Author Archives: Stephanie Lai

Jack Dongarra elected as Foreign Member of the Royal Society

Jack Dongarra


Professor Jack Dongarra

Jack Dongarra, Professor and Turing Fellow in the School of Mathematics and member of the Numerical Linear Algebra Group, has been elected as a Foreign Member of the Royal Society.  This honour recognizes his seminal contributions to algorithms for numerical linear algebra and the design and development of high performance mathematical software for machines ranging from workstations to the largest parallel computers.

Dongarra’s software and libraries, which include LINPACK, EISPACK, LAPACK, the BLAS, MPI, ATLAS, PLASMA, MAGMA, and PAPI, are universally considered as standards, both in academia and industry. They excel in the accuracy of the underlying numerical algorithms and the reliability and performance of the software. They benefit a very wide range of users through their incorporation into software including MATLAB, Maple, Mathematica, Octave, R, SciPy, and vendor libraries.

The Royal Society is the oldest scientific academy in continuous existence, going back to 1663. Each year the Royal Society elects up to 52 new Fellows and up to 10 new Foreign Members. Fellows and Foreign Members are elected for life on the basis of excellence in science. Each candidate is considered on their merits and can be proposed from any sector of the scientific community.

The full list of the newly elected Fellows and Foreign Members of the Royal Society is available here.

OUR ALUMNI – Sam Relton

In this blog post, we asked one of our alumni, Sam Relton, a few questions about his time with the Numerical Linear Algebra Group.

srelton.jpg

Please can you introduce yourself and tell us a bit about your experience before attending University of Manchester?

I was always pretty good at maths, because I liked understanding how things worked, and so I went to Manchester for my BSc. During that course I really enjoyed the numerical analysis and linear algebra modules because they underpin how all other mathematics is implemented in practice. I loved living in Manchester so I wanted to stick around, and I was lucky enough to be able to skip an MSc and go straight to a PhD in the NLA group.

What was your PhD thesis on?

My thesis was supervised by Nick Higham and called “Algorithms for Matrix Functions, their Frechet Derivatives, and Condition Numbers”. It consisted of four research papers covering theoretical and algorithmic advances in the computation of matrix functions, all woven together. Along with Nick, a few of these papers were co-authored with Awad Al-Mohy (a previous PhD student of Nick’s who was interested in similar problems).

Why did you choose to study your PhD in Manchester?

Manchester is a world-leading research group for numerical linear algebra and it was a privilege to learn from (and work with) the greatest researchers in the field. This also opens up a lot of opportunities in terms of attending conferences, visiting other institutions, and when looking for postdoctoral positions. Manchester is also a fantastic place to live, with plenty going on and a thriving community of PhD and post-doc researchers. I also had a few friends studying other courses that I shared a house with during my undergraduate degree and PhD.

How did you find Manchester?

I loved Manchester, it’s a large busy city full of interesting things to see and do whilst the cost of living is nowhere near that of London. Despite that, you can easily get into the countryside with a 30 minute drive! The maths department was brilliant with plenty of strong research groups to chat with, lots of seminars to attend, and a friendly and open atmosphere between all the staff and students.

Can you tell us about your career since leaving Manchester?

After doing a BSc, PhD, and 2 post-docs in high-performance computing at Manchester I decided to try something new. I now work in the School of Medicine at Leeds, applying complex statistical models and machine learning to electronic healthcare records (taken from GP and hospital databases) with collaborators in the School of Computing. Statistics and machine learning are really just a practical application of linear algebra / HPC, so much of what I learnt during my years in Manchester is still very relevant! Working with large interdisciplinary teams of doctors and nurses is an interesting change, and it’s nice to have direct impact on NHS policy decisions.

Version 4.0 of NLEVP Collection of Nonlinear Eigenvalue Problems

nlevpA new release, version 4.0, is available of the NLEVP MATLAB toolbox, which provides a collection of nonlinear eigenvalue problems. The toolbox has become a standard tool for testing algorithms for solving nonlinear eigenvalue problems.

When it was originally released in 2008, the toolbox contained 26 problems.  The new release contains 74 problems. It is now distributed via GitHub and is available at https://github.com/ftisseur/nlevp.

Further details are given in An Updated Set of Nonlinear Eigenvalue Problems. The collection will grow and contributions are welcome.

The following table shows the 22 new problems in version 4.0 of the toolbox .4.0 NLEVP problems

OUR ALUMNI – Edvin Hopkins

In this blog post, we asked one of our alumni, Edvin Hopkins, a few questions about his time with the Numerical Linear Algebra Group.

Craig Lucas

Please can you introduce yourself and tell us a bit about your experience before attending University of Manchester?

I obtained my BA in Mathematics from the University of Cambridge in 2005 and remained there for a few more years to do a PhD in numerical relativity. My association with the University of Manchester began in 2010, when I joined the NLA group as a KTP Associate, working on a joint project with NAG to implement some of the NLA group’s matrix function algorithms for the NAG Library.

Why did you choose to work with the University of Manchester?

The project I was involved in was a great opportunity to bridge the gap between academia and industry and to work with world leaders in their fields.

How did you find Manchester?

Well, I’m still there! It has really grown on me in the past few years, and is a great place to work.

Can you tell us about your careers since leaving Manchester?

At the end of the KTP project I continued in the NLA group as a post doctoral research associate, working with Professor Nick Higham for a year and half on his ERC-funded project on matrix functions. I then returned to work for NAG (in their Manchester office) which is where I am now. NAG still has very strong links with the University of Manchester and with the NLA group in particular.

What is your current role?

I am a Technical Consultant at NAG. My work involves implementing mathematical algorithms for the NAG Library, and high performance computing consultancy projects.

Our Alumni – Craig Lucas

In this blog post, we asked one of our alumni, Craig Lucas, a few questions about his time with the Numerical Linear Algebra Group.

Craig Lucas

Please can you introduce yourself and tell us a bit about your experience before attending University of Manchester?

I came to study Mathematics a little later than usual. I was a technician civil engineer working in land reclamation in Staffordshire and needed a change! I was always told I was good at maths and thought at 27 I should get a degree. I am very grateful to Graham Bowtell  at City University who took a chance on someone without A-levels. I developed an interest in Numerical Analysis and computing and wanted to take my study as far as I could. That brought me to Manchester for an MSc, and ultimately a PhD.

What was your PhD thesis on?

My thesis, supervised by Nick Higham, was “Algorithms for Cholesky and QR Factorizations, and the Semidefinite Generalized Eigenvalue Problem.” Arguably a rag bag of algorithms building on my MSc experience of symmetric matrices. I also met and worked with Sven Hammarling on QR updating. He then worked for NAG, as I do now.

Why did you choose to study your PhD in Manchester?

During my MSc I realised I was working with world leaders in their field. It wasn’t a difficult decision to stay on for a PhD, in fact, I felt incredibly lucky to have that opportunity.

How did you find Manchester?

I hated it! I had come up from London and it felt that a whole new world. I wasn’t used to strangers talking to me in the street! However, after about 18 months the place really started to grow on me, and now, nearly 20 years later, I can’t imagine living anywhere else. We have an incredible arts scene, fantastic restaurants, brilliant transport links and a cost of living that makes living back in London seem ridiculous.

Can you tell us about your career since leaving Manchester?

Firstly I never really left. In the 15 years since I finished my PhD I have taught on my old MSc, supervised students and several KTP projects jointly with the Numerical Linear Algebra group. After my PhD, I went to work in research computing at Manchester first, in high performance computing (HPC.) Then just over 10 years ago I joined NAG where I could use both my numerical analysis and HPC skills.

What is your current role?

I run NAG’s Manchester Office, which is a rather nice penthouse on Portland Street with a roof terrace, and the HPC team here. I am supervising my third KTP, involved in running NAG’s contribution to the EU POP project and every now and then write some mathematical software.

Our Alumni – Lijing Lin

In this blog post, we asked one of our alumni, Lijing Lin, a few questions about her time with the Numerical Linear Algebra Group.

Lijing Lin at PhD graduation

Please can you introduce yourself and tell us a bit about your experience before attending University of Manchester?

 I obtained my BSc from Nanjing University of Aeronautics and Astronautics and MSc from Fudan University in China, before coming to Manchester to study for my PhD in 2007.

What was your PhD thesis on?

 The title of my thesis is Roots of Stochastic Matrices and Fractional Matrix Powers. Computing roots of stochastic matrices arises from Markov chain models in finance and healthcare where a transition over a certain time interval is needed but only a transition over a longer time interval may be available. Besides developing new theories, we also developed a package for computing stochastic roots. Fractional matrix powers are more general functions than matrix roots. We developed a new algorithm for computing arbitrary real powers of matrices.

Why did you choose to study your PhD in Manchester?

 I had developed an interest in doing research in Numerical Linear Algebra during my MSc. The NLA group in Manchester is renowned for world-leading expertise in this area, and is one of the best places in the world to study and do research.

How did you find Manchester?

 I have studied, worked and lived in Manchester for over 11 years now. It is exciting, diverse and welcoming–a city that keeps growing and never stops surprising me.

Can you tell us about your career since leaving Manchester?

 After graduating, I continued working in Manchester as a Research Associate. With a solid background in NLA, my research now has moved toward machine learning, probabilistic modelling, and statistics.

What is your current role?

 I am currently a Turing PDRA in predictive healthcare. We are building prognostic models that allow consideration of “what if” scenarios to explore the effects of interventions, e.g. how would a person’s risk of getting heart attack change if he started or quit smoking now.

Jack Dongarra Awarded SIAM/ACM Prize in Computational Science and Engineering

Congratulations to Jack Dongarra who recently received the SIAM/ACM Prize in Computational Science and Engineering.

Jack Dongarra will receive the SIAM/ACM Prize in Computational Science and Engineering at the SIAM Conference on Computational Science and Engineering (CSE19) held February 25 – March 1, 2019 in Spokane, Washington. He will receive the award and deliver his prize lecture, “The Singular Value Decomposition: Anatomy of an Algorithm, Optimizing for Performance,” on February 28, 2019.

SIAM and the Association for Computing Machinery (ACM) jointly award the SIAM/ACM Prize in Computational Science and Engineering every two years at the SIAM Conference on Computational Science and Engineering for outstanding contributions to the development and use of mathematical and computational tools and methods for the solution of science and engineering problems. With this award, SIAM and ACM recognize Dongarra for his key role in the development of software and software standards, software repositories, performance and benchmarking software, and in community efforts to prepare for the challenges of exascale computing, especially in adapting linear algebra infrastructure to emerging architectures.

When asked about his research for which the prize was awarded, Dongarra said “I have been involved in the design and development of high performance mathematical software for the past 35 years, especially regarding linear algebra libraries for sequential, parallel, vector, and accelerated computers. Of course, the work that led to this award could not have been achieved without the help, support, collaboration, and interactions of many people over the years. I have had the good fortune of working on a number of high profile projects: in the area of mathematical software, EISPACK, LINPACK, LAPACK, ScaLAPACK, ATLAS and today with PLASMA, MAGMA, and SLATE; community de facto standards such as the BLAS, MPI, and PVM; performance analysis and benchmarking tools such as the PAPI, LINPACK benchmark, the Top500, and HPCG benchmarks; and the software repository netlib, arguably the first open source repository for publicly available mathematical software.”

This article was extracted from SIAM News. Further information is available here.

Professor Jack Dongarra

Professor Jack Dongarra

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