Scalability of Energy Efficiency in High-Performance Computing Systems

Abstract

This study focuses on analyzing the influence of the number of processors on performance and energy consumption in high-performance computers. We have developed conceptual models for potential improvement factors that could be achieved. We have applied these models and validated them using real data obtained from recent homogeneous and heterogeneous supercomputers listed in the TOP500 and Green500 rankings. Unlike previous studies, this study uses a large number of HPC systems to support the results: 237 systems for performance analysis, 96 for power consumption, and 32 for energy efficiency. The proposed models provide a better understanding of current architectural trends and allow for the assessment of achievable improvements in both computational performance and energy efficiency by increasing the number of CPUs or accelerators in each system. The study concludes that such improvements are more effective when increasing the number of accelerator cores rather than the CPU cores.