Publications

2019

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I. Mytilinis, D. Tsoumakos and N. Koziris. Maintaining Wavelet Synopses for Sliding-Window Aggregates, In 31st International Conference on Scientific and Statistical Database Management (SSDBM), 2019.
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G. Mylonas, D. Amaxilatis, L. Pocero, S. Tsampas, J. Gunneriusson, A Methodology for Saving Energy in Educational Buildings Using an IoT Infrastructure, In 10th ΙΕΕΕ International Conference on Information, Intelligence, Systems and Applications, 2019.
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M. Papadimitriou, J. Fumero, A. Stratikopoulos and C. Kotselidis, "Towards Prototyping and Acceleration of Java Programs onto Intel FPGAs," 2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM), San Diego, CA, USA, 2019, pp. 310-310.

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Juan Fumero, Michail Papadimitriou, Foivos S. Zakkak, Maria Xekalaki, James Clarkson, Christos Kotselidis. Dynamic Application Reconfiguration on Heterogeneous Hardware. In 15th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (VEE), 2019.

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Steffen Zeuch, Bonaventura Del Monte, Jeyhun Karimov, Clemens Lutz, Manuel Renz, Jonas Traub, Sebastian Breß, Tilmann Rabl, and Volker Markl. 2019. Analyzing efficient stream processing on modern hardware. Proc. VLDB Endow. 12, 5 (January 2019), 516-530. DOI: https://doi.org/10.14778/3303753.3303758

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Breß, S., Funke, H., Zeuch, S., Rabl, T. & Markl, V., (2019). An Overview of Hawk: A Hardware-Tailored Code Generator for the Heterogeneous Many Core Age. In: Meyer, H., Ritter, N., Thor, A., Nicklas, D., Heuer, A. & Klettke, M. (Hrsg.), BTW 2019

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Viktor Rosenfeld, Sebastian Breß, Steffen Zeuch, Tilmann Rabl, and Volker Markl. 2019. Performance Analysis and Automatic Tuning of Hash Aggregation on GPUs. In Proceedings of the 15th International Workshop on Data Management on New Hardware (DaMoN'19). ACM, New York, NY, USA, Article 8, 11 pages. DOI: https://doi.org/10.1145/3329785.3329922
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Philipp M. Grulich, Jonas Traub, Sebastian Breß, Asterios Katsifodimos, Volker Markl, and Tilmann Rabl. 2019. Generating Reproducible Out-of-Order Data Streams. In Proceedings of the 13th ACM International Conference on Distributed and Event-based Systems (DEBS '19). ACM, New York, NY, USA, 256-257. DOI: https://doi.org/10.1145/3328905.3332511

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Jonas Traub, Philipp Grulich, , Alejandro Rodriguez Cuellar, Sebastian Breß, Asterios Katsifodimos, Tilmann Rabl, and Volker Markl. 2019. Efficient Window Aggregation with General Stream Slicing. In EDBT. ACM.

2018

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Fotis Loukidis-Andreou, Ioannis Giannakopoulos, Katerina Doka, Nectarios Koziris. In IEEE 38th International Conference on Distributed Computing Systems (ICDCS), 2018.
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Constantinos Bitsakos, Ioannis Konstantinou, Nectarios Koziris. DERP: A Deep Reinforcement Learning Cloud System for Elastic Resource Provisioning, In IEEE International Conference on Cloud Computing Technology and Science (CloudCom), 2018.
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Clemens Lutz, Sebastian Breß, Tilmann Rabl, Steffen Zeuch, and Volker Markl. 2018. Efficient k-means on GPUs. In Proceedings of the 14th International Workshop on Data Management on New Hardware (DAMON '18). ACM, New York, NY, USA, Article 3, 3 pages. DOI: https://doi.org/10.1145/3211922.3211925

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Lutz, C., Breß, S., Rabl, T. et al. Datenbank Spektrum (2018) 18: 157.https://doi.org/10.1007/s13222-018-0293-x

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Sebastian Breβ, Bastian Köcher, Henning Funke, Steffen Zeuch, Tilmann Rabl, and Volker Markl. 2018. Generating custom code for efficient query execution on heterogeneous processors. The VLDB Journal 27, 6 (December 2018), 797-822. DOI: https://doi.org/10.1007/s00778-018-0512-y

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Behrens, Tobias; Rosenfeld, Viktor; Traub, Jonas; Breß, Sebastian; Markl, Volker: Efficient SIMD Vectorization for Hashing in OpenCL. In: Proceedings of the 21th International Conference on Extending Database Technology, EDBT 2018, Vienna, Austria, March 26-29, 2018. pp. 489–492, 2018
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James Clarkson, Juan Fumero, Michail Papadimitriou, Foivos S. Zakkak, Maria Xekalaki, Christos Kotselidis, and Mikel Luján. Exploiting High-Performance Heterogeneous Hardware for Java Programs using Graal. In 15th International Conference on Managed Languages and Runtimes (ManLang), 2018.

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Juan Fumero, Christos Kotselidis. Using Compiler Snippets to Exploit Parallelism on Heterogeneous Hardware: A Java Reduction Case Study. In the 10th International Workshop on Virtual Machines and Intermediate Languages (VMIL '18), November 2018.
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Maria Xekalaki, Juan Fumero, Christos Kotselidis. Challenges and proposals for enabling dynamic heterogeneous execution of Big Data frameworks. In 1st International Workshop on Next Generation Clouds for Extreme Data Analytics (Xtreme-Cloud), December 2018.
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James Clarkson, Juan Fumero, Michail Papadimitriou, Maria Xekalaki, Christos Kotselidis. Towards Practical Heterogeneous Virtual Machines. In MoreVMs 2018 Workshop on Modern Language Runtimes, Ecosystems, and VMs, April 2018.
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I. Mytilinis, C. Bitsakos, K. Doka, I. Konstantinou and N. Koziris, "The Vision of a HeterogeneRous Scheduler," 2018 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Nicosia, 2018, pp. 302-307. doi: 10.1109/CloudCom2018.2018.00065
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C. Bitsakos, I. Konstantinou and N. Koziris, "DERP: A Deep Reinforcement Learning Cloud System for Elastic Resource Provisioning," 2018 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), Nicosia, 2018, pp. 21-29.

Presentations

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Juan Fumero, TornadoVM: A Java a Virtual Machine for Exploiting High-Performance Heterogeneous Hardware, AORTA @ ECOOP, 2019.
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Christos Kotselidis, Practical hardware acceleration of managed languages, Software in a Heterogeneous World Workshop, HiPEAC CS, 2019.
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Juan Fumero, Managed runtimes in heterogeneous JVMs, Heterogeneity Alliance Workshop, HiPEAC, 2019
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Juan Fumero, E2Data: Current and Future Approaches, Heterogeneity Alliance Workshop, HiPEAC, 2019
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Michalis Papadimitriou, Exploiting Reconfigurable Hardware from Managed Languages, AccelCloud Workshop, HiPEAC, 2019
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Juan Fumero, TornadoVM: A Java a Virtual Machine for Exploiting High-Performance Heterogeneous Hardware, JVM Language Summit, 2019.
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Christos Kotselidis, E2Data: European Extreme Performing Big Data Stacks, Heterogeneity Alliance Workshop, HiPEAC, 2018.
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Ioannis Mitilinis, The Vision of a Heterogeneous Aware Scheduler, In Hipeac CSW, 2018.
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Katerina Doka, Enabling Heterogeniety in Big Data, Elec. Tec. Exhibition, Athens, Greece, 2018.
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Ioannis Komnios, E2Data: European Extreme Performing Big Data Stacks, BDV PPP, Brussels, Belgium, 2018.
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Juan Fumero, On the road for Heterogeneous VMs for Distributed Systems, HIPEAC CSW, Heraclion, Greece, 2018.

Code

This project has received funding from the European Union's Horizon H2020 research and innovation programme under grant agreement No 780245.

E2Data is part of the Heterogeneity Alliance