A Practical Algorithm Design and Evaluation for Heterogeneous Elastic Computing with Stragglers
Our extensive real measurements over Amazon EC2 show that the virtual instances often have different computing speeds even if they share the same configurations. This motivates us to study heterogeneous Coded Storage Elastic Computing (CSEC) systems where machines, with different computing speeds, j...
Gespeichert in:
Hauptverfasser: | , , , |
---|---|
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Our extensive real measurements over Amazon EC2 show that the virtual
instances often have different computing speeds even if they share the same
configurations. This motivates us to study heterogeneous Coded Storage Elastic
Computing (CSEC) systems where machines, with different computing speeds, join
and leave the network arbitrarily over different computing steps. In CSEC
systems, a Maximum Distance Separable (MDS) code is used for coded storage such
that the file placement does not have to be redefined with each elastic event.
Computation assignment algorithms are used to minimize the computation time
given computation speeds of different machines. While previous studies of
heterogeneous CSEC do not include stragglers-the slow machines during the
computation, we develop a new framework in heterogeneous CSEC that introduces
straggler tolerance. Based on this framework, we design a novel algorithm using
our previously proposed approach for heterogeneous CSEC such that the system
can handle any subset of stragglers of a specified size while minimizing the
computation time. Furthermore, we establish a trade-off in computation time and
straggler tolerance. Another major limitation of existing CSEC designs is the
lack of practical evaluations using real applications. In this paper, we
evaluate the performance of our designs on Amazon EC2 for applications of the
power iteration and linear regression. Evaluation results show that the
proposed heterogeneous CSEC algorithms outperform the state-of-the-art designs
by more than 30%. |
---|---|
DOI: | 10.48550/arxiv.2107.08496 |