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On the Throughput Optimization in Large-Scale Batch-Processing Systems

Kar, Sounak ; Rehrmann, Robin ; Mukhopadhyay, Arpan ; Alt, Bastian ; Ciucu, Florin ; Koeppl, Heinz ; Binnig, Carsten ; Rizk, Amr (2020)
On the Throughput Optimization in Large-Scale Batch-Processing Systems.
38th International Symposium on Computer Performance, Modeling, Measurements and Evaluation (PERF 2020). virtual Conference (02.-06.11.2020)
Conference or Workshop Item

Abstract

We analyze a data-processing system with $n$ clients producing jobs which are processed in \textit{batches} by $m$ parallel servers; the system throughput critically depends on the batch size and a corresponding sub-additive speedup function. In practice, throughput optimization relies on numerical searches for the optimal batch size, a process that can take up to multiple days in existing commercial systems. In this paper, we model the system in terms of a closed queueing network; a standard Markovian analysis yields the optimal throughput in $\omega\left(n^4\right)$ time. Our main contribution is a mean-field model of the system for the regime where the system size is large. We show that the mean-field model has a unique, globally attractive stationary point which can be found in closed form and which characterizes the asymptotic throughput of the system as a function of the batch size. Using this expression we find the \textit{asymptotically} optimal throughput in $O(1)$ time. Numerical settings from a large commercial system reveal that this asymptotic optimum is accurate in practical finite regimes.

Item Type: Conference or Workshop Item
Erschienen: 2020
Creators: Kar, Sounak ; Rehrmann, Robin ; Mukhopadhyay, Arpan ; Alt, Bastian ; Ciucu, Florin ; Koeppl, Heinz ; Binnig, Carsten ; Rizk, Amr
Type of entry: Bibliographie
Title: On the Throughput Optimization in Large-Scale Batch-Processing Systems
Language: English
Date: 2 November 2020
Event Title: 38th International Symposium on Computer Performance, Modeling, Measurements and Evaluation (PERF 2020)
Event Location: virtual Conference
Event Dates: 02.-06.11.2020
URL / URN: https://www.performance2020.deib.polimi.it/private-program/
Corresponding Links:
Abstract:

We analyze a data-processing system with $n$ clients producing jobs which are processed in \textit{batches} by $m$ parallel servers; the system throughput critically depends on the batch size and a corresponding sub-additive speedup function. In practice, throughput optimization relies on numerical searches for the optimal batch size, a process that can take up to multiple days in existing commercial systems. In this paper, we model the system in terms of a closed queueing network; a standard Markovian analysis yields the optimal throughput in $\omega\left(n^4\right)$ time. Our main contribution is a mean-field model of the system for the regime where the system size is large. We show that the mean-field model has a unique, globally attractive stationary point which can be found in closed form and which characterizes the asymptotic throughput of the system as a function of the batch size. Using this expression we find the \textit{asymptotically} optimal throughput in $O(1)$ time. Numerical settings from a large commercial system reveal that this asymptotic optimum is accurate in practical finite regimes.

Uncontrolled Keywords: B4
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Bioinspired Communication Systems
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Multimedia Communications
DFG-Collaborative Research Centres (incl. Transregio)
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > B: Adaptation Mechanisms
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > B: Adaptation Mechanisms > Subproject B4: Planning
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > C: Communication Mechanisms
DFG-Collaborative Research Centres (incl. Transregio) > Collaborative Research Centres > CRC 1053: MAKI – Multi-Mechanisms Adaptation for the Future Internet > C: Communication Mechanisms > Subproject C2: Information-centred perspective
Date Deposited: 26 Oct 2020 11:13
Last Modified: 19 Nov 2021 10:46
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