This paper addresses optimal mapping of parallel programs composed of a chain of data parallel tasks onto the processors of a parallel system. The input to the programs is a stream of data sets, each of which is processed in order by the chain of tasks. This computation structure, also referred to a
Optimal parallel processing of random task graphs
β Scribed by Zhen Liu; Rhonda Righter
- Publisher
- Springer US
- Year
- 2001
- Tongue
- English
- Weight
- 180 KB
- Volume
- 4
- Category
- Article
- ISSN
- 1094-6136
- DOI
- 10.1002/jos.70
No coin nor oath required. For personal study only.
β¦ Synopsis
We consider scheduling of tasks of parallel programs on multiprocessor systems where tasks have precedence relations and synchronization points. The task graph structures are random variables in the sense that successors to a task do not become known until the task is executed. Thus, as is often the case with parallel processing, scheduling must occur at run time rather than compile time. We prove that a simple scheduling policy stochastically minimizes the processes of task completions and job (i.e. set of parallel tasks) completions for several classes of task graph structures.
π SIMILAR VOLUMES
Given a parallel program represented by a task graph, the objective of a scheduling algorithm is to minimize the overall execution time of the program by properly assigning the nodes of the graph to the processors. This multiprocessor scheduling problem is NP-complete even with simplifying assumptio
An outerplanar graph is a planar graph that can be imbedded in the plane in such a way that all vertices lie on the exterior face. An outerplanar graph is maximal if no edge can be added to the graph without violating the outerplanarity. In this paper, an optimal parallel algorithm is proposed on th
## Abstract We consider a denumerable state Markovian sequential control process. It is well known that when we consider the expected total discounted income as a criterion, there exists a nonrandomized stationary policy that is optimal. It is also well known that when we consider the expected aver