and the desperation of software all matter more.


 What did you learn? What stood out for you? Please add your comments and thoughts below ...

ISC 11 Preview

ISC11 - the mid-season big international conference for the world of supercomputing - is next week in Hamburg.

Will you be attending? What will you be looking to learn? I will be watching out for three battles.

GPU vs MIC vs Fusion

The fight for top voice in manycore/GPU world will be one interesting theme of ISC11. Will this be the year that the GPU/manycore theme really means more than just NVidia and CUDA? AMD has opened the lid on Fusion in recent weeks and has sparked some real interest. Intel's MIC (or Knights) is probably set for some profile at ISC11 now the Knights Ferry program has been running a while. How will NVidia react to no longer being the loudest (only?) noise in GPU/manycore land? Or will NVidia's early momentum carry through?

Exascale vs Desktop HPC

Both the exascale vision/race/distraction (select according to your preference) and the promise of desktop HPC (personal supercomputing?) have space on the agenda and exhibit floor at ISC11. Which will be the defining scale of the show? Will most attendees be discussing exascale and the research/development challenges to get there? Or will the hopes and constraints of "HPC for the masses" have people talking in the aisles? Will the lone voices trying to link the two extremes be heard? (technology trickle down, market solutions to efficient parallel programming etc.) What about the "missing middle"?

Software vs Hardware

The biggie for me. Will this be the year that software really gets as much attention as hardware? Will the challenges and opportunities of major applications renovation get the profile it deserves? Will people just continue to say "and software too". Or will the debate - and actions - start to follow? The themes above might (should) help drive this (porting to GPU, new algorithms for manycore, new paradigms for exascale, etc). Will people trying to understand where to focus their budget get answers? Balance of hardware vs software development vs new skills? Balance of "protect legacy investment" against opportunity of fresh look at applications?

The rest?

What have I not listed? National flag waving. I'm not sure I will be watching too closely whether USA, Japan, China, Russia or Europe get the most [systems|petaflops|press releases|whatever]. Nor the issue of cloud vs traditional HPC. I'm not saying those two don't matter. But I am guessing the three topics above will have more impact on the lives of HPC users and technology developers - both next week and for the next year once back at work.

 What will you be looking out for?

Technical computing futures part 2: GPU and manycore success

[Originally posted on The NAG Blog]

In my previous blog, I suggested that the HPC revolution towards GPUs (or similar many-core technologies) as the primary processor has a lot in common with the move from RISC to commodity x86 processors a few years ago. A new technology appears to offer cheaper (or better) performance than the incumbent, for some porting and tuning pain. Of course, I’m not the first HPC blogger to have made this observation, but I hope to follow it a little further.

In particular, my previous blog suggested the outcome might be: “at first the uptake is tentative ... but in a few years time, we might well look back with nostalgia to when GPU’s were not the dominant processor for HPC systems” – in other words, hard going initially, but GPU/many-core will “win” eventually. I even ended up with an ambitious promise for my next blog (i.e. this one): “an idea of what/who will emerge as the dominant solution ...”

Continuing the basis of using the past to guess the future, my prediction is that the next steady state of HPC processors will be GPU-like/manycore technologies (for most of the FLOPS at least) and, just like the current steady state (x86), those few companies with the strongest financial muscle will eventually own the dominant market share. However, other companies will have pioneered many of the technologies that make that dominant market share possible, enjoying good market share surges in the process.

I can even have a go at predicting some of the path that might get us to the next steady state of HPC architecture. NVIDIA has already shown us that GPUs for HPC are sometimes a good solution – and importantly, that a good programming ecosystem (CUDA) really helps adoption. Over the last year or so, I’d say the HPC community has moved from “if GPUs can work in this case ...” to “how do I make GPUs work across my workload?”

As Intel’s Knights processors bring us many-core but with a familiar x86 instruction set, we might learn that getting good performance across a broad range of applications is possible, but critically dependent on software tools and hard work by skilled parallel programmers. AMD’s Fusion with tighter links between CPU & GPU, could show that the nature of the integration between the many-core/GPU unit and the rest of the system (be it CPU, network, main memory etc) will affect not only maximum performance on specific applications, but maybe more importantly the ease of getting “good enough” performance across a range of applications.

I don't know of any GPU/many-core/accelerator announcements from IBM, but it’s always possible IBM will throw in another useful contribution before the dust settles. They were one of the first into many-core processors for HPC acceleration with Cell and they cannot be easily counted out of top end HPC solutions - e.g. the forthcoming Blue Waters (POWER7) and Sequoia (BG/Q) chart-toppers.

But back to my “winner” prediction. When the revolution settles into a new steady state of mostly GPU/many-core for HPC processors, there won’t be (can’t be) critical distinctions between the various products anymore for most applications. Whichever product we consider (whether GPU or x86-based or whatever), many-core is sufficiently different from few-core (e.g. 1-8 cores) to mean that the early winners have been those users who are easily able to move their key applications across to get step changes in cost and performance.

The big winners in the next stages of the GPU/manycore emergence will be those users who can move the bulk of their high-value-generating HPC usage to many-core processors with the most attractive transition (economy and speed) compared to their competitors.

So what about the dominant solution I promised? For the technology to be pervasive, first there must be greater commonality between offerings (I stop short of standardization) so that programmers have at least a hope of portability. Secondly, users need to be able to extract the available performance. Ideally these would mean a software method that makes many-core programming “good enough easily enough” is discovered – and if so, that software method will be the dominant solution, across all hardware.

Or, if the magic bullet is still not market ready, skilled parallel programmers will be the dominant solution for achieving competitive performance and cost benefits - just like it is for HPC using commodity x86 processors today.

Supercomputing's future: Is it CPU or GPU?

[Article by me on ZDNet UK, 16 June, 2010]

Graphics processing units are a hot topic, but that does not assure them a place in supercomputing's future ...

http://www.zdnet.co.uk/news/it-strategy/2010/06/16/supercomputings-future-is-it-cpu-or-gpu-40089202/

Revealing the future of technical computing: part 1

[Originally posted on The NAG Blog]

I recall some years ago porting an application code I worked with, which was developed and used almost exclusively on a high end supercomputer, to my PC. Naively (I was young), I was shocked to find that, per-processor, the code ran (much) faster on my PC than on the supercomputer. With very little optimization effort.


How could this be – this desktop machine costing only a few hundred pounds was matching the performance of a four processor HPC node costing many times that? Since I was also starting to get involved in HPC procurements, I naturally asked why we spend millions on special supercomputers, when for a twentieth of the price, we’d get the same throughput from a bunch of high-spec PCs?


The answer then (and now) was that I was extrapolating from only one application, and that application could be run as lots of separate test cases with no reduction in capability (i.e. we didn’t need large memory etc, just lots of parameter space). However, the other major workload (which I also ported and also ran fast on the PC) would not have been able to do the size of problem we wanted on a PC – we needed the larger memory and extra grunt from parallel processing. (We did look at the newfangled Network Of Workstations emerging at the time but decided it might be a wolf in sheep’s clothing. Sorry.)


In the end, we had to find a balance between (a) speed at lowest cost for the one application; (b) the best capability for the other application (i.e. fastest solution time for the largest problems); (c) ease of programming – to get a good enough (fast-enough) code developed with the limited developer effort and funding we had; and (d) whole life affordability.


Why do I foist this reminiscence on you? Because the current GPU crisis (maybe “crisis” is a bit strong – "PR storm" perhaps?) looks very much the same to me. The desktop HPC surprise of my youth has evolved into the dominant HPC processor and so for some years now, we have been developing and running our applications on clusters of general purpose processors – and a new upstart is trying to muscle in with the same tactic – “look how fast and how cheap” – the GPU (or similar technologies – e.g. Larrabee, sorry Knights-thingy).


The issues are the same: (a) for some applications, GPUs offer substantial performance improvements for considerably less cost than a “normal” HPC processor; (b) for other applications, the limits such as off-card bandwidth etc mean that GPU’s cannot deliver the required capability; (c) the underlying concern is ease of programming for GPUs; (d) affordability – sure GPU’s are cheap to buy, but what about power costs when in bulk, or code porting costs, etc?


Maybe the result will be the same as when commodity processors and clusters eventually exploded to leave custom supercomputer hardware as the minority solution. At first the uptake (now) is tentative - and painful. Some will have great success stories, many will get burnt. But in a few years time, we might well look back with nostalgia to when GPU’s were not the dominant processor for HPC systems.


I’ll continue on the future of HPC in my next blog in a few days, including an idea of what/who will emerge as the dominant solution ...

What’s the next revolution in technical computing?

[Originally posted on The NAG Blog]

It’s a question that absorbs the attention of the technical computing community, especially those working at the leading edge of technology and performance (high performance computing, HPC). What is the next disruptive technology? In other words, what is the next technology that will replace a currently dominant technology? Usually a disruptive technology presents a step-change in performance, cost or ease-of use (or a combination of these) compared to the established technology. The new technology may or may not be disruptive in the sense of discontinuous change in user experience.



Why is identifying disruptive technology so important? First, those who spot the right change early enough and deploy it effectively can attain a significant advantage over competitors as a result of a substantial improvement in technical computing capability or reduction in cost. Second, identifying the right technology change in time can help ensure that future investments (whether software engineering, procurement planning, or HPC product development) are optimally spent.



However, in a field as fast moving as technical computing, spotting the next disruptive technologies of specific relevance to your individual needs can easily become a full time activity (which is why NAG helps to do this for others).



One very credible candidate for disruptive change in HPC right now is GPU computing (or related products that might be in development). However, at the Newport conference recently, the discussion turned to what the next disruptive technology to hit HPC would be (after the possible GPU disruption). One suggestion, made by John West (of InsideHPC fame), was that the next disruptive technology could be in software, especially programming tools and interfaces. This builds on the fact that parallel computing is no longer a specialist activity unique to the HPC crowd – parallel processors are becoming pervasive across all areas of computing from embedded to personal to workgroup technical computing. Parallel programming is thus heading towards a mass market activity – and the mass market is unlikely to view what we have in HPC currently (Fortran plus MPI and/or OpenMP, or limited tools, etc) with much favour. I’m not knocking any of these, but they are not mass-market interfaces to parallel computing. So perhaps the mass market, through volume of people in need – and companies driven by economics will come up with a “better” solution for interfacing with supercomputers.



As a HPC community we lost control of much of our hardware to the commodity market some years ago. Maybe we now face losing control of our software to the commodity community too.