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
Speed of parallel processing for random task graphs
โ Scribed by Marco Isopi; Charles M. Newman
- Publisher
- John Wiley and Sons
- Year
- 1994
- Tongue
- English
- Weight
- 681 KB
- Volume
- 47
- Category
- Article
- ISSN
- 0010-3640
No coin nor oath required. For personal study only.
โฆ Synopsis
The random graph model of parallel computation introduced by Gelenbe et al. depends on three parameters: n, the number of tasks (vertices); F, the common distribution of T i , . . . , T,, the task processing times, and p = p,, the probability for a given i < j that task i must be completed before task j is started. The total processing time is R,,, the maximum sum of T,'s along directed paths of the graph. We study the large n behavior of Rn when np,, grows sublinearly but superlogarithmically, the regime where the longest directed path contains about enp,, tasks. For an exponential (mean one) F, we prove that R,, is about 4np,. The "discrepancy" between 4 and e is a large deviation effect.
Related results are obtained when np,, grows exactly logarithmically and when F is not exponential, but has a tail which decays (at least) exponentially fast. 01994 John Wiley L Sons, Inc.
๐ SIMILAR VOLUMES
We present a parallel randomized algorithm running on a CRCW PRAM, to determine whether two planar graphs are isomorphic, and if so to find the isomorphism. We assume that we have a tree of separators for each planar graph ลฝ ลฝ 2 . 1 q โ which can be computed by known algorithms in O log n time with