HPDC Achievement Award 2021
Rosa Badia, for her innovations in parallel task-based programming models, workflow applications and systems, and leadership in the high performance computing research community.
Title: Superscalar programming models: a perspective from Barcelona.
Abstract: The importance of the programming model in the development of applications has been increasingly more important with the evolution of computing architectures and infrastructures. Aspects such as the number of cores and heterogeneity in the computing nodes, the increase in scale, and new highly distributed environments (the so-called computing continuum) make it even more critical. Superscalar programming models have been proposed as an alternative for the development of parallel and distributed applications. They are a family of task-based programming models that aim at offering a sequential programming interface while enabling a parallel execution in distributed programming environments. Generic aspects supported by the model are: task dependency analysis, parallelism exploitation, data renaming, and data management. Over the years, BSC has developed multiple instances of this family, each of them with some specific aspects depending on the needs and possibilities of the existing computing infrastructure.
The talk will present a historical perspective of the superscalar programming models for distributed computing and the challenges that we foresee for the near future.
Bio: Rosa M. Badia holds a PhD on Computer Science (1994) from the Technical University of Catalonia (UPC). She is the manager of the Workflows and Distributed Computing research group at the Barcelona Supercomputing Center (BSC). She is considered one of the key researchers in Parallel programming models for multicore and distributed computing due to her contribution to task-based programming models during the last 15 years. The research group focuses on PyCOMPSs/COMPSs, a parallel task-based programming distributed computing, and its application to the development of large heterogeneous workflows that combine HPC, Big Data, and Machine Learning. The group is also doing research around the dislib, a parallel machine learning library parallelized with PyCOMPSs. Dr Badia has published near 200 papers in international conferences and journals on the topics of her research. She has been very active in projects funded by the European Commission in contracts with industry. She has been actively contributing to the BDEC international initiative and is a member of HiPEAC Network of Excellence. She received the Euro-Par Achievement Award 2019 for her contributions to parallel processing and the DonaTIC award, category Academia/Researcher in 2019. She is the IP of the EuroHPC project eFlows4HPC.
Past Winners
- 2019: Geoffrey Fox, Indiana University, USA
- 2018: Satoshi Matsuoka, Riken CCS, Japan
- 2017: David Abramson, University of Queensland, Australia
- 2016: Jack Dongarra, UTK and Oak Ridge
- 2015: Ewa Deelman, Information Sciences Institute - USC, USA
- 2014: Rich Wolski, UC Santa Barbara, USA
- 2013: Miron Livny, University of Wisconsin-Madison, USA
- 2012: Ian Foster, University of Chicago and Argonne National Laboratory, USA