Name
Abstract | ||
|---|---|---|
Task graphs provide an efficient model of computation for specification, analysis, and implementation of concurrent applications. In this paper, we present a novel approach for mapping the class of series-parallel task graphs onto multi-core architectures based on pattern matching. Both the topology of the graph and the state of the tasks are encoded as a stream of tokens, which is iteratively rewritten at multiple positions in parallel. Hence, our technique is most useful for compute-intensive applications that must adapt to frequently varying and unpredictable workload at runtime. Several complex examples have been evaluated on a multi-core architecture and the experimental results show the effectiveness of our approach. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SAMOS.2013.6621123 | Embedded Computer Systems: Architectures, Modeling, and Simulation |
Keywords | Field | DocType |
graph theory,multiprocessing systems,pattern matching,processor scheduling,rewriting systems,compute-intensive applications,concurrent applications,dynamic task mapping,graph topology,multicore architectures,pattern matching,physical restrictions,power constraints,series-parallel task graphs,stream rewriting,task scheduling | Graph theory,Architecture,Workload,Computer science,Parallel computing,Task mapping,Model of computation,Rewriting,Multi-core processor,Pattern matching | Conference |
Citations | PageRank | References |
3 | 0.40 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lars Middendorf | 1 | 16 | 4.07 |
| Christian Zebelein | 2 | 38 | 5.43 |
| Christian Haubelt | 3 | 796 | 68.77 |