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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Vydáno v:The Journal of supercomputing Ročník 74; číslo 10; s. 5399 - 5431
Hlavní autoři: Khalid, Yasir Noman, Aleem, Muhammad, Prodan, Radu, Iqbal, Muhammad Azhar, Islam, Muhammad Arshad
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.10.2018
Springer Nature B.V
Témata:
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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Shrnutí: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.
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ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-018-2435-1