Author Archives: Stephanie Lai

Nick Higham Named 2020 ACM Fellow

Professor Nick Higham has been named among the 2020 Association for Computing Machinery (ACM) Fellows, who are recognised for work underpinning contemporary computing.

The accomplishments of the 2020 ACM Fellows have driven innovations that have ushered in significant improvements across many areas of technology, industry, and personal life.

Nick has been recognised for his contributions to numerical linear algebra, numerical stability analysis, and communication of mathematics.

He is among 95 ACM Fellows, representing universities, corporations and research centres around the world, who are celebrated for their wide-ranging and fundamental contributions in areas including artificial intelligence, cloud computing, computer graphics, virtual reality, and more.

The ACM Fellows programme recognises the top 1% of ACM members for their outstanding accomplishments in computing and information technology and/or outstanding service to ACM and the larger computing community. Fellows are nominated by their peers, with nominations reviewed by a distinguished selection committee.

ACM President Gabriele Kotsis said: “The 2020 ACM Fellows have demonstrated excellence across many disciplines of computing. These men and women have made pivotal contributions to technologies that are transforming whole industries, as well as our personal lives. We fully expect that these new ACM Fellows will continue in the vanguard in their respective fields.”

Professor Nicholas J. Higham, University of Manchester

Numerical Linear Algebra Group Activities 2020

The Numerical Linear Algebra Group had a productive year in 2020, despite working remotely from March onwards because of the pandemic. This post summarizes what we got up to. Publications are not included here, but many of them can be found on MIMS EPrints under the category Numerical Analysis; see also these news stories about our publications.

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Craig Lucas, Nick Higham, Xinye Chen, Steven Elsworth, Xiaobo Liu, Michael Connolly, Mantas Mikaitis, Len Freeman, Massimiliano Fasi, Pierre Blanchard, Sven Hammarling, Asad Raza Aitor Mehasi Mehasi, Stephanie Lai, Gian Maria Negri Porzio, Thomas McSweeney, Mawussi Zounon, Françoise Tisseur, Srikara Pranesh, Yuqing Zhang, Eleni Vlachopoulou, March 2020.

Software

We make our research codes available as open source, principally on GitHub; see the repositories of ConnollyFasiHighamLiuPranesh, Tisseur, and Zounon.

We also put MATLAB software on MATLAB Central File Exchange and on our own web sites, e.g., the Rational Krylov Toolbox (RKToolbox).

PhD Students

We welcomed new PhD students Xinye Chen and Thomas Seleiro.

Steven Elsworth successfully defended his PhD thesis Rational Krylov Methods and Machine Learning Approaches to Time Series Forecasting in March 2020 .

Michael Connolly took an internship with MathWorks from July to September 2020.

Postdoctoral Research Associates (PDRAs)

Mantas Mikaitis, previously an EPSRC Doctoral Prize Fellow in the group, is now working on the ICONIC project in the group.   During the year he successfully defended his PhD thesis Arithmetic Accelerators for a Digital Neuromorphic Processor in the Department of Computer Science.

Massimiliano Fasi left the group in September 2020 and is now working at Örebro University in Sweden.

Roberto Cahuantzi  was a member of the group from March to September 2020, working with Stefan Güttel.

Recognition and Service

Jack Dongarra received the 2020 IEEE Computer Society’s Computer Pioneer Award.

Srikara Pranesh and Michael Connolly won first and second best poster prizes, respectively, at the SIAM UKIE Section Meeting, Edinburgh, January 2020.

Françoise Tisseur received the London Mathematics Society’s Fröhlich Prize.

Theo Mary received an honourable mention for the 2020 Householder Prize and the 2021 SIAG/LA Early Career Prize. He also received a grant from the Faculty of Engineering Sciences of Sorbonne University for a project on”Mixed precision algorithms for HPC”.

Sixteen publications by members of the NLA group feature among the top 40 most read articles in two SIAM journals, both leading venues for publications in numerical linear algebra.

Stefan  Güttel was awarded the 2021 James H. Wilkinson Prize in Numerical Analysis and Scientific Computing.

Nick Higham received the IMA Gold Medal 2020.

Theo Mary has been awarded the 2021 SIAG/LA Early Career Prize by the SIAM Activity Group on Linear Algebra.

Grants

Stefan Güttel’s and Nick Higham’s Alan Turing Fellowships have been extended by one year to September 2021.

Stefan Güttel received a Small Project Grant from the Alan Turing Institute.

Nick Higham and Françoise Tisseur received funding for work on multi-precision algorithms from Lawrence Livermore National Laboratory under the Exascale Computing Project.

Nick Higham and Françoise Tisseur received funding from The MathWorks, Inc. to support a PhD student to work on exploiting multiprecision arithmetic.

Massimiliano Fasi is one of the participants of the 2020 INdAM-GNCS project “Low-rank methods for linear algebra problems with data-sparse structure” funded by the Scientific Computing Group of the Istituto Nazionale di Alta Matematica “Francesco Severi”.

External Presentations

SIAM UKIE Annual Meeting 2020, Edinburgh, January 10: Connolly, Liu, Negri Porzio, Pranesh, Higham, Pranesh and Tisseur.
SIAM Conference on Parallel Processing for Scientific Computing (PP20) in Seattle, Washington, US, February 12 – 15: Fasi, Mary, Mikaitis, Pranesh and Zounon.
Theo Mary, Performance and Accuracy of Mixed-Precision Matrix Factorizations, SIAM PP20, February, 2020.
Srikara Pranesh, Point Arithmetic for the Solution of Linear System of Equations, SIAM PP20, February, 2020.
Mawussi Zounon, Opportunities for Multi Precision Computation in Memory Bound Applications, SIAM PP20, February, 2020.
Nick Higham, Are Numerical Linear Algebra Algorithms Accurate at Extreme Scale and at Low Precisions?, in E-NLA Online seminar series on Numerical Linear Algebra, April 29, 2020.
Nick Higham, Random Orthogonal Matrices in High Performance Computing, Masked Guest Speaker, King Abdullah University of Science and Technology, 2020.
Nick Higham, The Anatomy of the World’s Fastest Linear Equation Solver, Online Distinguished Lecture, The Hong Kong Polytechnic University, September 2020.
Theo Mary, Mixed Precision Low Rank Compression of Data Sparse Matrices, Communications in NLA, online, September 2020.
Nick Higham, Rehabilitating Correlations, Leicester Actuarial Science Society and Students Union Mathematical Society, 2020.
Theo Mary, Mixed precision arithmetic: hardware, algorithms and analysis, London Mathematical Society Virtual Graduate Student Meeting, November, 2020.
Nick Higham, Mathematics of today’s floating-point arithmetic, London Mathematical Society Naylor Lecture, November 20, 2020.
Françoise Tisseur, Towards Reliable Eigensolvers for Nonlinear Eigenvalue Problems, in E-NLA Online seminar series on Numerical Linear Algebra, November 25, 2020.

Other Notable Tweets

Theo Mary Awarded the 2021 SIAG/LA Early Career Prize

Dr Theo Mary, a CNRS researcher at Sorbonne University (Paris) and a former postdoctoral researcher in the Numerical Linear Algebra Group (2018-2019), has been awarded the SIAG/LA Early Career Prize by the SIAM Activity Group on Linear Algebra.

The SIAM Activity Group on Linear Algebra (SIAG/LA) awards the SIAG/LA Early Career Prize every three years to one post-PhD early career researcher in the field of applicable linear algebra for outstanding contributions to the field within six years of receiving the PhD or equivalent degree as of January 1 of the award year. The selection committee wishes to recognize Theo for his “significant contributions to linear algebra topics, including block low rank methods, software development, probabilistic rounding error analysis, mixed precision arithmetic, and backward error analysis.”

The prize will be awarded at the 2021 SIAM Conference on Applied Linear Algebra (LA21), to be held on a virtual platform May 17-21, 2021.

Nick Higham Awarded the IMA Gold Medal 2020

Professor Nick Higham has been awarded the IMA Gold Medal 2020 by the Institute of Mathematics and its Applications. Institute Gold Medals are awarded every two years in recognition of outstanding contributions to mathematics and its applications.

This is the second such success for a member of the Department of Mathematics: Professor Fritz Ursell won the IMA Gold Medal 1994.

The full prize citation is available here.

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Professor Nicholas J. Higham, University of Manchester

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Stefan Güttel awarded the 2021 SIAM James H. Wilkinson Prize

Dr Stefan Güttel will receive the 2021 James H. Wilkinson Prize in Numerical Analysis and Scientific Computing. This prestigious prize, established in 1979, is awarded every four years by the Society for Industrial and Applied Mathematics (SIAM). SIAM is the world’s largest professional association devoted to applied mathematics with over 14,000 individual members.
 
Dr Güttel’s research is in computational mathematics, and in particular, in efficient numerical algorithms for high-dimensional problems. The prize recognizes his contributions to the analysis, implementation, and application of rational and block Krylov methods. These methods have recently become very popular for the efficient solution of large eigenvalue problems, matrix equations, and in model order reduction.
 
Dr Güttel’s work is applicable to a wide range of problems in science and engineering. He maintains active collaborations with other Departments and companies such as Arup, Autotrader, AspenTech, N Brown Group, and Schlumberger-Doll Research. He also holds a fellowship with the Alan Turing Institute, the UK’s national institute for data science and artificial intelligence.
 
Dr Güttel will deliver a prize lecture at the 2021 SIAM Conference on Computational Science and Engineering (CSE21), to be held on a virtual platform in March 2021.
 
guettel

NLA Group Articles Amongst Most Read In SIAM Journals

simax-siscSixteen publications by members of the NLA group feature among the top 40 most read articles in two SIAM journals, both leading venues for publications in numerical linear algebra. 

The following articles are amongst the 20 most read in the SIAM Journal on Matrix Analysis and Applications:

The following articles are amongst the 20 most read in the SIAM Journal on Scientific Computing:

The full lists (updated daily) are available here and here

2020 NLA group photo

This year’s group photo was taken on March 5, 2020 after the NLA group meeting. Most group members are in the photo; those missing include Jack Dongarra, Stefan Güttel, Ramaseshan Kannan and Marcus Webb. 

The banner on this website has also been updated with the new group photo.  A high resolution version of the photo is available here.

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By row from the back: Craig Lucas, Nick Higham, Xinye Chen, Steven Elsworth, Xiaobo (Bob) Liu, Michael Connolly, Mantas Mikaitis, Len Freeman, Massimiliano Fasi, Pierre Blanchard, Sven Hammarling, Asad Raza Aitor Mehasi Mehasi, Stephanie Lai, Gian Maria Negri Porzio, Thomas McSweeney Mawussi Zounon, Françoise Tisseur, Srikara Pranesh, Yuqing (Mila) Zhang, Eleni Vlachopoulou.

NLA Group at the SIAM Conference on Parallel Processing for Scientific Computing

Several members of the group attended the SIAM Conference on Parallel Processing for Scientific Computing held in Seattle on February 12-15, 2020.

The presentations given are as follows:

Nick Higham and Srikara Pranesh also organised a two part mini-symposium (Advances in Algorithms Exploiting Low Precision Floating-Point Arithmetic, MS10 and MS21) at the conference. 

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Max Fasi, Mantas Mikatis, Mawussi Zounon, Sri Pranesh, Theo Mary at SIAM Conference on Parallel Processing for Scientific Computing, Seattle, Washington, February 12-15, 2020.

Conference Celebrating the 70th Birthday of Jack Dongarra

by Sven Hammarling, Nick Higham, and Françoise Tisseur

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Jack Dongarra

July 18, 2020 is the 70th birthday of Professor Jack Dongarra, who holds appointments at the University of Tennessee, Oak Ridge National Laboratory, and the University of Manchester.

Jack has made 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. His recent honours include election as a Foreign Member of the Royal Society and receipt of the
SIAM/ACM Prize in Computational Science and Engineering (2019)and the IEEE Computer Society Computer Pioneer Award (2020).

To celebrate Jack’s birthday we are organizing a conference New Directions in Numerical Linear Algebra and High Performance Computing: Celebrating the 70th Birthday of Jack Dongarra at The University of Manchester, July 17, 2020.  Registration is now open and we welcome submission of posters.

Numerical Algorithms for High-Performance Computational Science Issue of Phil Trans R Soc A

RS journalProfessors Jack Dongarra and Nick Higham, together with Dr Laura Grigori (Inria Paris), have edited the issue Numerical Algorithms for High-Performance Computational Science of the journal Philosophical Transaction of The Royal Society A. The issue is now available online.

The issue contains papers from a Discussion meeting of the same title organized at the Royal Society in April 2019.  A report on that meeting, along with photos from it, is available here.  The content of the issue, with links to the papers, is as follows.

Table of Contents

Numerical algorithms for high-performance computational science by Jack Dongarra, Laura Grigori and Nicholas J. Higham.

The future of computing beyond Moore’s Law by John Shalf.

Hierarchical algorithms on hierarchical architectures by D. E. Keyes , H. Ltaief and G. Turkiyyah.

Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations by Michael Hopkins, Mantas Mikaitis, Dave R. Lester and Steve Furber.

Preparing sparse solvers for exascale computing by Hartwig Anzt, Erik Boman, Rob Falgout et al.

On the cost of iterative computations by Erin Carson and Zdeněk Strakoš.

Rethinking arithmetic for deep neural networks by G. A. Constantinides.

Machine learning and big scientific data by Tony Hey , Keith Butler, Sam Jackson and Jeyarajan Thiyagalingam.

The physics of numerical analysis: a climate modelling case study by T. N. Palmer.

Exascale applications: skin in the game by Francis Alexander, Ann Almgren, John Bell et al.

Big telescope, big data: towards exascale with the Square Kilometre Array by A. M. M. Scaife.

Optimal memory-aware backpropagation of deep join networks by Olivier Beaumont, Julien Herrmann, Guillaume Pallez (Aupy) and Alena Shilova.

High-performance sampling of generic determinantal point processes by Jack Poulson.

A survey of algorithms for transforming molecular dynamics data into metadata for in situ analytics based on machine learning methods by Michela Taufer , Trilce Estrada and Travis Johnston.

The parallelism motifs of genomic data analysis by Katherine Yelick , Aydın Buluç, Muaaz Awan et al.

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