On Performance Resilient Scheduling for Scientific Workflows in HPC Systems with Constrained Storage Resources
文献类型：会议论文
| 作者 | Yang Wang; Wei Shi; Eduardo Berrocal |
| 出版日期 | 2015 |
| 会议名称 | ScienceCloud 2015 |
| 会议地点 | USA |
| 英文摘要 | Although the storage capacity is rapidly increasing, the size of datasets is also ever-growing, especially for those workflows in HPC that perform the parameter sweep studies. Consequently, the deadlock caused by the storage competition between concurrent workflow instances is still a major pragmatic concern and storage management remains important for high performance and throughput computing. In practice, there are various ways to this issue,ranging from admission control to deadlock resolution. Despite being a simple solution, the admission control is conservative and not space efficient to storage utilization. Therefore, in this paper,we study the performance of the deadlock resolution approach by proposing a resource allocation algorithm which is performance resilient to the workflows characterized by different features. The algorithm is designed based on our previous result, called DDS,which takes advantages of the dataflow information of the workflow to resolve deadlock based on detection&recovery principle. We improve DDS to allow it to not only resolve the deadlock but also overcome the performance anomaly, a not yet investigated prperformance-resilience algorithm, denoted as DDS+. The studiesoblem in our previous studies. We thus called the improved algorithm in this paper can be viewed as a follow-up research on DDS and show the performance behavior of the improved algorithm in various conditions. Therefore, the results in this paper are more useful to adapt DDS+ to the workflows with different characteristics in reality while keeping the performance stable. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/6996]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | 2015 |
| 推荐引用方式 GB/T 7714 | Yang Wang,Wei Shi,Eduardo Berrocal. On Performance Resilient Scheduling for Scientific Workflows in HPC Systems with Constrained Storage Resources[C]. 见:ScienceCloud 2015. USA. |
入库方式： OAI收割
来源：深圳先进技术研究院
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