# Investigating Supercomputer Performance with Sustainability in the Era of Artificial Intelligence
## 5 Results and Discussion
### Core Counts
In contrast, the core counts of supercomputers in the top EE rankings are much lower, consistently remaining in the thousands. None of the top-EE supercomputers in 2021 had core counts of 1 million or higher. Notably, _MN-3_, which secured the number 1 spot on the list of the 10 most energy-efficient supercomputers, had only 1664 cores, a stark contrast to the millions of cores seen in the top 10 systems in terms of performance. Interestingly, _Perlmutter_ and _Juwels_, both having fewer than a million cores, achieved recognition in both the top 10 for performance and the top 10 for EE. This demonstrates the ability to balance high computational performance with sustainability, challenging the notion that large core counts are essential for achieving peak performance. Figure 6 illustrates the core counts of supercomputers ranked in the top 10 for both performance and EE in 2020. Similar to the trend observed in 2021, the core counts of the top-performing supercomputers show a balanced distribution: 50% have core counts in the millions, while the remaining 50% have core counts in the hundreds of thousands. For the EE supercomputers, most core counts remain in the thousands, with the notable exceptions of _Fugaku_, _Summit_, and _NA-1_ with core counts in the millions. In addition, _Juwels_, _Selene_,  
Figure 4: Supercomputer core counts for 2022: core counts of the top-performing supercomputers for (**A**) November and (**C**) June; core counts of the most energy-efficient supercomputers for (**B**) November and (**D**) June. _HPC5, Fugaku_, and _Marconi-100_ are notable for appearing in both the top 10 for performance and the top 10 for EER. Figure 5: Supercomputer core counts for 2021: core counts of the top-performing supercomputers for (**A**) November and (**C**) June; core counts of the most energy-efficient supercomputers for (**B**) November and (**D**) June. Figure 6: Supercomputer core counts for 2020: core counts of the top-performing supercomputers for (**A**) November and (**C**) June; core counts of the most energy-efficient supercomputers for (**B**) November and (**D**) June. The year 2020 stands out as a significant milestone for achieving a balance between core counts for powerful computation and sustainability. Five supercomputers, comprising a combination of systems with hundreds of thousands and millions of cores, achieved placement in both the top performance and top energy efficiency rankings. This highlights the ability to balance exceptional computational power with sustainable energy use. Observations and Implications  
A closer look at the 2024 trend reveals that _Frontier_ and _LUMI_ find it challenging to maintain positions in the top 10 EE rankings achieved in 2023 and 2022 but retained spots among the top 10 supercomputers in terms of performance. This shift is likely because new supercomputing systems that are more energy efficient entered the Green500 list. Therefore, it could be concluded that more work is being performed to improve the energy efficiency of new machines than to improve the performance of the machines. It has been observed that supercomputers consistently securing the number 1 spot in the top 10 EE rankings typically have a very small number of cores. The only exception is _Frontier TDS_, which once achieved the top position with 120,832 cores. However, in most cases, the number of cores for the top-EE supercomputers remains below 20,000 throughout the period under study. The disparity in number of cores between top-performing supercomputers and top-EE supercomputers highlights a significant trade-off in achieving peak computational performance. Conversely, supercomputers optimized for EE appear to have lower core counts, possibly to reduce energy consumption and improve power utilization ratios. This trend likely underscores the strategy of minimizing core counts as a critical factor in achieving and maintaining sustainability.