Main research interests
My research interests focus on:
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High Performance Computing & Parallel Optimization
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GPU Computing/Multi-core programming
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Grid/Cluster and P2P - Computing
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Parallel algorithms for Combinatorial Optimization
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Big Graphs
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Framworks and HPC Platforms for Big Graphs
Research Projects
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Leader of the project (HPC-Optim) High Performance Computing for Combinatorial Optimization, CERIST, March 2012-December 2016.
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Member (WP Leader) of the project (BiGraPS) Big Graph Data Processing on HPC platforms: Application to improve Mobility in Smart Cities, January 2017-December 2019.
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Member of the coordinating team of ERANETMED, December 2013 - December 2017.
Collaboration
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MCSI, ESI, Algiers, Algeria
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Hybrid GPU/CPU multi-core B&B algorithms
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Parallel satellite image processing
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DOLPHIN Team, INRIA/LIFL/University Lille1, Lille, France.
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Grid-based Parallel Branch and Bound Algorithms
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GPU/multi-core B&B algorithms
International Responsabilities
Reviewer in International Journals
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IEEE TPDS - IEEE’s Transactions on Parallel and Distributed Systems
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JPDC - The Journal of Parallel and Distributed Computing
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CCPE - Concurrency and Computation: Practice and Experience
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PPL - Parallel Processing Letters
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SOCO - Soft Computing Journal
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CAIE - Computers & Industrial Engineering
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IJICT - International Journal of Information and Communication Technology
Conference/Event Organization
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Member of the steering committee of IEEE ICT-DM'2015 ICT-DM'2015, France, December 2015.
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Organizer of HPC days (JCIA'2014) Algiers, October 2014.
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Member of the organizing committee of ICT-DM'2014, Algeria, March 2014.
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Chair of the Scientific Computing training session and member of organizing committee of CARI’2012 (Algiers 2012)
Member of Technical Program Committees
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IEEE Int. Conf. on ICTs for Disaster Management, ICT-DM'2017, Germany, December 2017.
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Workshop on Parallel Optimization using/for Multi and Manycore HPC (POMCO'2016), Austria, 2016
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13th Int. Conf. on Distributed Computing and Artificial Intelligence (DCAI'16), Spain, 2016
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IEEE Int. Conf. on Vehicular Traffic Management (IEEE VTM’2016)
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Multi/Manycore computing for parallel Metaheuristics (McM’2015), Morocco, 2015
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International Workshop on Parallel Optimization using High Performance Computing, POMM'2014, Bologna, Italy, 2014
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International Conference on Metaheuristics and Nature Inspired Computing, META'2014, Marrakech, Morocco, 2014
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International Conference on Advanced Networking, Distributed Systems and Applications INDS'2014, Bejaia, Algeria, 2014
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IEEE International Conference on Vehicular Traffic Management IEEE VTM'2014, Seoul, Korea, 2014
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IEEE International Conference on Information and Communication Technologies for Disaster Management IEEE ICT-
DM'2014, Algiers, Algeria, 2014
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IEEE International Conference on Vehicular Traffic Management IEEE VTM'2012, Dublin, Ireland, 2012
Thesis summary
Solving to optimality large instances of combinatorial optimization
problems using Branch and Bound (B&B) algorithms requires a huge
amount of computing resources. Nowadays, such power is provided by large
scale environments such as computational grids. However, grids induce
new challenges: scalability, heterogeneity, and fault tolerance. Most of
existing grid-based B&Bs are developed using the Master-Worker
paradigm, their scalability is therefore limited. Moreover fault
tolerance is rarely addressed in these works. In this thesis, we propose
three main contributions to deal with these issues: P2P-B&B,
H-B&B, and FTH-B&B. P2PB&B is a MW-based B&B framework
which deals with scalability by reducing the task request frequency and
enabling direct communication between workers. H-B&B also deals with
scalability. Unlike the state-of-the-art approaches, H-B&B is fully
dynamic and adaptive, meaning it takes into account the dynamic
acquisition of new computing resources. FTH-B&B is based on new
fault tolerant mechanisms enabling efficient building of the hierarchy
and maintaining its balancing, and minimizing of work redundancy when
storing and recovering tasks. The proposed approaches have been
implemented using ProActive grid-middleware and applied to the Flow-Shop
scheduling Problem (FSP). The large scale experiments performed on
Grid'5000 proved the efficiency of the proposed approaches.
Ph.D. dissertation
Scalable and Fault Tolerant Hierarchical B&B Algorithms for Computational Grids. [Slides] [PDF]