In parallel systems, similar jobs tend to arrive within bursty periods. This fact leads to the existence of the locality phenomenon, a persistent similarity between nearby jobs, in...
This paper analyzes the effect of overbooking for scheduling systems in a commercial environment. In this scenario each job is associated with a release time and a finishing deadl...
Abstract. Grids reliability remains an order of magnitude below clusters on production infrastructures. This work is aimsed at improving grid application performances by improving ...
Diane Lingrand, Johan Montagnat, Janusz Martyniak,...
It is important to identify scalability constraints in existing job scheduling software as they are applied to next generation parallel systems. In this paper, we analyze the scala...
Norman Bobroff, Richard Coppinger, Liana Fong, See...
In this paper, we address the problem of finding workload exchange policies for decentralized Computational Grids using an Evolutionary Fuzzy System. To this end, we establish a n...
Abstract. This paper describes a new and novel scheme for job admission and resource allocation employed by the SODA scheduler in System S. Capable of processing enormous quantitie...
Joel L. Wolf, Nikhil Bansal, Kirsten Hildrum, Suja...
Abstract. As multi-core processors proliferate, it has become more important than ever to ensure efficient execution of parallel jobs on multiprocessor systems. In this paper, we s...
Scheduling a task graph onto several processors is a trade-off between maximising concurrency and minimising interprocessor communication. A technique to reduce or avoid interproc...
In this paper, we examine the concept of giving every job a trial run before committing it to run until completion. Trial runs allow immediate job failures to be detected shortly a...
Ojaswirajanya Thebe, David P. Bunde, Vitus J. Leun...
The number of applications with many parallel cooperating processes is steadily increasing, and developing efficient runtimes for their execution is an important task. Several fram...