HPC is Now | Supercomputing 2019

In November 2019, the Science and Technology Facilities Council (STFC) Hartree Centre and Scientific Computing Department exhibited at international conference Supercomputing 2019 (SC19) in Denver, USA. In this blog post, Research Software Engineer Tim Powell shares some thoughts and insights from the Hartree Centre team.

Hartree Centre team members attending Supercomputing 2019.

The variety of experiences one can have at Supercomputing is vast, and I think this is a good echo for the direction high performance computing (HPC) is going. The number of different disciplines that are adopting HPC and the different techniques available to acquire your computing power are growing more diverse. When discussing the themes of SC19 with a colleague (in the stationery room of all places) I accidentally summed it up quite well: “Supercomputing 2019 was tall and broad.”

So let’s look at each aspect of this assessment – first up: “tall”. The next phase of supercomputing is exa-scale. There was a significant number of talks, birds-of-a-feather, and panels discussing exa-scale computing, the applications, software, and hardware.

Our Chief Research Officer, Vassil Alexandrov, gives his account of Supercomputing 2019 and the current exa-scale landscape here:

“Supercomputing 2019 was a busy time for me, as always! In the discussions and talks I attended, I felt that this year’s content was of an even higher quality than previous years, and I noted that there were more precise presentations delivered by researchers.

One area which I paid particular attention to was the discussion around exa-scale. The US National Labs are making big moves with their Exa-Scale Computing Project. They are investing $1.8 billion in hardware and a similar amount for the development of software. The current US roadmap is to have their first machine, Frontier, in place in Q3 of 2021 costing an estimated $400 million. With another two machines to be delivered in 2022, each costing $600 million. All 3 machines are expected to be exa-scale and are rumoured to be a combination of AMD, Intel, Cray, and NVIDIA.

Europe are also heading towards exa-scale computing – eight centres across Europe are going to host large peta-scale and pre-exa-scale machines in their program to developing exa-scale capabilities, with machines expecting to reach 150-200 peta-flops. Japan is about to install their Post-K supercomputer which is based on ARM processors and it is likely to be a very efficient machine. The expectation is for it to be operational early 2020 so I am excited to see what the results will be when it is up and running. China is also a player but that is behind closed doors at the moment. It will be interesting to see what they reveal.

Throughout SC19, it was clear that the software challenges are going to be harder than the hardware challenges. My opinion is that we are still a few years off from having true exa-scale machines.”

Vassil Alexandrov chairs the 10th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems for academia and industry alongside Prof. Jack Dongarra (UTK & ORNL), Al Geist (ORNL) and Dr Christian Engelmann at Supercomputing 2019.

Now, let’s talk about how SC19 was broad”.

More so this year, than in previous years, have the different applications of HPC become so obvious. Multitudes of National Laboratories and Research Institutes from around the globe were seen displaying use cases on their stands in the exhibition hall, and there was a large variety of different topics discussed in talks and panels. There was, quite literally, something for everyone – assuming you have an interest or involvement in computation that is!

I think this is largely due to the growth in access to data, and new techniques such as machine learning and artificial intelligence (AI) requiring disciplines that traditionally don’t use HPC to access more computing resource. Additionally, with the massively growing offering of cloud computing resource, the barrier to entry has been significantly reduced and it is easier than ever to provision a cluster-in-the-cloud.

So tall is more powerful computing, and broad is more computing applications. This all accumulates in a bigger impact of High Performance Computing, which again was echoed at SC19 with a series of talks in the 1st HPC Impact Showcase.

My personal highlight this year at SC19 was participating in the Building the Future panel at the 6th SC Workshop on Best Practices for HPC Training and Education. The all-day workshop focused around common challenges for enhancing HPC training and education, and allowed the global community to share experiences and resources to address them. The Building the Future panel focused the discussion around how we as trainers and educators can best prepare for the future of HPC and the training and education needs it will bring. The key take-away from my talk was that there is a diverse future of applications for HPC and we need to help facilitate the power of HPC to non-HPC experts who are only just finding uses for it.

Tim Powell speaks at the Building The Future panel during the 6th SC Workshop on Best Practices for HPC Training and Education.

On the following day I was fortunate enough to attend the Early Careers Program, aimed at people in the first few years of their career in HPC and delivering a variety of activities, talks, and panels. It was great to see STFC represented by Catherine Jones and Alison Kennedy. As a Research Software Engineer (RSE) I particularly enjoyed panels and talks involving RSE and members from the RSE Societies around the globe. It’s great to see that managing research software properly is being put on the international stage at conferences as big as SC! I also noted that in a series of talks on cloud computing, a lot of time was given over to discussing the advantages (rarely the disadvantages) of tailor-made HPC in the cloud.

As a team, we had great fun facilitating a very popular build-your-own Lego supercomputer activity, in the form of our very own Scafell Pike! Needless to say, our limited supplies disappeared quicker and quicker each morning as the word spread. Our HPiC Raspberry Pi cluster was also present, boasting some new and updated demos developed by our recent summer placement students James and Lizzie!

The Hartree Centre takes its supercomputer Scafell Pike to Supercomputing 2019… in Lego form!

I also spoke to some of my colleagues to get their own perspectives on SC19. Aiman Shaikh, Research Software Engineer, discussed her first time at the conference:

“I really enjoyed being part of the Women in HPC workshop, and attending technical talks around containers in HPC and LLVM compilers. The networking events held by different vendors was also a great opportunity to meet people. There was so much going on everywhere that it was difficult to keep pace with everything!

HPC and Cloud Operations at CERN was a very interesting talk by Maria Girone, who talked about technologies used at CERN, software and architecture issues and how they are investigating machine learning (ML) for object detection and reconstruction.

The Women in HPC workshop was really good, especially the keynote from Bev Crair, Lenovo, on “the butterfly effect of inclusive leadership”. Bev said that diverse teams lift performance by inviting in creativity, which I completely agree with. Another inspiring and motivating talk by Hai Ah Nam from Los Alamas National Lab talked about surviving difficult events and minimising their impact to your career. Hai explained that we cannot stop unforeseen events in life but we can focus on how to tackle them. The Women in HPC networking events, often joined by many diverse groups of people, provided a great chance to network with attendees from all different backgrounds.

The journey of exploration did not ended after SC as afterwards I went to the Rockies with some colleagues, which was fun-filled few days walking and with so little light pollution we could see the Milky Way at night!”

Aiman Shaikh gets involved in the Women in HPC workshop at Supercomputing 2019.

SC19 was a new experience for Research Software Engineer Drew Silcock too:

“Attending SC19 for the first time really exposed me to the wider scientific computing community. I gained an understanding of the various technologies used by the scientists and engineers and for what purposes they were used. Many are scaling their applications with standard MPI+ OpenMP stacks, but I attended several interesting workshops and talks about alternative technologies and approaches. Of particular interest to me are all topics relating to the development and programming languages and compilers, so I very much enjoyed hearing from people working on and with the LLVM compiler toolchain, additions to the C++ standard and the development of domain-specific languages for scientific computing.

In terms of trends, it’s exciting to see how many people are starting and continuing to use Python for scientific computing. Cloud services are also becoming increasingly relevant, especially for new companies without on premise capabilities. As machine learning models get bigger and bigger, there is more effort being put into bridging the gaps between the HPC and ML communities to ensure that they can benefit each other.”

Jony Castagna, a NVIDA Deep Learning Ambassador with 10 years experience in HPC and several years experience in Deep Learning, shared his thoughts:

“We’re seeing fast-growing applications of Deep Learning for science. Three different approaches have been identified: support/accelerate current algorithms like via AI precondition or matrix solver through Neural Networks (NN); solve partial differential equation using NN but enforcing physical information (via Physical Informed Neural Networks, PINN); fully replacing physical equations with NN trained using numerical simulation data. In particular this latest approach seems most attractive as it seems to show the capability of NN in learning the physics from data and extrapolate further at higher speed. For example, in the work of Kadupitiya, Fox and Jadhao, a simple NN has been used to predict the contact density of ions in Nanoconfinement using trained data from a Molecular Dynamic (MD) simulation. A strong match between prediction and MD simulation has been presented.

An increasing use of C++17 standard library has emerged for performance portability. Many paradigms, like Kokkos, RAJA, HPX, etc. have been presented as possible solution for targeting different architectures. However, NVIDIA doesn’t look to be standardising the heterogeneous programming, they expect the hardware to become more homogeneous between CPU and GPU. We’d like to test NN with DL_MESO to see how well they perform in reproducing coarse grain simulation. We have also applied for an ECAM2 project to port DL_MESO on C++17 and use Kokkos for performance portability. This will allow us to compare performance with the current CUDA version and understand how well Kokkos can perform.”

James Clark and Aiman Shaikh attend talks by Mellanox Technologies at Supercomputing 2019.

High Performance Software Engineer James Clark concluded:

“On Sunday I presented at the Atos Quantum Workshop. This was a showcase of how the Hartree Centre is using our Quantum Learning Machine, such as our joint training and access programme with Atos and our ongoing project work with Rolls-Royce.

I also talked about our future plans to develop quantum software that can take advantage of both quantum computing and HPC.

One of the most interesting developments in HPC this year was how far ARM CPUs have come. Riken and Fujitsu’s Fugaku is one of the major success stories, with the first deployment of the new SVE (Scalable Vector Extensions) instructions. Fujitsu announced that Cray will be bringing their ARM CPUs to the rest of the world. NVidia also announced that their GPGPUs will be supported on ARM platforms, with a number of ARM CPUs listed as supported on release. I am looking forward to the increased competition in the hardware space turns out, especially with AMD’s Rome CPUs and Intel’s Xe GPUs. The future of HPC looks to be very interesting and it’s an exciting time to be involved.”

I couldn’t have said it better myself!

Caught in the data loop?

Fresh from the Open Data Institute (ODI) Summit 2019 and bursting with questions, Holly Halford, Science and Business Engagement Manager for the STFC Hartree Centre, explores the use of personal data for online marketing and asks: how do we stop ourselves getting stuck in the data loop?

So, your friend is getting married. You post a few harmless pictures on Instagram, throwing in a few #wedding tags for good measure. The next day, you’re scrolling through your social media feeds and perusing news sites only to find that every sponsored post, every inch of ad space is now trying to sell you wedding dresses. Wedding venues. Wedding fayres. Decorative wedding trees. Things you didn’t even know existed – all useless to you and, presumably, the advertiser – but the ads are still there, taking up precious mindshare.

But you asked for this – you were the one who carelessly hashtagged your way into the echo chamber… right?

From targeted advertising to political persuasion, whether to help or hinder us, our personal data is being used on a daily basis to effect changes in our behaviour. From the extra purchase you didn’t really need to make, to the life milestones you are forced to start thinking about because your data fits a certain demographic.

New research, conducted by the ODI and YouGov and published to coincide with the recent ODI Summit 2019, concluded that nearly 9 in 10 people (87%) feel it is important that organisations they interact with use data about them ethically – but ethical means different things in different contexts to different people. In discussion at the conference, Prof. Nigel Shadbolt and Sir Tim Berners-Lee highlighted that research shows people are reasonably accepting of personal data being used for targeted advertising, but less amenable to it being used for political advertising. Tim proposed a possible reasoning for this, positioning himself as in favour of targeted commercial advertising – at least towards himself – as it generally helps to find the things you want faster, and also helps companies to make the sales that keep them in business. A “win-win” for both consumer and economy, then.

Sir Tim Berners-Lee in conversation with Professor Nigel Shadbolt and Zoe Kleinman at the ODI Summit 2019.

He suggested that political advertising is different in nature because it may make people act in a way that isn’t truly in their own personal best interest due to a manipulation or misrepresentation of information. It’s of course, possible to argue that the same can be true of misleading commercial advertising but the potential impacts are almost always limited to being purely financial – spending money you didn’t need to, getting into debt etc – and these ramifications are not significantly different to the pitfalls of marketing via any other route. Traditional print media, billboards or television advertising have all probably promised you a better life at some point, if you just buy that car, that smartphone or that deodorant.

Tim has a point – targeted advertising can be useful and makes some logical sense, especially if we have actively searched for related terms or shown our interest in a certain product or service by interacting with content related to it. Despite how 1984 it can feel sometimes, I’m actually personally much more comfortable with data-driven advertising based around our active behaviors as opposed to the other option – the demographic based approach, which I feel has the potential to be far more insidious.

There’s a beauty product advert in my Facebook feed. If I click on the “why am I seeing this” feature, I am quickly informed that Company X “is trying to reach females aged 25 to 54”. Whilst the transparency is a welcome change, it doesn’t fill me with hope that a significant proportion of the media thrust upon us each day is tailored based on nothing more than gender or other divisive demographics. I often wonder how many men have beauty product adverts showing up in their feeds compared to say… cars, watches, sporting equipment? (I unscientifically and anecdotally tested this theory on a colleague recently, a man in a similar age bracket to myself. He reported an unusually high capacity of DIY ads.)

Credit: Death To Stock

The data bias is there, entrenched in historic trends that have potentially damaging consequences in the perpetuation of gender stereotypes and more – if your demographic fits the initial (and undoubtedly biased) statistical trend, do we now, via data-driven marketing, perpetuate it for all eternity?

But how do we address the very fundamentals of marketing and communications without perpetuating stereotypes and pushing conformity to social norms? As a marketing and communications professional, I confess that the commonly used concept of developing “personas” to describe your target audience and help articulate your message more clearly to them has never sat well with me, because those personas by nature are based on stereotypes and assumptions. Knowing your audience is an absolutely crucial pillar of marketing, but if you only ever acknowledge an existing or expected audience, how do you access new markets and prevent alienating potential customers outside of that bracket? Not to mention the ethical concerns this approach flags up. We need to take a more creative approach to get messages heard without excluding anyone. It may not be the easiest route but I’m certain that it is possible, more ethical and when executed successfully, more effective.

So, what can we, as consumers, do to prevent trapping ourselves with our own hashtags and search terms? The current options seem fairly lacking. Perhaps we can turn to AI-driven discovery of “things you might enjoy”. Features like this can be found on most common media platforms, with varying degrees of success. But as the algorithms get more accurate, the tighter the loop closes. As Tim purported, the intention is to be helpful and save us time – if only to provide a good user experience that keeps you invested in using the platform, of course – but everything it suggests will be based on existing tastes and activity. If you’re predisposed to playing Irish folk music, good luck getting Spotify to suggest you might have an undiscovered a passion for post-progressive rock.

Credit: Death To Stock

This presents a bigger problem when considering the landscape of opinions, causes and politics. The idea of social media curating our own personal echo chambers and arenas of confirmation bias is not a new one. It’s true that we can subscribe to contrasting interest groups, a tactic some journalists have been using – but how many of us have the patience to subject ourselves to a cacophony of largely irrelevant content, if it’s not a professional requirement? A more pressing question is: if we don’t interact positively (or at all) with that “alternate” content, does another algorithm begin to de-prioritise it until we no longer see it anyway and we’re back where we started?

Is the answer in a change of algorithms, then? The tactic of ignoring trends and demographics seems to be entirely at odds with the notion of creating better, more accurate AI algorithms and data-driven technologies. Whether we like it or not, they are meant to do exactly that – generate accurate predictions based on statistically evidenced trends and demographics. I feel quite strongly that a great deal more creative thought is required to ensure that ethical practices and regulations are instigated in line with the pace of technological advancement, and prevent data-driven marketing from driving us round in circles for the foreseeable future.

Afterword: I wrote the majority of this blog post before the launch of the Contract for the Web recently announced by Sir Tim Berners-Lee. It presents an encouraging and much needed first step towards safeguarding all the opportunities the internet presents and championing fairness, safety and empowerment. Now, let’s act on it.