Now showing items 1-6 of 6
Techniques and evaluation of processor co-allocation in multi-cluster systems
Computer processing power is increasing at a very high rate. A computer considered to be fast today may not be fast in a few years to come. At the same time, the number and complexity of resource intensive computer ...
Using the greedy approach to schedule jobs on multi-cluster systems
(WORLDCOMP 2006: The 2006 World Congress in Computer Science, Computer Engineering and Applied Computing, 2006)
Clusters, multi-cluster systems and the grid are becoming popular high performance computing infrastructures. How jobs are scheduled on them greatly influence the performance. Since jobs are online in most computer systems, ...
The Influence of Job Physical Characteristics on their Schedulability in Multi-cluster Systems
(Fountain Publishers, 2006)
Performance (and sensitivity) studies in parallel job scheduling mostly use average values of the measurement metrics over the entire job stream. This does not give an idea of relative job performance (hence starvation) ...
Performance, fairness and effectiveness in space slicing multi-cluster schedulers
(ACTA Press, 2007)
Parallel job schedulers have mostly been evaluated/compared using performance metrics. The deductions, however, can be misleading due to selective starvation. This calls for studies in scheduler fairness. Most studies have ...
Group-wise performance evaluation of processor co-allocation in multi-cluster systems
Performance evaluation in multi-cluster processor co-allocation - like in many other parallel job scheduling problems - is mostly done by computing the average metric value for the entire job stream. This does not give a ...
Co-allocation with communication considerations in multi-cluster systems
Processor co-allocation can be of performance benefit. This is because breaking jobs into components reduces overall cluster fragmentation. However, the slower inter-cluster communication links increase job execution times. ...