No abstract

High-Performance Computing (HPC) platforms are growing in size and complexity. In order to improve the quality of service of such platforms, researchers are devoting a great amount of effort to devise algorithms and techniques to improve different aspects of performance such as energy consumption, total usage of the platform, and fairness between users. In spite of this, system administrators are always reluctant to deploy state of the art scheduling methods and most of them revert to EASY-backfilling, also known as EASY-FCFS (EASY-First-Come-First-Served). Newer methods frequently are complex and obscure and the simplicity and transparency of EASY are too important to sacrifice. In this work, we used execution logs from five HPC platforms to compare four simple scheduling policies: FCFS, Shortest estimated Processing time First (SPF), Smallest Requested Resources First (SQF), and Smallest estimated Area First (SAF). Using simulations, we performed a thorough analysis of the cumulative results for up to 180 weeks and considered three scheduling objectives: waiting time, slowdown and per-processor slowdown. We also evaluated other effects, such as the relationship between job size and slowdown, the distribution of slowdown values, and the number of backfilled jobs, for each HPC platform and scheduling policy. We conclude that one can only gain by replacing EASYbackfilling with SAF with backfilling, as it offers improvements in performance by up to 80% in the slowdown metric while maintaining the simplicity and the transparency of FCFS. Moreover, SAF reduces the number of jobs with large slowdowns and the inclusion of a simple thresholding mechanism guarantees that no starvation occurs. Finally, we propose SAF as a new benchmark for future scheduling studies.

No abstract

Social distancing in response to the COVID-19 pandemic brought several modifications in our daily lives. With these changes, some people have reported alterations in their feelings of how fast time was passing. In this study, we assessed whether and how social distancing and the evolution of the COVID-19 pandemic influenced participants’ time awareness and production of time intervals. Participants ( n = 3855) filled in the first questionnaire approximately 60 days after the start of social distancing in Brazil and weekly questionnaires for 15 weeks during social distancing. Our results indicate that time was perceived as expanded at the beginning, but this feeling decreased across the weeks. Time awareness was strongly associated with psychological factors such as loneliness, stress, and positive emotions, but not with time production. This relation was shown between participants and within their longitudinal reports. Together, our findings show how emotions are a crucial aspect of how time is felt.

No abstract