Thursday, April 25, 2024 | 08:30 am (CET) | Room: S.2.37 | Alpen-Adria Universität Klagenfurt

Ana Lucia Varbanescu | Assoc. Prof. Dr. ir. at the University of Twente and University of Amsterdam

Abstract: “Computation” has become a massive part of our daily lives: in science, a lot of experiments and analysis rely on massive computation, in AI we use vast resources to train and use massive models, and in engineering we use complex simulations and digital twins to increase efficiency and productivity. Under the assumption that computation is cheap, and time-to-result is the only relevant metric, we often use significant computational resources at low efficiency. In this talk, I argue this approach is an unacceptable waste of computing resources, and demonstrate we can do better! By means of a couple of case-studies, I will show how performance engineering can be used for zero-waste computing, proving how efficiency and time-to-result can be happily married. I will further propose a co-design methodology that leverages such performance engineering methods to enable the selection of algorithms _and_ their effective deployment on suitable infrastructure. The approach relies on design-space exploration, driven by efficient search methods and compositional performance models. I will conclude by reflecting on the next steps and open questions that need answers to make this co-design approach feasible and applicable for more applications and systems.

Bio: Ana Lucia Varbanescu holds a BSc and MSc degree from POLITEHNICA University in Bucharest, Romania. She obtained her PhD from TU Delft, The Netherlands, and continued to work as a Postdoc researcher in The Netherlands, at TU Delft and VU University in Amsterdam. She is a MacGillavry fellow at University of Amsterdam, where she was tenured in 2018 as Associate Professor. Since 2022, she is Professor at University of Twente, The Netherlands. She has been a visiting researcher at IBM TJ Watson (2006, 2007), Barcelona Supercomputing Center (2007), NVIDIA (2009), and Imperial College of London (2013).  She has received several national grants (including a personal Veni grant) and she is a co-PI for the Graph-Massivizer EU project. Ana’s research stems from HPC, and investigates the use of heterogeneous systems for high-performance applications, with a special focus on performance and energy efficiency modeling for both scientific and data-intensive applications. Her latest research focuses on zero-waste computing and model-based systems co-design.

 

Friday, March 15, 2024 | 10:00 am (CET) | Room: S.2.69 | Universität Klagenfurt Matteo Zavatteri | Assistant Professor  in computer science at the Department of Mathematics of University of Padua, Italy Abstract: A recent direction in Business Process Management studied methodologies to control the execution of Business Processes under several sources of uncertainty in order to always get to the end by satisfying all constraints. Current approaches encode business processes into temporal constraint networks or timed game automata in order to exploit their related strategy synthesis algorithms. However, the proposed encodings can only synthesize single-strategies and fail to handle loops. To overcome these limits I will discuss a recent approach based on supervisory control. The approach considers structured business processes with resources, parallel and mutually exclusive branches, loops, and uncertainty. I will discuss an encoding into finite state automata and prove that their concurrent behavior models exactly all possible executions of the process. After that, I will introduce tentative commitment constraints as a new class of constraints restricting the executions of a process. Finally, I will discuss a tree decomposition of the process that plays a central role in modular supervisory control. Bio: Matteo Zavatteri is assistant professor in computer science at the Department of Mathematics of University of Padua, Italy. He received a master degree in engineering and computer science and a Ph.D. in computer science from University of Verona (ITALY). His research interests are in the fields of formal methods, discrete event systems, supervisory control, temporal reasoning, artificial intelligence, and business process management. Currently he works in the iNEST (Interconnected Nord-Est Innovation Ecosystem) project, which is a project supported with 110M€ by the National Recovery and Resilience Plan, funded by the European Union in the NextGenerationEU plan. In such a project he develops neuro-symbolic approaches for digital twins.