# Log Analysis-Based Resource and Execution Time Improvement in HPC: A Case Study
## 5 Conclusions and Future Work  
Parallel computing is a suitable solution for solving large-scale problems. The main content of this study is to optimize the order of jobs executed in the Tachyon2 system to efficiently use the entire available resources. This experiment analyzed the actual logs of job execution using the converted log in the Tachyon2 system. Note that the average utilization of the Tachyon2 system is about 85.6% and the average wait time is about 9.3 hours. This can be seen as a fragmentation of resources that occur during scheduling. Of course, it is not possible to use all the resources perfectly to reflect both usage and execution time. However, it is possible to minimize resource fragmentation occurring during job scheduling and to make resource utilization more efficient by analyzing the jobs performed on the computational resources. Such utilization can be more improved by studying and applying the appropriate scheduling algorithms. One way is to analyze the statistics of large-scale operations, which are gradually increasing in the Tachyon2 system, to grasp the user's success rate, execution time, and resource size. Based on the statistical results, the backfill scheduling algorithm is studied and simulated to reduce resource fragmentation in Tachyon2. This study effectively used available resources and reduced turnaround time for backfilled tasks. In the end, we improved the performance of the overall scheduler.  
This paper focuses on the simulation of the backfill scheduling algorithm that analyzes the supercomputer's job statistics and targets cases of inefficient resource use. Although it is useful to understand how to improve the utilization of an actively working system, it is necessary for us to apply the various scheduling algorithms to the current system and analyze the work execution history continuously and repeatedly as future work. In that sense, research is needed to apply advanced algorithms that reflect when a job is done earlier than expected or when available resources are suddenly added. Such research will optimize resource utilization and reduce overall user latency. In this experiment, our main target system was the Tacyon2 supercomputer. As of writing, the next generation of KISTI's 5 th supercomputer Nurion consists of 8400 compute nodes based on many-core architectures and production services launched in December 2018. Therefore, it is worth evaluating newly delivered supercomputers with the same approach to find the resource underutilization problem, ultimately providing more resources to scientists for better and faster scientific outcomes.  
**Author Contributions:** Conceptualization, J.Y.; Methodology, J.Y., S.-Y.N. and C.P.; Data curation, J.Y.; Software, J.Y.; Validation, J.Y., S.-Y.N. and H.Y.; Investigation, J.Y. and C.P.; Writing--Original Draft Preparation, J.Y.; Writing--Review & Editing, J.Y. and S.-Y.N.; Supervision, H.Y.; Project administration, T.H.; Funding acquisition, T.H. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research has been performed as a subproject of Project No. K-19-L02-C01-S01 (The National Supercomputing Infrastructure Construction and Service) supported by the KOREA INSTITUTE of SCIENCE and TECHNOLOGY INFORMATION(KISTI).  
**Conflicts of Interest:** The authors declare no conflict of interest.