SwePub - sökning: WFRF:(Chi Yaoyao)

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1.	Sun, Jinghao, et al. (författare) On the Volume Calculation for Conditional DAG Tasks : Hardness and Algorithms 2020 Ingår i: PROCEEDINGS OF THE 2020 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE 2020). - NEW YORK, USA. - 9783981926347 ; , s. 204-209 Konferensbidrag (refereegranskat)abstract The hardness of analyzing conditional directed acyclic graph (DAG) tasks remains unknown so far. For example, previous researches asserted that the conditional DAG's volume can be solved in polynomial time. However, these researches all assume well-nested structures that are recursively composed by single-source-single-sink parallel and conditional components. For conditional DAGs in general that do not comply with this assumption, the hardness and algorithms of volume computation are still open. In this paper, we construct counterexamples to show that previous work cannot provide a safe upper bound of the conditional DAG's volume in general. Moreover, we prove that the volume computation problem for conditional DAGs is strongly NP-hard. Finally, we propose an exact algorithm for computing the conditional DAG's volume. Experiments show that our method can significantly improve the accuracy of the conditional DAG's volume estimation.

Sun, Jinghao, et al. (författare)
On the Volume Calculation for Conditional DAG Tasks : Hardness and Algorithms
2020
Ingår i: PROCEEDINGS OF THE 2020 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION (DATE 2020). - NEW YORK, USA. - 9783981926347 ; , s. 204-209
Konferensbidrag (refereegranskat)abstract
- The hardness of analyzing conditional directed acyclic graph (DAG) tasks remains unknown so far. For example, previous researches asserted that the conditional DAG's volume can be solved in polynomial time. However, these researches all assume well-nested structures that are recursively composed by single-source-single-sink parallel and conditional components. For conditional DAGs in general that do not comply with this assumption, the hardness and algorithms of volume computation are still open. In this paper, we construct counterexamples to show that previous work cannot provide a safe upper bound of the conditional DAG's volume in general. Moreover, we prove that the volume computation problem for conditional DAGs is strongly NP-hard. Finally, we propose an exact algorithm for computing the conditional DAG's volume. Experiments show that our method can significantly improve the accuracy of the conditional DAG's volume estimation.

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