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Embedded Systems ArchitectureProf. Dr. Ben Juurlink

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Prof. Dr. Ben Juurlink



Prof. Dr. Ben Juurlink received the M.Sc. degree from Utrecht University, Utrecht, The Netherlands, and the Ph.D. degree from Leiden University, Leiden, The Netherlands, in 1992 and 1997, respectively.

In 1997-1998 he worked as a post-doctoral researcher at the Heinz Nixdorf Institute in Paderborn, Germany, and from 1998 to 2009 he was a faculty member (first assistant professor, then associate professor) of the Computer Engineering Laboratory of Delft University of Technology, Delft, The Netherlands. Currently, he is professor for Embedded Systems Architectures in the Faculty of Electrical Engineering and Computer Science of Berlin University of Technology, Berlin, Germany. He is also co-founder of Spin Digital GmbH.

Dr. Juurlink’s research interests include multi- and many-core processors, reconfigurable computing, and the art of mapping applications effectively and efficiently to computer architectures. He has (co-)authored more than 130 articles in international conferences and journals, and received best paper awards at the IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS) in 2002, and at the third IEEE International Conference on Consumer Electronics – Berlin (ICCE-Berlin). He has also received a Technology Transfer Award from the HiPEAC Network of Excellence for transferring some of the video coding technology that has been developed in his group to a Greece-based SME.

Dr. Juurlink is a senior member of the ACM and a senior member of the IEEE. He has been the Principal Investigator of several national research projects, Work Package leader in several European projects, and Coordinator of the EU projects LPGPU, Film265, and LPGPU2. He has served on many program committees, is an editor of the Elsevier journal on Microprocessors and Microsystems: Embedded Hardware Design, and was the general co-chair of the HiPEAC conference in 2013.

Professional Experience

Professor for Embedded Systems Architectures

Berlin University of Technology, Germany

01/2010 -

Associate professor

Delft University of Technology, Netherlands

02/2007 - 12/2009

Director of education for master's programs in Computer Engineering and Embedded Systems

Delft University of Technology, Netherlands

09/2006 - 12/2009

Assistant professor

Delft University of Technology, Netherlands

09/1999 - 01/2007

Postdoctoral fellow

Delft University of Technology, Netherlands

09/1998 - 08/1999

Postdoctoral fellow

Paderborn University, Germany

01/1997 - 07/1998

Postdoctoral fellow

Leiden University, Netherlands

09/1996 - 12/1996

Visiting researcher

Max-Planck-Institut für Informatik, Saarbrücken, Germany


Research assistant

Leiden University, Netherlands

09/1992 - 08/1996

Teaching assistant

Utrecht University, Netherlands

09/1990 - 01/1992


PhD degree in computer science

Leiden University, Netherlands. Thesis title: Computational models for parallel computers


MSc degree in computer science

Utrecht University, Netherlands



ALONA: Automatic Loop Nest Approximation with Reconstruction and Space Pruning
Citation key 10.1007/978-3-030-85665-6_1
Author Daniel Maier and Biagio Cosenza and Ben Juurlink
Title of Book Euro-Par 2021: Parallel Processing
Pages 3–18
Year 2021
ISBN 978-3-030-85665-6
Address Cham
Editor Leonel Sousa and Nuno Roma and Pedro Tomás
Publisher Springer International Publishing
Abstract Approximate computing comprises a large variety of techniques that trade the accuracy of an application's output for other metrics such as computing time or energy cost. Many existing approximation techniques focus on loops such as loop perforation, which skips iterations for faster, approximated computation. This paper introduces ALONA, a novel approach for automatic loop nest approximation based on polyhedral compilation. ALONA's compilation framework applies a sequence of loop approximation transformations, generalizes state-of-the-art perforation techniques, and introduces new multi-dimensional approximation schemes. The framework includes a reconstruction technique that significantly improves the accuracy of the approximations and a transformation space pruning method based on Barvinok's counting that removes inaccurate approximations. Evaluated on a collection of more than twenty applications from PolyBench/C, ALONA discovers new approximations that are better than state-of-the-art techniques in both approximation accuracy and performance.
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Older Publications

Further Publications of Prof. Juurlink  are here available.


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