id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-027451-ztx9fsbg	De Chiara, Davide	Data Mining for Big Dataset-Related Thermal Analysis of High Performance Computing (HPC) Data Center	2020-05-25		.txt	text/plain	5758	326	51	This work presents an algorithm that clusters hotspots with the goal of reducing a data centre's large thermal-gradient due to uneven distribution of server dissipated waste heat followed by increasing cooling effectiveness. Thermal-aware schedulers adopt different thermal-aware approaches (e.g. system-level for work placements [16] ; execute 'hot' jobs on 'cold' compute nodes; predictive model for job schedule selection [17] ; ranked node queue based on thermal characteristics of rack layouts and optimisation (e.g. optimal setpoints for workload distribution and supply temperature of the cooling system). Analysis conducted are as follows: hotspots localisation; users categorisations based on submitted jobs to CRESCO6 cluster; compute nodes categorisation based on thermal behaviour of internal and surrounding air temperatures due to workload related waste heat dissipation. Data collected are related to: relevant parameters for each node (e.g. inlet air temperature, internal temperature of each node, energy consumption of CPU, RAM, memory, etc…); environmental parameters (e.g. air temperatures and humidity in both the hot and cold aisles); cooling system related parameters (e.g. fan speed); and finally, individual users who submit their jobs to cluster node.	./cache/cord-027451-ztx9fsbg.txt	./txt/cord-027451-ztx9fsbg.txt