Dynamic Allocation of Processor Cores to Graph Applications on Commodity Servers
Graph processing is increasingly adopted to solve problems that span many application domains, including scientific computing, social networks, and big-data analytics. These applications present particular features (huge working sets and irregular scalability) that make the default Linux scheduler,...
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| Veröffentlicht in: | 2023 32nd International Conference on Parallel Architectures and Compilation Techniques (PACT) S. 323 - 324 |
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21.10.2023
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| Abstract | Graph processing is increasingly adopted to solve problems that span many application domains, including scientific computing, social networks, and big-data analytics. These applications present particular features (huge working sets and irregular scalability) that make the default Linux scheduler, which adopts a time-sharing policy to provide a fair scheduler, perform poorly when co-locating multiple graph applications in the same processor. This work focuses on maximizing processor utilization, which is a major concern of current data centers. To this end, we propose AFAIR, a flexible scheduling policy that allocates multiple graph applications on the same processor and assigns a fraction of the cores exclusively to each application instead of sharing them. Moreover, AFAIR dynamically adds/removes cores to the running applications, adapting the number of threads used for parallel execution to balance memory load. This allows AFAIR to achieve almost perfect fairness, on average 95%. |
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| AbstractList | Graph processing is increasingly adopted to solve problems that span many application domains, including scientific computing, social networks, and big-data analytics. These applications present particular features (huge working sets and irregular scalability) that make the default Linux scheduler, which adopts a time-sharing policy to provide a fair scheduler, perform poorly when co-locating multiple graph applications in the same processor. This work focuses on maximizing processor utilization, which is a major concern of current data centers. To this end, we propose AFAIR, a flexible scheduling policy that allocates multiple graph applications on the same processor and assigns a fraction of the cores exclusively to each application instead of sharing them. Moreover, AFAIR dynamically adds/removes cores to the running applications, adapting the number of threads used for parallel execution to balance memory load. This allows AFAIR to achieve almost perfect fairness, on average 95%. |
| Author | Sahuauillo, Julio Jones, Timothy M. Pons, Lucia |
| Author_xml | – sequence: 1 givenname: Lucia surname: Pons fullname: Pons, Lucia email: lupones@disca.upv.es organization: Universitat Politè cnica de València Valencia,Valencia,Spain – sequence: 2 givenname: Julio surname: Sahuauillo fullname: Sahuauillo, Julio email: jsahuqui@disca.upv.es organization: Universitat Politè cnica de València Valencia,Valencia,Spain – sequence: 3 givenname: Timothy M. surname: Jones fullname: Jones, Timothy M. email: timothy.jones@cl.cam.ac.uk organization: University of Cambridge,Cambridge,United Kingdom |
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| Snippet | Graph processing is increasingly adopted to solve problems that span many application domains, including scientific computing, social networks, and big-data... |
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| SubjectTerms | fair scheduling graph processing Instruction sets Linux Multicore processing multicore processor Processor scheduling resource management runtime optimization Scalability Scientific computing Social networking (online) |
| Title | Dynamic Allocation of Processor Cores to Graph Applications on Commodity Servers |
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