Abstract
Demand for multi-process resource invariably outstrips supply and users must often share some common provision. Where batch-based, whole processor allocation proves inflexible, user programs must compete at runtime for the same resource so the load is changeable and unpredictable. We are exploring a mechanism to balance the runtime load by moving computations between processors to optimize resource use. In this paper, we present a generic
algorithmic farm skeleton which is able to move worker tasks between processors in a heterogeneous architecture at runtime guided by a simple dynamic load model. Our experiments suggest that this mechanism is able to effectively compensate for unpredictable load variations.
algorithmic farm skeleton which is able to move worker tasks between processors in a heterogeneous architecture at runtime guided by a simple dynamic load model. Our experiments suggest that this mechanism is able to effectively compensate for unpredictable load variations.
| Original language | English |
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| Publication status | Published - Jul 2012 |
| Event | 18th International Conference on Parallel and Distributed Processing Techniques and Applications - Las Vegas, United States Duration: 16 Jul 2012 → 19 Jul 2012 |
Conference
| Conference | 18th International Conference on Parallel and Distributed Processing Techniques and Applications |
|---|---|
| Country/Territory | United States |
| City | Las Vegas |
| Period | 16/07/12 → 19/07/12 |