A Fast Heuristic for Improving the Energy Efficiency of Asymmetric VFI-Based Manycore Systems

Voltage/Frequency Islands (VFIs) are practically used in multicore systems. VFIs cluster cores share the same Voltage/Frequency (V/F) levels for the entire application runtime. Using VFIs, switching V/F levels has less overhead per-core while saving more energy in exchange for tolerable execution de...

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Bibliographic Details
Published in:IEEE transactions on sustainable computing 2022-04, Vol.7 (2), p.358-370
Main Authors: Hajiamini, Shervin, Shirazi, Behrooz, Dong, Hongbo
Format: Article
Language:English
Subjects:
Algorithms
Clustering
Electric potential
Energy budget
Energy consumption
Energy efficiency
Energy-aware systems
Heuristic
heuristic methods
multi-core/single-chip multiprocessors
Multicore processing
Optimization
Run time (computers)
Runtime
similarity measures
Sorting
Task analysis
Voltage
Workload
Workloads
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Summary:Voltage/Frequency Islands (VFIs) are practically used in multicore systems. VFIs cluster cores share the same Voltage/Frequency (V/F) levels for the entire application runtime. Using VFIs, switching V/F levels has less overhead per-core while saving more energy in exchange for tolerable execution delay. This paper targets the well-known K-means algorithm for clustering cores, where each cluster contains cores with similar computational workloads across application phases. K-means produces sub-optimal clusters when cores workloads do not have the same variation across all phases. Furthermore, the workload variations require running a VFI with a different V/F level per-phase. This paper presents a fast heuristic that facilitates clustering by sorting computational workloads per-phase before applying K-means. The VFIs V/F levels are dynamically adjusted to meet energy budget constraints. This framework provides a guideline for users to choose a number of clusters that satisfies system configurations and energy efficiency preferences. Three parameters are evaluated to represent the computational workloads: utilization, Instruction-Per-Cycle (IPC), and execution time. For an application with highly varying workload, execution time achieves 52 and 65% percent more energy efficiency compared to utilization and IPC, respectively. Results show that the degree of workload variations for different applications impacts changing or fixing VFIs V/F levels.
ISSN:2377-3782
2377-3782
2377-3790
DOI:10.1109/TSUSC.2021.3092730