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pro vyhledávání: '"Lucarelli, Giorgio"'
Modern platforms are using accelerators in conjunction with standard processing units in order to reduce the running time of specific operations, such as matrix operations, and improve their performance. Scheduling on such hybrid platforms is a chall
Externí odkaz:
http://arxiv.org/abs/1912.03088
Autor:
Beaumont, Olivier, Canon, Louis-claude, Eyraud-Dubois, Lionel, Lucarelli, Giorgio, Marchal, Loris, Mommessin, Clément, Simon, Bertrand, Trystram, Denis
Publikováno v:
ACM Computing Survey, Vol. 53, No. 3, 2020
The evolution in the design of modern parallel platforms leads to revisit the scheduling jobs on distributed heterogeneous resources. The goal of this survey is to present the main existing algorithms, to classify them based on their underlying princ
Externí odkaz:
http://arxiv.org/abs/1909.11365
Akademický článek
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Autor:
Lucarelli, Giorgio, Moseley, Benjamin, Thang, Nguyen Kim, Srivastav, Abhinav, Trystram, Denis
In this paper, we consider the online problem of scheduling independent jobs \emph{non-preemptively} so as to minimize the weighted flow-time on a set of unrelated machines. There has been a considerable amount of work on this problem in the preempti
Externí odkaz:
http://arxiv.org/abs/1804.08317
Autor:
Lucarelli, Giorgio, Moseley, Benjamin, Thang, Nguyen Kim, Srivastav, Abhinav, Trystram, Denis
When a computer system schedules jobs there is typically a significant cost associated with preempting a job during execution. This cost can be from the expensive task of saving the memory's state and loading data into and out of memory. It is desira
Externí odkaz:
http://arxiv.org/abs/1802.10309
We study the problem of executing an application represented by a precedence task graph on a parallel machine composed of standard computing cores and accelerators. Contrary to most existing approaches, we distinguish the allocation and the schedulin
Externí odkaz:
http://arxiv.org/abs/1711.06433
Publikováno v:
Algorithmica 81, 3391-3421 (2019)
We study online scheduling problems on a single processor that can be viewed as extensions of the well-studied problem of minimizing total weighted flow time. In particular, we provide a framework of analysis that is derived by duality properties, do
Externí odkaz:
http://arxiv.org/abs/1502.03946
We revisit the non-preemptive speed-scaling problem, in which a set of jobs have to be executed on a single or a set of parallel speed-scalable processor(s) between their release dates and deadlines so that the energy consumption to be minimized. We
Externí odkaz:
http://arxiv.org/abs/1407.7654
Autor:
Bampis, Evripidis, Kononov, Alexander, Letsios, Dimitrios, Lucarelli, Giorgio, Sviridenko, Maxim
We propose a unifying framework based on configuration linear programs and randomized rounding, for different energy optimization problems in the dynamic speed-scaling setting. We apply our framework to various scheduling and routing problems in hete
Externí odkaz:
http://arxiv.org/abs/1403.4991
Autor:
Bampis, Evripidis, Chau, Vincent, Letsios, Dimitrios, Lucarelli, Giorgio, Milis, Ioannis, Zois, Georgios
MapReduce is emerged as a prominent programming model for data-intensive computation. In this work, we study power-aware MapReduce scheduling in the speed scaling setting first introduced by Yao et al. [FOCS 1995]. We focus on the minimization of the
Externí odkaz:
http://arxiv.org/abs/1402.2810