̽��ֱ�� of Cambridge - Paul Alexander

Design work on ‘brain’ of world’s largest radio telescope completed

sc604 — Thu, 09 May 2019 09:47:47 +0000

̽��ֱ��SKA’s Science Data Processor (SDP) consortium has concluded its engineering design work, marking the end of five years’ work to design one of two supercomputers that will process the enormous amounts of data produced by the SKA’s telescopes.

̽��ֱ��SDP consortium, led by the ̽��ֱ�� of Cambridge, has designed the elements that will together form the ‘brain’ of the SKA. SDP is the second stage of processing for the masses of digitised astronomical signals collected by the telescope’s receivers. In total, close to 40 institutions in 11 countries took part.

̽��ֱ��UK government, through the Science and Technology Facilities Council (STFC), has committed £100m to the construction of the SKA and the SKA Headquarters, as its share as a core member of the project. ̽��ֱ��global headquarters of the SKA Organisation are located in the UK at Jodrell Bank, home to the iconic Lovell Telescope

“It’s been a real pleasure to work with such an international team of experts, from radio astronomy but also the High-Performance Computing industry,” said Maurizio Miccolis, SDP’s Project Manager for the SKA Organisation. “We’ve worked with almost every SKA country to make this happen, which goes to show how hard what we’re trying to do is.”

̽��ֱ��role of the consortium was to design the computing hardware platforms, software, and algorithms needed to process science data from the Central Signal Processor (CSP) into science data products.

“SDP is where data becomes information,” said Rosie Bolton, Data Centre Scientist for the SKA Organisation. “This is where we start making sense of the data and produce detailed astronomical images of the sky.”

To do this, SDP will need to ingest the data and move it through data reduction pipelines at staggering speeds, to then form data packages that will be copied and distributed to a global network of regional centres where it will be accessed by scientists around the world.

SDP itself will be composed of two supercomputers, one located in Cape Town, South Africa and one in Perth, Australia.

“We estimate SDP’s total compute power to be around 250 PFlops – that’s 25% faster than IBM’s Summit, the current fastest supercomputer in the world,” said Maurizio. “In total, up to 600 petabytes of data will be distributed around the world every year from SDP –enough to fill more than a million average laptops.”

Additionally, because of the sheer quantity of data flowing into SDP: some 5 Tb/s, or 100,000 times faster than the projected global average broadband speed in 2022, it will need to make decisions on its own in almost real-time about what is noise and what is worthwhile data to keep.

̽��ֱ��team also designed SDP so that it can detect and remove manmade radio frequency interference (RFI) – for example from satellites and other sources – from the data.

“By pushing what’s technologically feasible and developing new software and architecture for our HPC needs, we also create opportunities to develop applications in other fields,” said Maurizio.

High-Performance Computing plays an increasingly vital role in enabling research in fields such as weather forecasting, climate research, drug development and many others where cutting-edge modelling and simulations are essential.

Professor Paul Alexander, Consortium Lead from Cambridge’s Cavendish Laboratory said: “I’d like to thank everyone involved in the consortium for their hard work over the years. Designing this supercomputer wouldn’t have been possible without such an international collaboration behind it.”

An international group of scientists led by the ̽��ֱ�� of Cambridge has finished designing the ‘brain’ of the Square Kilometre Array (SKA), the world’s largest radio telescope. When complete, the SKA will enable astronomers to monitor the sky in unprecedented detail and survey the entire sky much faster than any system currently in existence.

Designing this supercomputer wouldn’t have been possible without such an international collaboration behind it

Paul Alexander

SKA Organisation

Artist’s impression of the full Square Kilometre Array at night

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Masters of the universe

sc604 — Fri, 19 Jun 2015 12:44:01 +0000

Imagine having to design a completely automated system that could take all of the live video from all of the hundreds of thousands of cameras monitoring London, and automatically dispatch an ambulance any time any person falls and hurts themselves, anywhere in the city, without any human intervention whatsoever. That is the scale of the problem facing the team designing the software and computing behind the world’s largest radio telescope.

When it becomes operational in 2023, the Square Kilometre Array (SKA) will probe the origins, evolution and expansion of our universe; test one of the world’s most famous scientific theories; and perhaps even answer the greatest mystery of all — are we alone?

Construction on the massive international project, which involves and is funded by 11 different countries and 100 organisations, will start in 2018. When complete, it will be able to map the sky in unprecedented detail — 10,000 times faster and 50 times more sensitively than any existing radio telescope — and detect extremely weak extraterrestrial signals, greatly expanding our ability to search for planets capable of supporting life.

̽��ֱ��SKA will be co-located in South Africa and Australia, where radio interference is least and views of our galaxy are best. ̽��ֱ��instrument itself will be made up of thousands of dishes that can operate as one gigantic telescope or multiple smaller telescopes — a phenomenon known as astronomical interferometery, which was developed in Cambridge by Sir Martin Ryle almost 70 years ago.

“ ̽��ֱ��SKA is one of the major big data challenges in science,” explains Professor Paul Alexander, who leads the Science Data Processor (SDP) consortium, which is responsible for designing all of the software and computing for the telescope. In 2013, the ̽��ֱ��’s High Performance Computing Service unveiled ‘Wilkes’ — one of the world’s greenest supercomputers with the computing power of 4,000 desktop machines running at once, and a key test-bed for the development of the SKA computing platform.

During its projected 50-year lifespan, the SKA will carry out several experiments to study the nature of the universe. Cambridge researchers will focus on two of these, the first of which will follow hydrogen through billions of years of cosmic time.

“Hydrogen is the raw material from which everything in the universe developed,” says Alexander. “Everything we can see in the universe and everything that we’re made from started out in the form of hydrogen and a small amount of helium. What we want to do is to figure out how that happened.”

̽��ֱ��second of the two experiments will look at pulsars — spinning neutron stars that emit short, quick pulses of radiation. Since the radiation is emitted at regular intervals, pulsars also turn out to be extremely accurate natural clocks, and can be used to test our understanding of space, time and gravity, as proposed by Einstein in his general theory of relativity.

By tracking a pulsar as it orbits a black hole, the telescope will be able to examine general relativity to its absolute limits. As the pulsar moves around the black hole, the SKA will follow how the clock behaves in the very strong gravitational field.

“General relativity tells us that massive objects like black holes warp the space–time around them, and what we call gravity is the effect of that warp,” says Alexander. “This experiment will enable us to test our theory of gravity with much greater precision than ever before, and perhaps even show that our current theories need to be changed.”

Although the SKA experiments will tell us much more than we currently know about the nature of the universe, they also present a massive computing challenge. At any one time, the amount of data gathered from the telescope will be equivalent to five times the global internet traffic, and the SKA’s software must process that vast stream of data quickly enough to keep up with what the telescope is doing.

Moreover, the software also needs to grow and adapt along with the project. ̽��ֱ��first phase of the SKA will be just 10% of the telescope’s total area. Each time the number of dishes on the ground doubles, the computing load will be increased by more than the square of that, meaning that the computing power required for the completed telescope will be more than 100 times what is required for phase one.

“You can always solve a problem by throwing more and more money and computing power at it,” says Alexander. “We have to make it work sensibly as a single system that is completely automated and capable of learning over time what the best way of getting rid of bad data is. At the moment, scientists tend to look at data but we can’t do that with the SKA, because the volumes are just too large.”

̽��ֱ��challenges faced by the SKA team echo those faced in many different fields, and so Alexander’s group is working closely with industrial partners such as Intel and NVIDIA, as well as with academic and funding partners including the Universities of Manchester and Oxford, and the Science and Technology Facilities Council. ̽��ֱ��big data solutions developed by the SKA partners to solve the challenges faced by a massive radio telescope can then be applied across a range of industries.

One of these challenges is how to process data efficiently and affordably, and convert it into images of the sky. ̽��ֱ��target for the first phase of the project is a 300 ‘petaflop’ computer that uses no more than eight megawatts of power: more than 10 times the performance of the world’s current fastest supercomputer, for the same amount of energy. ‘Flops’ (floating point operations per second) are a standard measure of computing performance, and one petaflop is equivalent to a million billion calculations per second.

“ ̽��ֱ��investment in the software behind the SKA is as much as €50 million,” adds Alexander. “And if our system isn’t able to grow and adapt, we’d be throwing that investment away, which is the same problem as anyone in this area faces. We want the solutions we’re developing for understanding the most massive objects in the universe to be applied to any number of the big data challenges that society will face in the years to come.”

Inset images: Artist's impression of the SKA, which will be made up of thousands of dishes that operate as one gigantic telescope (SKA Organisation); Professor Paul Alexander ( ̽��ֱ�� of Cambridge).

̽��ֱ��‘world’s largest IT project’ — a system with the power of one hundred million home computers — may help to unravel many of the mysteries of our universe: how it began, how it developed and whether humanity is alone in the cosmos.

This experiment will enable us to test our theory of gravity with much greater precision than ever before, and perhaps even show that our current theories need to be changed

Paul Alexander

SKA Organisation

Artist's impression of the SKA, which will be made up of thousands of dishes that operate as one gigantic telescope

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Big Data – getting to the heart of the Information Revolution

lw355 — Mon, 01 Jun 2015 11:11:34 +0000

Our unprecedented ability to collect, store and analyse data is opening up new frontiers in science and the humanities, from extending our knowledge of how the universe is built, to creating new understanding of the genetic basis of disease, to discovering the impact of schools on pupil achievement.

It’s causing us to challenge not only long-held ideas about what is possible in research, but also to reflect on the value that we place upon ever-increasing quantification and the effect of pervasive data collection on our role as citizens.

‘Big Data’ has also been highlighted by the UK government as among the country’s ‘Eight Great Technologies’ that will help drive economic growth.

But what actually is big data? Collecting and analysing data on individuals, societies and all aspects of the natural world, is routine in research. So why the current preoccupation with the ‘bigness’ of data?

Part of this is the sheer deluge of data that we are now able to collect and store. Back in 2010, Google CEO Eric Schmidt declared that every two days we create as much information as we did from the dawn of civilisation up until 2003. And that was five years ago.

Of course size doesn’t always matter – sometimes big data can mean large datasets that are incredibly messy, with missing or corrupt information, which requires complex mathematical algorithms to make sense of it all.

Another aspect of the current interest in big data is the realisation that just because we can collect data doesn’t mean we are making the best use of it. In fact, big data is often described as data exceeding our ability to handle it, and for which new analytical methods are required to extract useful information. But this is clearly a moving target, and research is urgently needed to keep up.

Recognising this, the government announced earlier this year that the new £42 million Alan Turing Institute, to be based in London, will carry out research in organising, storing and interrogating big data, headed by the universities of Cambridge, Edinburgh, Oxford, Warwick and UCL.

A more subtle distinction that sets ‘big data’ apart from just ‘data’ is in the combination of factors that describe it, the so-called ‘Big Vs of Big Data’, including:

its Volume in terms of size, or the number of variables needed to describe it,
its Velocity, in how it’s collected and processed in real-time,
the Variety of its diverse, linked and unstructured datasets,
its Veracity in terms of where it originates from and how complete it is,
and finally its Value, and especially how the use, linkage and re-use of data can provide crucial new insights that may have been unforeseen at the time the data was collected.

Cambridge researchers are at the forefront of solving many of the challenges that big data presents. New machine learning algorithms are being developed, to the point that machines can now automate some very human tasks, like image recognition, reading and annotating text, or even writing documents in plain English.

For the very biggest big data projects such as the Large Hadron Collider and the Square Kilometre Array, Cambridge researchers are designing new methods to deal with huge data volumes and clever analytics to understand the fundamental makeup of matter and the origins of the universe.

Developing new mathematics and the algorithms to handle this data explosion go hand in hand with improving the storage and computing infrastructure underlying the big data revolution. Cambridge is home to Wilkes, one of the world’s most energy-efficient supercomputers, while scientists in the Computer Laboratory are building a test-bed data centre, where large-scale ‘experiments’ can be done in a safe environment to optimise the data centres of the future.

And what of the data that we personally generate in our everyday lives? Our researchers are asking whether what we share on social media could tell us about ourselves, how best to take the data captured in hospital records to improve patient treatment and if newly available datasets can be used to uncover corruption and misuse of public funds.

Questions of privacy, anonymity and consent are a crucial component of our research, and require engagement from governments, lawmakers, ethicists and, by consultation, the public. In a world where datasets can be linked together, where the breadcrumb trail that we leave as we go about our online and offline lives can be recorded, analysed and converted into a detailed picture of our behaviour, movements, actions and thoughts, a radical change to the way we conceive of these notions is taking place.

In order to make practical use of what we learn from these data, distillation and visualisation of the central information is key, and doing so in a way which is robust, comprehensible and actionable relies not only on advances in science but in our statistical literacy and a critical understanding of what the data can tell us, and what is left out.

And in the rush to convert our world into pixels and numbers, perspectives from the humanities and social sciences are needed more than ever before. What are the implications of data-driven hypothesis development for the practice of science, and for how evidence is used to make policy? What room does this data-driven society leave for aspects of the world that cannot be captured by computers? How does big data supplant or shore-up existing power structures?

To answer these questions requires a meeting of minds – between those working with the statistics, mathematics and algorithms underlying the new field of ‘data science’ and the computer scientists and engineers who are building systems to store and manage data, along with those who can offer perspectives in the social sciences and humanities to ensure that big data can deliver benefits in a sustainable and appropriate way. To this end, in 2013, the ̽��ֱ�� created Cambridge Big Data, a Strategic Research Initiative that brings together a diverse research community to allow Cambridge to respond to the ever-increasing challenges of big data.

Professor Paul Alexander (Chair) and Dr Clare Dyer-Smith (Coordinator) Cambridge Big Data

Big data has captured the world’s attention, with talk of a new Industrial Revolution based on information, and of data being one of the 21st century’s most valuable commodities. Today, we commence a month-long focus on research that uses, produces and interrogates huge datasets.

Cambridge researchers are at the forefront of solving many of the challenges that big data presents

Paul Alexander and Clare Dyer-Smith, Cambridge Big Data

Andy Wilkinson

̽��ֱ��Twingl mind

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Cambridge announced as one of five key partners in new national Alan Turing Institute

cjb250 — Wed, 28 Jan 2015 10:00:00 +0000

̽��ֱ��Alan Turing Institute will promote the development and use of advanced mathematics, computer science, algorithms and ‘Big Data’ – the collection, analysis and interpretation of immense volumes of data – for human benefit. Located at the British Library in London, it will bring together leaders in advanced mathematics and computing science from the five of the UK’s most respected universities – Cambridge, Edinburgh, Oxford, UCL and Warwick – and partners.

Dr Cable said: “Alan Turing’s genius played a pivotal role in cracking the codes that helped us win the Second World War. It is therefore only right that our country’s top universities are chosen to lead this new institute named in his honour.

“Headed by the universities of Cambridge, Edinburgh, Oxford, Warwick and UCL - the Alan Turing Institute will attract the best data scientists and mathematicians from the UK and across the globe to break new boundaries in how we use big data in a fast moving, competitive world.”

̽��ֱ��delivery of the Institute is being coordinated by the Engineering and Physical Sciences Research Council (EPSRC), which invests in research and postgraduate training across the UK. ̽��ֱ��Institute is being funded over five years with £42 million from the UK government. ̽��ֱ��selected university partners will contribute further funding. In addition, the Institute will seek to partner with other business and government bodies.

Professor Philip Nelson, EPSRC’s Chief Executive said: “ ̽��ֱ��Alan Turing Institute will draw on the best of the best academic talent in the country. It will use the power of mathematics, statistics, and computer science to analyze Big Data in many ways, including the ability to improve online security. Big Data is going to play a central role in how we run our industries, businesses and services. Economies that invest in research are more likely to be strong and resilient; the Alan Turing Institute will help us be both.”

̽��ֱ�� ̽��ֱ�� of Cambridge has a strong historical association with Alan Turing, who studied as an undergraduate from 1931 to 1934 at King's College, from where he gained first-class honours in mathematics. Research at Cambridge continues his legacy of groundbreaking work in mathematics and computer science, extending into many areas that he helped pioneer, including mathematical biology, language modelling, statistical inference and artificial intelligence.

Cambridge researchers will play a critical role in shaping the research agenda for the Alan Turing Institute, bringing in world experts in mathematics, statistics, computer science and information engineering, and linking to the research challenges of the future, such as the study of huge genomic datasets, or the development of the world’s largest radio telescope, the Square Kilometre Array.

In 2013, the ̽��ֱ�� created Cambridge Big Data, a cross-School strategic initiative bringing together experts in a number of themes. These range from the fundamental technologies of data science, to applications in disciplines as diverse as astronomy, clinical medicine and education, as well as experts exploring the ethical, legal, social and economic questions that are critical to making data science work in practice. ̽��ֱ��research developed at the Alan Turing Institute will link to the first of these themes, allowing for a rich exchange of ideas within a broad researcher community, and a joined-up and multidisciplinary approach to the big data challenges of the future.

Professor Paul Alexander, who heads Cambridge Big Data, said: “Modern technology allows for the collection of immense volumes of data, but the challenge of converting this ‘Big Data’ into useful information is enormous. ̽��ֱ��Alan Turing Institute is an immensely exciting opportunity for the collective expertise of Cambridge and its partners to rise to this very important challenge and make a huge contribution to the future success of the UK economy, our ability to provide health and societal benefits and the ability of British universities to remain at the cutting edge of research.”

̽��ֱ�� ̽��ֱ�� of Cambridge is to be one of the five universities that will lead the new Alan Turing Institute, announced the Rt Hon Dr Vince Cable, Secretary of State for Business, Innovation and Skills today.

Alan Turing’s genius played a pivotal role in cracking the codes that helped us win the Second World War. It is therefore only right that our country’s top universities are chosen to lead this new institute named in his honour

Vince Cable

r2hox

Big Data

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