ACM Computing Surveys (CSUR)
Designing efficient algorithms for parallel computers
Designing efficient algorithms for parallel computers
Graph Algorithms
Computer Architecture and Parallel Processing
Computer Architecture and Parallel Processing
Distributed Sorting on Local Area Networks
IEEE Transactions on Computers
Finding an extremum in a network
ISCA '82 Proceedings of the 9th annual symposium on Computer Architecture
Combinatorial Algorithms: Theory and Practice
Combinatorial Algorithms: Theory and Practice
Graph Theory with Applications to Engineering and Computer Science (Prentice Hall Series in Automatic Computation)
Optimal NODUP All-to-All Broadcast Schemes in Distributed Computing Systems
IEEE Transactions on Parallel and Distributed Systems
On General Results for All-to-All Broadcast
IEEE Transactions on Parallel and Distributed Systems
Broadcast-Efficient Protocols for Mobile Radio Networks
IEEE Transactions on Parallel and Distributed Systems
Solving An Algebraic Path Problem and Some Related Graph Problems on a Hyper-Bus Broadcast Network
IEEE Transactions on Parallel and Distributed Systems
Energy-Efficient Routing in the Broadcast Communication Model
IEEE Transactions on Parallel and Distributed Systems
An Optimal Multiple Bus Network for Fan-in Algorithms
ICPP '97 Proceedings of the international Conference on Parallel Processing
A Fast Sorting Algorithm and Its Generalization on Broadcast Communications
COCOON '00 Proceedings of the 6th Annual International Conference on Computing and Combinatorics
| Hi-index | 14.98 |
Some common guidelines that can be used to design parallel algorithms under the single-channel broadcast communication model are presented. Several graph problems are solved, including topological ordering, the connected component problem, breadth-first search, and depth-first search. If an ideal conflict resolution scheme is used, all of the algorithms require O(n) time by using n processors. Under such a situation, the algorithms are all optimal. If a realistic conflict resolution is used, the algorithms require O(n log n) time by using n/log n processors. For both cases, all of the algorithms achieve optimal speedups.