Author of the publication

Energy Characterization of Garbage Collectors for Dynamic Applications on Embedded Systems.

, , , , , and . PATMOS, volume 3728 of Lecture Notes in Computer Science, page 69-78. Springer, (2005)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

No persons found for author name Olcoz, Katzalin
add a person with the name Olcoz, Katzalin
 

Other publications of authors with the same name

Unified data path allocation and BIST intrusion., , and . Integr., 28 (1): 55-99 (1999)User-profile-based analytics for detecting cloud security breaches., , , , and . IEEE BigData, page 4529-4535. IEEE Computer Society, (2017)A Unified Cloud-Enabled Discrete Event Parallel and Distributed Simulation Architecture., , , , and . CoRR, (2023)MAMUT: Multi-Agent Reinforcement Learning for Efficient Real-Time Multi-User Video Transcoding., , , , , and . DATE, page 558-563. IEEE, (2019)Revisiting Conventional Task Schedulers to Exploit Asymmetry in ARM big.LITTLE Architectures for Dense Linear Algebra., , , and . CoRR, (2015)Energy Characterization of Garbage Collectors for Dynamic Applications on Embedded Systems., , , , , and . PATMOS, volume 3728 of Lecture Notes in Computer Science, page 69-78. Springer, (2005)Data path structures and heuristics for testable allocation in high level synthesis., , , , and . Microprocess. Microprogramming, 39 (2-5): 263-266 (1993)Level-Spread: A New Job Allocation Policy for Dragonfly Networks., , , , , and . IPDPS, page 1123-1132. IEEE Computer Society, (2018)Performance Evaluation of Barrier Techniques for Distributed Tracing Garbage Collectors., , , and . PARCO, volume 33 of John von Neumann Institute for Computing Series, page 549-556. Central Institute for Applied Mathematics, Jülich, Germany, (2005)Distributed training and inference of deep learning solar energy forecasting models., , , , and . PDP, page 173-176. IEEE, (2023)