Author Archives: Stephanie Lai

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 careers 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 careers 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

Research Associate in Numerical Linear Algebra Group – 2 posts

The Numerical Linear Algebra Group at the University of Manchester is seeking two Research Associates to work with Professor Nick Higham on developing and analyzing numerical linear algebra algorithms for current and future high-performance computers.

Topics for investigation include linear equations, linear least squares problems, eigenvalue problems, the singular value decomposition, correlation matrix problems, and matrix function evaluation. This work will exploit multiprecision arithmetic (particularly the fast half precisions available on some recent and forthcoming processors) and techniques such as acceleration and randomization. It will involve using rounding error analysis, statistical analysis, and numerical experiments to obtain new understanding of algorithm accuracy and efficiency.

One of the posts is associated with Professor Higham’s Royal Society Research Professorship. The other post is associated with the EPSRC project Inference, Computation and Numerics for Insights into Cities (ICONIC), which involves Imperial College (Professor Mark Girolami), the University of Manchester (Professor Nick Higham), the University of Oxford (Professor Mike Giles), and the University of Strathclyde (Professor Des Higham).

The closing date is February 11, 2019. For the advert and more details see here.

 

Beyer Chair in Applied Mathematics

The School of Mathematics is seeking to appoint an outstanding mathematical scientist to the Beyer Chair in Applied Mathematics.

The Beyer Chair is a senior professorial position in Applied Mathematics, established in 1881 by an endowment from the industrialist Charles Frederick Beyer.

Applicants will have a distinguished track record of research in one or more areas of Applied Mathematics, defined in its broadest sense, and will play a leading role in the life of the School, by providing inspiring leadership in research, and also through appropriate teaching and service activities.

The closing date is March 22, 2019. For advert and more details see here.

NLA Group Talks at SIAM Conference on Computational Science and Engineering 2019

Members of the Numerical Linear Algebra Group will be giving nine presentations at the upcoming SIAM Computational Science and Engineering (CSE) conference. They are also organizing the two-part minisymposium Advances in Analyzing Floating-point Errors in Computational Science.

The conference will be held at the Spokane Convention Center, Washington, USA, from 25th February to 1st March, 2019.

Here are the dates and times where members of our group will be giving their talks:

Tuesday 26 February
9:45 – 10:05 Sven Hammarling
Standardization of the Batched Blas

Wednesday 27 February
9:45 – 10:05 Theo Mary
A New Approach to Probabilistic Roundoff Error Analysis
14:15 – 14:35 Pierre Blanchard
Algorithm Based Error Analysis for Mixed Precision Matrix Factorizations

Thursday 28 February
8:45 – 9:15 Jack Dongarra
SIAM/ACM Prize in Computational Science and Engineering: The Singular Value Decomposition: Anatomy of an Algorithm, Optimizing for Performance
9:45 – 10:05 Françoise Tisseur
NLEVP: A Collection of Nonlinear Eigenvalue Problems 
10:35-10:55 Steven Elsworth
The Rational Krylov Toolbox
14:15 – 14:35 Nick Higham
Exploiting Half Precision Arithmetic in Solving Ax=b
15:05 – 15:25 Jack Dongarra
Experiments with Mixed Precision Algorithms in Linear Algebra
16:10 – 16:30 Mawussi Zounon
Distributed Tasking in the PLASMA Numerical Library

Friday 1 March
9:45 – 11:25 Srikara Pranesh
Domain Decomposition Method for High Dimensional Stochastic Systems

More information on CSE19 is available here.

Theo Mary awarded the Gilles Kahn prize

The Gilles Kahn prize was awarded to Theo Mary for his PhD thesis Block Low-Rank multifrontal solvers: complexity, performance, and scalability (PDF here). The thesis was prepared at the University of Toulouse, France and co-supervised by Patrick Amestoy and Alfredo Buttari. Theo is currently a Research Associate in the Numerical Linear Algebra group.

The Gilles Kahn prize is awarded each year by the SIF, the French Society of Computer Science, for an excellent PhD thesis in the field of computer science. 

In the thesis, Theo investigated the use of low-rank approximations inside direct, factorization-based methods to reduce the computational cost of the solution of large, sparse systems of linear equations. His work included theoretically computing the asymptotic complexity reduction achieved by these methods and implementing them on parallel computers to translate this theoretical reduction into significant performance gains on both shared- and distributed-memory architectures. The potential and efficiency of these methods was assessed on several industrial applications, notably ones arising in geosciences and structural mechanics.

The official award ceremony will take place at the SIF congress (February  6-7, 2019, in Bordeaux). Theo has also been invited to present his work to the entire scientific community at the SIF congress.

Theo Mary
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