Scalability of heterogeneous parallel systems

Kalinov, Alexey

doi:10.1134/s0361768806010014

Cited by 9 publications

(6 citation statements)

References 15 publications

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“…This means that, in most cases, the techniques used on homogeneous parallel systems must be reworked to be applied to systems which are not necessarily homogeneous [3,7].…”

Section: Background and Objectivesmentioning

confidence: 99%

Dynamic Load Balancing on Dedicated Heterogeneous Systems

Galindo¹,

Almeida²,

Badía³

2008

Recent Advances in Parallel Virtual Machine and Message Passing Interface

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Abstract. Parallel computing in heterogeneous environments is drawing considerable attention due to the growing number of these kind of systems. Adapting existing code and libraries to such systems is a fundamental problem. The performance of this code is affected by the large interdependence between the code and these parallel architectures. We have developed a dynamic load balancing library that allows parallel code to be adapted to heterogeneous systems for a wide variety of problems. The overhead introduced by our system is minimal and the cost to the programmer negligible. The strategy was validated on several problems to confirm the soundness of our proposal.

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“…This means that, in most cases, the techniques used on homogeneous parallel systems must be reworked to be applied to systems which are not necessarily homogeneous [3,7].…”

Section: Background and Objectivesmentioning

confidence: 99%

Dynamic Load Balancing on Dedicated Heterogeneous Systems

Galindo¹,

Almeida²,

Badía³

2008

Recent Advances in Parallel Virtual Machine and Message Passing Interface

View full text Add to dashboard Cite

show abstract

“…There are different scalability and efficiency indicators for heterogeneous systems referred in bibliography [1,3,5]. Many references suggest that the node with more computational power should be taken as a reference.…”

Section: Discussionmentioning

confidence: 99%

“…Each node has a Maximum Number of Cores given by MNC. In Table 1 the set of four heterogeneous systems used in our experiments is described, where each row specifies the number of cores used from each node (1)(2)(3)(4)(5). It means that the data in Table 1 gives the number of used cores of each node in each heterogeneous system.…”

Section: Discussionmentioning

confidence: 99%

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Automatic tuning of iterative computation on heterogeneous multiprocessors with ADITHE

et al. 2009

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This work studies the problem of balancing the workload of iterative algorithms on heterogeneous multiprocessors. An approach, called ADITHE, is proposed and evaluated. Its main features are: (1) using a homogeneous distribution of the workload on the heterogeneous system, the speed of every node is estimated during the first iterations of the algorithm; (2) according to the speed of every node, a new workload distribution is carried out; (3) the remaining iterations of the algorithm are executed. The result of this workload redistribution is that the execution times for every iteration at every node are similar and, consequently, the penalties due to synchronization between nodes at every iteration are mostly eliminated. This approach is appropriate for iterative algorithms with similar workload at every iteration, and with a relevant number of iterations. The high portability of ADITHE is guaranteed because the estimation of speed of nodes is included in the execution of the parallel algorithm. There is a wide variety of iterative algorithms related to science and engineering which can take advantage of ADITHE. An example of this kind of algorithms (morphological processing of hyperspectral images) is considered in this work to evaluate its performance when ADITHE is applied. The analysis of the re-152 J. A. Martínez et al. sults shows that ADITHE significantly improves the performance of parallel iterative algorithms on heterogeneous platforms.

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“…This means that, in most cases, the techniques used on homogeneous parallel systems must be reworked in order to be applied to systems which are not necessarily homogeneous [12,13]. The objective of this work is to develop a simple and efficient dynamic adaptation strategy of the code for heterogeneous systems that minimizes code intrusion so that the program can be adapted without any prior knowledge of the architecture and without the need to develop analytical models.…”

Section: Objectivesmentioning

confidence: 99%

Adaptive load balancing of iterative computation on heterogeneous nondedicated systems

et al. 2011

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Dynamic load balancing in heterogeneous systems is a fundamental research topic in parallel computing due to the high availability of such systems. The efficient utilization of the heterogeneous resources can significantly enhance the performance of the parallel system. At the same time, adapting parallel codes to state-ofthe-art parallel computers composed of heterogeneous multinode-multicore processors becomes a very hard task because parallel codes are highly dependent on the parallel architectures. That means that applications must be tailored requiring a great deal of programming effort. We have developed the ALBIC (Adaptive Load Balancing of Iterative Computation) system that allows for the dynamic load balancing of iterative codes in heterogeneous dedicated and nondedicated Linux based systems. In order to validate the system several parallel codes have been analyzed in different scenarios. The results show that the ALBIC approach achieves better performance than the other proposal. This lightweighted library eases porting homogeneous parallel codes to heterogeneous platforms, since the code intrusion is low and the programming effort is quite reduced.

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Scalability of heterogeneous parallel systems

Cited by 9 publications

References 15 publications

Dynamic Load Balancing on Dedicated Heterogeneous Systems

Dynamic Load Balancing on Dedicated Heterogeneous Systems

Automatic tuning of iterative computation on heterogeneous multiprocessors with ADITHE

Adaptive load balancing of iterative computation on heterogeneous nondedicated systems

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