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| Content Provider | ACM Digital Library |
|---|---|
| Author | Goiri, I igo Nguyen, Thu D. Haque, Md E. Bianchini, Ricardo |
| Abstract | We propose GreenPar, a scheduler for parallel high-perormance applications in datacenters partially powered by on-site generation of renewable ("green'') energy. GreenPar schedules the workload to maximize the green energy consumption and minimize the grid ("brown'') energy consumption, while respecting a performance service-level agreement (SLA). When green energy is available, GreenPar increases the resource allocations of active jobs to reduce runtimes. When using brown energy, GreenPar reduces resource allocations within the constraints imposed by the performance SLA to conserve energy. GreenPar makes its decisions based on the speedup profile of each job. We have implemented GreenPar in a real solar-powered datacenter. Our results show that GreenPar can increase the green energy consumption and reduce both the average job runtime and the brown energy consumption, compared to schedulers that are oblivious to on-site green energy. |
| Starting Page | 217 |
| Ending Page | 227 |
| Page Count | 11 |
| File Format | |
| ISBN | 9781450335591 |
| DOI | 10.1145/2751205.2751221 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2015-06-08 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Energy-aware scheduling Renewable energy Datacenters |
| Content Type | Text |
| Resource Type | Article |
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