Tomasz Ciesielczyk
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Tomasz Ciesielczyk has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Alberto Cabrera
Universidad de La Laguna, ULL
1 shared publication - Ariel Oleksiak
Poznan Supercomputing and Networking Center, Poland
1 shared publication - Francisco Almeida
Universidad de La Laguna
1 shared publication - Grzegorz Waligóra
Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965 Poznan, Poland
1 shared publication - Vicente Blanco
Universidad de La Laguna
1 shared publication - Wojciech Piatek
Poznań Supercomputing and Networking Center
1 shared publication
Latest Publications
- Open Access
- 20 May 2020
- Published by Springer Nature in Journal of Scheduling
- Vol. 24 (5) , 489-505
An approach to reduce energy consumption and performance losses on heterogeneous servers using power capping
Rapid growth of demand for remote computational power, along with high energy costs and infrastructure limits, has led to treating power usage as a primary constraint in data centers. Especially, recent challenges related to development of exascale systems or autonomous edge systems require tools that will limit power usage and energy consumption. This paper presents a power capping method that allows operators to quickly adjust the power usage to external conditions and, at the same time, to reduce energy consumption and negative impact on performance of applications. We propose an optimization model and both heuristic and exact methods to solve this problem. We present an evaluation of power capping approaches supported by results of application benchmarks and experiments performed on new heterogeneous servers.
- 20 May 2020
- Published by Springer Nature in Journal of Scheduling
- Vol. 24 (5) , 489-505
Open AccessAn approach to reduce energy consumption and performance losses on heterogeneous servers using power capping
Rapid growth of demand for remote computational power, along with high energy costs and infrastructure limits, has led to treating power usage as a primary constraint in data centers. Especially, recent challenges related to development of exascale systems or autonomous edge systems require tools that will limit power usage and energy consumption. This paper presents a power capping method that allows operators to quickly adjust the power usage to external conditions and, at the same time, to reduce energy consumption and negative impact on performance of applications. We propose an optimization model and both heuristic and exact methods to solve this problem. We present an evaluation of power capping approaches supported by results of application benchmarks and experiments performed on new heterogeneous servers.