Data-parallel programming on MIMD computers
Data-parallel programming on MIMD computers
A migratable user-level process package for PVM
Journal of Parallel and Distributed Computing - Special issue on workstation clusters and network-based computing
Transparent adaptive parallelism on NOWs using OpenMP
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
OpenMP on networks of workstations
SC '98 Proceedings of the 1998 ACM/IEEE conference on Supercomputing
Adaptive Parallelism and Piranha
Computer
An Overview of a Compiler for Scalable Parallel Machines
Proceedings of the 6th International Workshop on Languages and Compilers for Parallel Computing
Dome: Parallel Programming in a Heterogeneous Multi-User Environment
Dome: Parallel Programming in a Heterogeneous Multi-User Environment
Adaptive and reliable parallel computing on networks of workstations
ATEC '97 Proceedings of the annual conference on USENIX Annual Technical Conference
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We present a system that allows task parallel OpenMP programs to execute on a network of workstations (NOW) with a variable number of nodes. Such adaptivity, generally called adaptive parallelism, is important in a multi-user NOW environment, enabling the system to expand the computation onto idle nodes or withdraw from otherwise occupied nodes. We focus on task parallel applications in this paper, but the system also lets data parallel applications run adaptively. When an adaptation is requested, we let all processes complete their current tasks, then the system executes an extra OpenMP join-fork sequence not present in the application code. Here, the system can change the number of nodes without involving the application, as processes do not have a compute-relevant private process state. We show that the costs of adaptations is low, and we explain why the costs are lower for task parallel applications than for data parallel applications.