STRENGHTENING HPE LEADERSHIP IN HIGH PERFORMANCE COMPUTING AND DATA ANALYTICS

The HPE HPC/AI EMEA Research Lab (ERL) performs research and development in strategic areas that strengthen HPE leadership in high-performance computing and data analytics, and which deepen HPE’s involvement in the scientific and technical communities of EMEA.

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The ERL is focused on collaborative R&D and codesign efforts, including:

- Software codesign

- Experimental hardware codesign

- In-house innovation projects

- EU-funded R&D projects

- Collaborations with partners/customers and Centres of Excellence

- Internships and student hosting

CURRENT FOCUSES

The HPE HPC/AI EMEA Research Lab is currently focused on workflow and component optimization for HPC and analytics frameworks, machine learning and the role of new technologies such as non-volatile memory.  The HPE HPC/AI EMEA Research Lab can bring deep expertise in the more traditional HPC ecosystem along with expertise in machine learning, asynchronous tasking, data analytics and mathematical optimization.

CENTRES OF EXCELLENCE (COE)

ERL staff provide the expertise within the Centres of Excellence for ARCHER in Edinburgh and at KAUST in Saudi Arabia. The CoEs are a forum for bespoke deep technical engagements where, for example, advanced software is designed specifically for the needs of the customer’s application base.

CURRENT PROJECTS

Plan4Res

The general objective of the project is to fill the gaps between the increasing complexity of the future energy system planning and operational problems, and the currently available system analysis tools. The project will develop an end-to-end planning tool which will help to successfully increase the share of renewable energy into the European Energy System without compromising on system reliability. The targeted platform will account for the Pan-European interconnected electricity system, potential synergies with other energy systems, emerging technologies and flexibility resources, providing a fully integrated modeling environment.

 

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EXPERTISE

EXPERTISE is a European Training Network (ETN) that will contribute to train the next generation of mechanical and computer science engineers with a common basic knowledge on the challenges, the paradigms, the technologies and the methodologies in the field of nonlinear structural dynamics of turbomachinery and High Performance Computing.

 

The ultimate research objective of EXPERTISE is to develop advanced tools for the dynamics analysis of large-scale models of turbine components to pave the way towards the virtual testing of the entire machine.

 

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MAESTRO

Maestro will build a data-aware and memory-aware middleware framework that addresses ubiquitous problems of data movement in complex memory hierarchies and at many levels of the HPC software stack. Moving data through memory was not always the bottleneck. Software rightfully insulates users from hardware details

 

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EPIGRAM-HS

The overall objective of EPiGRAM-HS is the development of a new validated programming environment for large-scale heterogeneous computing systems, including accelerators, reconfigurable hardware and low-power microprocessor together with non-volatile and high-bandwidth memories, for enabling applications to run on large-scale heterogeneous systems at maximum performance.

 

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SODALITE

SODALITE will provide application developers and infrastructure operators with tools that (a) abstract their application and infrastructure requirements to (b) enable simpler and faster development, deployment, operation, and execution of heterogeneous applications reflecting diverse circumstances over (c) heterogeneous, software-defined, high-performance, cloud infrastructures, with a particular focus on performance, quality, manageability, and reliability.

 

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ERL STAFF AND RESEARCH INTEREST

Tim Dykes, Research Engineer

Tim joined ERL as a Research Engineer in 2018, where he currently leads HPE efforts in EU projects such as EPiGRAM-HS and EXPERTISE. He holds a Ph.D. from the University of Portsmouth, U.K., focusing on high performance scientific visualisation in Astronomy. His research interests include heterogeneous high-performance architectures, performance portability, complex memory hierarchies, software and compiler optimisation, and scientific visualisation.

 

Aniello Esposito, Senior Research Engineer

Aniello Esposito  is responsible for the centre of excellence collaboration with KAUST (Saudi Arabia) among other research activities in the area of supercomputing. He is also involved in pre-sales as an expert application analyst for European procurements as well as site acceptances and he is part of the algorithms track technical committee of the Supercomputing conference. Before joining the research lab, Aniello worked as an application analyst, focusing on the optimization of large-scale scientific codes and general user support as well as trainings on Cray systems which took place on-site at HLRS, DWD, HLRN, and KAUST. Aniello studied physics at the Swiss Federal Institute of Technology in Zurich (ETHZ) with a focus on theory and computational methods and earned a Ph.D. from ETHZ in applied physics. After a postdoc he joined Cray in January 2012. His main interests lie in the implementation and optimization of large-scale scientific codes in the area of traditional high-performance computing as well as machine learning.

 

Clément Foyer, Early Stage Researcher - Ph.D. candidate

Clément Foyer is a Ph.D. candidate at the University of Bristol who joined HPE HPC&AI EMEA Research Lab in early 2018 as an early stage researcher. He earned a B.Sc. from the Université de Poitiers and a M.Sc. in computer science from ENSEIRB-MATMECA (École Nationale Supérieure d’Électronique, Informatique, Télécommunications, Mathématique et Mécanique de Bordeaux), with a specialization in high-performance computing. He then worked at Inria Bordeaux – Sud-Ouest as a research engineer, where he specialized in communication library and data locality optimization. Clément contributed to the Open MPI project and to the netloc companion tool for hwloc. His focus is data locality optimization in the context of heterogeneous memory systems. The Ph.D. is granted as part of the EXPERTISE European training network.

 

Christopher Haine, Research Engineer

Christopher Haine joined ERL in October 2018 as a research engineer, working in particular on the Maestro EU project He earned a bachelor's degree in computer science at the Université de Reims Champagne-Ardenne, and a master's degree at the Université de Versailles, specializing in high-performance computing and simulation. Christopher earned a Ph.D. from the Université de Bordeaux, focused on loop kernel optimization by data layout restructuring. Christopher's main interests are data movement in complex memory hierarchies and optimization of scientific applications.

 

Utz-Uwe Haus, Master Research Engineer

Utz-Uwe Haus, senior researcher at ERL, studied mathematics and computer science at the Technical University of Berlin (TU Berlin). After obtaining a doctorate in mathematics at the University of Magdeburg he worked on nonstandard applications of mathematical optimization in chemical engineering, material science, and systems biology. He led a junior research group at the Magdeburg Center for Systems Biology and was principal investigator on various EU FP7 ITN projects. After five years as senior researcher at the Department of Mathematics at ETH Zürich, he co-founded CERL, and is now technical leader of ERL. Research interests focus on parallel programming and data transfer-aware scheduling problems, as well as data analytics and novel compute architectures, and their relation to Mathematical Optimization and Operations Research.

 

Alfio Lazzaro, Research Engineer

Alfio Lazzaro joined ERL in October 2018 as a research engineer. He earned his Ph.D. in experimental particle physics at the University of Milan in 2007. In 2010 he joined CERN openlab with a COFUND-CERN and Marie Curie fellowship. From 2012 to 2014 he was an application analyst at Cray, based at the Swiss National Supercomputing Centre. From 2015 to 2018, he was a postdoctoral research associate at ETH Zurich and University of Zurich, working on the CP2K team under the Swiss PASC project. His main interests are optimization and parallelization of scientific applications.

 

Nina Mujkanovic, Software Engineer

Nina Mujkanovic joined CERL in 2017. She performs system administration duties and contributes to various research projects as a software engineer. Prior to joining Cray, she was part of the HPC system administration team at the University of Bern in Switzerland, where she also earned an M.Sc. in computer science. During her studies, she specialized in advanced information processing, with a special focus on machine learning. Her thesis focused on creating a deep neural network for the detection of pathologies in the retina. Nina’s interests include deep learning, high-performance computing, and open source.

 

Harvey Richardson, Senior Research Engineer

Harvey Richardson began his career with research roles after being awarded a Ph.D. in physics. As a researcher, he gained an interest in parallel computing through use and management of AMD DAP and Meiko systems. In 1992 Harvey joined Thinking Machines Corporation providing on-site support of the national Connection Machine CM-200 service at EPCC in Edinburgh. Harvey was responsible for user training, hardware, software, and application support. In 1998 Harvey joined the HPC benchmarking group of Sun Microsystems where he ran customer benchmarks to determine suitability of product and performance for customers’ applications. Harvey joined Cray in 2010 to work on research projects, both directly with customers and in larger research collaborations such as the EU CRESTA, EPIGRAM and EPIGRAM-HS projects looking at technologies that can help take real applications to exascale. Harvey has developed and taught many training courses and workshops. He has also developed various profiling and benchmarking tools. Harvey has particular interests in computer architecture and performance, programming models, and language standards.

 

Karthee Sivalingam, Research Engineer

Karthee Sivalingam is a research engineer at HPE HPC/AI EMEA Research Lab. He is part of the Cray Centre of Excellence at ARCHER, which supports scientists and engineers by providing deep technical support of reported issues, Research Software Engineering and facilitating broad collaboration with service providers and customers. He currently leads HPE's efforts for the SODALITE project that focuses on automating optimization of HPC and AI application deployments across diverse targets like supercomputers, cloud. He has more than 5 years' experience in Commercial Software Development (IT) and 10 years in HPC research and development with focus on convergence of HPC in Cloud, AI and Data Analytics.  Few things that keep him awake are a weak backhand (Tennis), fast bowling (Cricket) and his bamboo garden.

 

Irene Ferrario, Project Manager

Irene Ferrario joined ERL in 2018 to support the coordination and project management of ERL’s R&D projects. Irene has an expertise in project management, communication and legal and financial frameworks of projectized organizations. Before joining ERL, Irene worked in different advisory roles in EU Affairs in the UK and in Italy. Irene holds a PMP Qualification from the Project Management Institute and an M.A. in public policy. In her professional path, she has developed a keen interest in the communication and impact of new technologies on society.

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