E-OSched: a load balancing scheduler for heterogeneous multicores

The contemporary multicore era has adhered to the heterogeneous computing devices as one of the proficient platforms to execute compute-intensive applications. These heterogeneous devices are based on CPUs and GPUs. OpenCL is deemed as one of the industry standards to program heterogeneous machines....

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Vydané v:	The Journal of supercomputing Ročník 74; číslo 10; s. 5399 - 5431
Hlavní autori:	Khalid, Yasir Noman, Aleem, Muhammad, Prodan, Radu, Iqbal, Muhammad Azhar, Islam, Muhammad Arshad
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.10.2018 Springer Nature B.V
Predmet:	Compilers Computation Computer Science Computer simulation Industry standards Interpreters Load balancing Processor Architectures Programming Languages Resource scheduling Scheduling Servers State of the art Scheduling Load balancing Heterogeneous multicores Data-parallel applications
ISSN:	0920-8542, 1573-0484
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Abstract	The contemporary multicore era has adhered to the heterogeneous computing devices as one of the proficient platforms to execute compute-intensive applications. These heterogeneous devices are based on CPUs and GPUs. OpenCL is deemed as one of the industry standards to program heterogeneous machines. The conventional application scheduling mechanisms allocate most of the applications to GPUs while leaving CPU device underutilized. This underutilization of slower devices (such as CPU) often originates the sub-optimal performance of data-parallel applications in terms of load balance, execution time, and throughput. Moreover, multiple scheduled applications on a heterogeneous system further aggravate the problem of performance inefficiency. This paper is an attempt to evade the aforementioned deficiencies via initiating a novel scheduling strategy named OSched. An enhancement to the OSched named E-OSched is also part of this study. The OSched performs the resource-aware assignment of jobs to both CPUs and GPUs while ensuring a balanced load. The load balancing is achieved via contemplation on computational requirements of jobs and computing potential of a device. The load-balanced execution is beneficiary in terms of lower execution time, higher throughput, and improved utilization. The E-OSched reduces the magnitude of the main memory contention during concurrent job execution phase. The mathematical model of the proposed algorithms is evaluated by comparison of simulation results with different state-of-the-art scheduling heuristics. The results revealed that the proposed E-OSched has performed significantly well than the state-of-the-art scheduling heuristics by obtaining up to 8.09% improved execution time and up to 7.07% better throughput.
AbstractList	The contemporary multicore era has adhered to the heterogeneous computing devices as one of the proficient platforms to execute compute-intensive applications. These heterogeneous devices are based on CPUs and GPUs. OpenCL is deemed as one of the industry standards to program heterogeneous machines. The conventional application scheduling mechanisms allocate most of the applications to GPUs while leaving CPU device underutilized. This underutilization of slower devices (such as CPU) often originates the sub-optimal performance of data-parallel applications in terms of load balance, execution time, and throughput. Moreover, multiple scheduled applications on a heterogeneous system further aggravate the problem of performance inefficiency. This paper is an attempt to evade the aforementioned deficiencies via initiating a novel scheduling strategy named OSched. An enhancement to the OSched named E-OSched is also part of this study. The OSched performs the resource-aware assignment of jobs to both CPUs and GPUs while ensuring a balanced load. The load balancing is achieved via contemplation on computational requirements of jobs and computing potential of a device. The load-balanced execution is beneficiary in terms of lower execution time, higher throughput, and improved utilization. The E-OSched reduces the magnitude of the main memory contention during concurrent job execution phase. The mathematical model of the proposed algorithms is evaluated by comparison of simulation results with different state-of-the-art scheduling heuristics. The results revealed that the proposed E-OSched has performed significantly well than the state-of-the-art scheduling heuristics by obtaining up to 8.09% improved execution time and up to 7.07% better throughput.
Author	Aleem, Muhammad Islam, Muhammad Arshad Prodan, Radu Khalid, Yasir Noman Iqbal, Muhammad Azhar
Author_xml	– sequence: 1 givenname: Yasir Noman surname: Khalid fullname: Khalid, Yasir Noman organization: Capital University of Science and Technology – sequence: 2 givenname: Muhammad orcidid: 0000-0001-8342-5757 surname: Aleem fullname: Aleem, Muhammad email: aleem@cust.edu.pk organization: Capital University of Science and Technology – sequence: 3 givenname: Radu surname: Prodan fullname: Prodan, Radu organization: Alpen-Adria-Universität – sequence: 4 givenname: Muhammad Azhar surname: Iqbal fullname: Iqbal, Muhammad Azhar organization: Capital University of Science and Technology – sequence: 5 givenname: Muhammad Arshad surname: Islam fullname: Islam, Muhammad Arshad organization: Capital University of Science and Technology
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SubjectTerms	Compilers Computation Computer Science Computer simulation Industry standards Interpreters Load balancing Processor Architectures Programming Languages Resource scheduling Scheduling Servers State of the art
Title	E-OSched: a load balancing scheduler for heterogeneous multicores
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