Andy Pimentel chairs the Parallel Computing Systems (PCS) group within the Systems and Networking Lab at the Informatics Institute of the University of Amsterdam. The PCS group performs research on the design, programming and run-time management of multi-core and multi-processor computer systems. The modeling, analysis and optimization of the extra-functional aspects of these systems, such as performance, power/energy consumption and system dependability but also the degree of productivity to design and program these systems, play a pivotal role in our work.
PhD in Computer Science, 1998
University of Amsterdam
MSc in Computer Science, 1993
University of Amsterdam
The paper ‘The Choice of AI Matters: Alternative Machine Learning Approaches for CPS Anomalies’ by Odyurt, Sapra and Pimentel was accepted for IEA/AIE 2021.
The paper ‘Power Passports for Fault Tolerance: Anomaly Detection in Industrial CPS Using Electrical EFB’ by Odyurt, Roeder, Pimentel, Alonso, and de Laat was accepted for IEEE ICPS 2021 and received the Best Student Paper Award.
Dolly Sapra received the Best Paper Award at IEA/AIE 2020 for her paper entitled ‘Constrained Evolutionary Piecemeal Training to Design Efficient Neural Networks’
The chapter entitled ‘Methodologies for design space exploration’ has been accepted for the Handbook of Computer Architecture (Springer)
The paper ‘A Case for Security-aware Design-Space Exploration of Embedded Systems’ by Pimentel was accepted for the Journal of Low Power Electronics and Applications (special issue on Design Space Exploration and Resource Management of Multi/Many-Core Systems).
EU H2020 ITN/ETN project on approximate computing for power and energy optimisation granted!
The paper ‘Deep Learning Model Reuse and Composition in Knowledge Centric Networking’ by Sapra and Pimentel was accepted for ICCCN 2020.
The paper ‘CITTA: Cache Interference-aware Task Partitioning for Real-time Multi-core Systems’ by Xiao and Pimentel was accepted for ACM LCTES 2020.
The paper ‘An Evolutionary Optimization Algorithm for Gradually Saturating Objective Functions’ by Sapra and Pimentel was accepted for ACM GECCO 2020.
The paper ‘Constrained Evolutionary Piecemeal Training to Design Efficient Neural Networks’, by Sapra and Pimentel was accepted for IEA/AIE 2020.
The paper ‘Schedulability Analysis of Global Scheduling for Multicore Systems with Shared Caches’ by Xiao, Altmeyer and Pimentel was accepted for IEEE Transactions on Computers, 2020.