Parallel computing works
TL;DR: Parallel Computing Works! by G.C.C Fox, R.D. Williams, and P. c. Messina is a guide to parallel computing in the 21st Century.
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Abstract: Parallel Computing Works! by G.C. Fox, R.D. Williams, and P.C. Messina 977 pp. $69.95 Morgan Kaufmann San Francisco 1994 ISBN 1-55860-253-4
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Citations
Cooperative Robotics for Multi-Target Observation
TL;DR: An important issue that arises in the automation of many security, surveillance, and reconnaissance tasks is that of observing (or monitoring) the movements of targets navigating in a bounded area.
160
Cooperative multi-robot observation of multiple moving targets
Lynne E. Parker,B.A. Emmons +1 more
- 20 Apr 1997
TL;DR: This paper investigates the use of a cooperative team of autonomous sensor-based robots for multi-robot observation of multiple moving targets, and presents a distributed approximate approach to solving this problem that combines low-level multi- robot control with higher-level control.
Distributed frameworks and parallel algorithms for processing large-scale geographic data
Ken A. Hawick,Paul Coddington,H. A. James +2 more
- 01 Oct 2003
TL;DR: A historical review of work in this area over the last decade leads us to believe parallel computing will continue to play an important role in GIS and speculate on algorithmic and systems issues for the future.
PASSION: Parallel And Scalable Software for Input-Output
Alok Choudhary,Rajesh Bordawekar,Michael Harry,Rakesh Krishnaiyer +3 more
- 01 Jan 1994
TL;DR: The PASSION compiler is to automatically translate out-of-core data parallel programs to node programs for distributed memory machines, with calls to the PASSION Runtime Library, which provides support at the language, compiler, runtime as well as system level.
Dynamic load balancing strategies for conservative parallel simulations
Azzedine Boukerche,Sajal K. Das +1 more
- 01 Jun 1997
TL;DR: A dynamic load balancing algorithm which assumes no compile time knowledge about the workload parameters is proposed, based upon a process migration mechanism, and the notion of CPU-queue length, which indicates the workload at each processor.
103
References
Cooperative Robotics for Multi-Target Observation
TL;DR: An important issue that arises in the automation of many security, surveillance, and reconnaissance tasks is that of observing (or monitoring) the movements of targets navigating in a bounded area.
160
Cooperative multi-robot observation of multiple moving targets
Lynne E. Parker,B.A. Emmons +1 more
- 20 Apr 1997
TL;DR: This paper investigates the use of a cooperative team of autonomous sensor-based robots for multi-robot observation of multiple moving targets, and presents a distributed approximate approach to solving this problem that combines low-level multi- robot control with higher-level control.
Distributed frameworks and parallel algorithms for processing large-scale geographic data
Ken A. Hawick,Paul Coddington,H. A. James +2 more
- 01 Oct 2003
TL;DR: A historical review of work in this area over the last decade leads us to believe parallel computing will continue to play an important role in GIS and speculate on algorithmic and systems issues for the future.
PASSION: Parallel And Scalable Software for Input-Output
Alok Choudhary,Rajesh Bordawekar,Michael Harry,Rakesh Krishnaiyer +3 more
- 01 Jan 1994
TL;DR: The PASSION compiler is to automatically translate out-of-core data parallel programs to node programs for distributed memory machines, with calls to the PASSION Runtime Library, which provides support at the language, compiler, runtime as well as system level.
Hybrid cloud and cluster computing paradigms for life science applications
Judy Qiu,Jaliya Ekanayake,Thilina Gunarathne,Jong Youl Choi,Seung-Hee Bae,Hui Li,Bingjing Zhang,Tak-Lon Wu,Yang Ruan,Saliya Ekanayake,Adam Hughes,Geoffrey C. Fox +11 more
TL;DR: The hybrid cloud (MapReduce) and cluster (MPI) approach offers an attractive production environment while Twister promises a uniform programming environment for many Life Sciences applications.
101