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29 March 2024 |
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Article overview
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CMS Workflow Execution using Intelligent Job Scheduling and Data Access Strategies | Khawar Hasham
; Antonio Delgado Peris
; Ashiq Anjum
; Dave Evans
; Dirk Hufnagel
; Eduardo Huedo
; José M. Hernández
; Richard McClatchey
; Stephen Gowdy
; Simon Metson
; | Date: |
24 Feb 2012 | Abstract: | Complex scientific workflows can process large amounts of data using
thousands of tasks. The turnaround times of these workflows are often affected
by various latencies such as the resource discovery, scheduling and data access
latencies for the individual workflow processes or actors. Minimizing these
latencies will improve the overall execution time of a workflow and thus lead
to a more efficient and robust processing environment. In this paper, we
propose a pilot job based infrastructure that has intelligent data reuse and
job execution strategies to minimize the scheduling, queuing, execution and
data access latencies. The results have shown that significant improvements in
the overall turnaround time of a workflow can be achieved with this approach.
The proposed approach has been evaluated, first using the CMS Tier0 data
processing workflow, and then simulating the workflows to evaluate its
effectiveness in a controlled environment. | Source: | arXiv, 1202.5480 | Services: | Forum | Review | PDF | Favorites |
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