Algorithmic approach for applying load balancing during task migration in multi-core system

Johari, Suchi; Kumar, Arvind

doi:10.1109/pdgc.2014.7030710

Cited by 5 publications

(6 citation statements)

References 3 publications

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“…Some amount of waiting is therefore almost inevitable, even if such system software as load balancers may support the run-time redistribution of partially executed threads across cores, through such techniques as task (thread) migration. Task migration is the transfer of partially executed tasks from a core or a cluster of cores to another core or cluster of cores in M/MCP [31][32][33][34]. Task migration may be used to migrate a task from heavily loaded cores to lightly loaded or idle cores in M/ MCP, in particular for HeMCP, in order to balance the load across all cores.…”

Section: Normal Form Of Core Heterogeneitymentioning

confidence: 99%

Section: Parallelism and P-fractions!mentioning

confidence: 99%

“…Equation (37) is closely connected with the multi-Amdahl model (33). Indeed, if we subdivide the resource X into Q parts instead of n and define the efficiency function as e x j = 1/ A j , (33) transforms into (37). The major difference, however, is that the constraint (32) is not required: different configurations are allowed to reuse the same cores or resources because their execution times do not overlap.…”

Section: Parallelism and P-fractions!mentioning

confidence: 99%

“…Task migration is the transfer of partially executed tasks from a core or a cluster of cores to another core or cluster of cores in M/MCP [31–34]. Task migration may be used to migrate a task from heavily loaded cores to lightly loaded or idle cores in M/MCP, in particular for HeMCP, in order to balance the load across all cores.…”

Section: Normal Form Of Core Heterogeneitymentioning

confidence: 99%

“…Various problems related to mapping parallelisable (mostly software) workloads onto M/MCP hardware platforms have also been intensely scrutinised. The energy-efficient load balancing, task migration and scheduling have been the target of substantial investigations [5,[31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

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Amdahl's law in the context of heterogeneous many‐core systems – a survey

Al-hayanni

Xia

Rafiev

et al. 2020

IET Computers & Digital Techniques

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For over 50 years, Amdahl's Law has been the hallmark model for reasoning about performance bounds for homogeneous parallel computing resources. As heterogeneous, many-core parallel resources continue to permeate into the modern server and embedded domains, there has been growing interest in promulgating realistic extensions and assumptions in keeping with newer use cases. This study aims to provide a comprehensive review of the purviews and insights provided by the extensive body of work related to Amdahl's law to date, focusing on computation speedup. The authors show that a significant portion of these studies has looked into analysing the scalability of the model considering both workload and system heterogeneity in real-world applications. The focus has been to improve the definition and semantic power of the two key parameters in the original model: the parallel fraction (f) and the computation capability improvement index (n). More recently, researchers have shown normal-form and multi-fraction extensions that can account for wider ranges of heterogeneity, validated on many-core systems running realistic workloads. Speedup models from Amdahl's law onwards have seen a wide range of uses, such as the optimisation of system execution, and these uses are even more important with the advent of the heterogeneous many-core era.

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Section: Normal Form Of Core Heterogeneitymentioning

confidence: 99%