Scheduling in multiprogrammed parallel systems
SIGMETRICS '88 Proceedings of the 1988 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Workcrews: an abstraction for controlling parallelism
International Journal of Parallel Programming
Global optimization
The performance of multiprogrammed multiprocessor scheduling algorithms
SIGMETRICS '90 Proceedings of the 1990 ACM SIGMETRICS conference on Measurement and modeling of computer systems
The Processor Working Set and its Use in Scheduling Multiprocessor Systems
IEEE Transactions on Software Engineering
SPLASH: Stanford parallel applications for shared-memory
ACM SIGARCH Computer Architecture News
A dynamic processor allocation policy for multiprogrammed shared-memory multiprocessors
ACM Transactions on Computer Systems (TOCS)
Robust partitioning policies of multiprocessor systems
Performance Evaluation - Special issue: performance modeling of parallel processing systems
Using compile-time analysis and transformations to reduce false sharing on shared-memory multiprocessors
A case for user-level dynamic page migration
Proceedings of the 14th international conference on Supercomputing
IEEE Software
Adaptive Scheduling for Master-Worker Applications on the Computational Grid
GRID '00 Proceedings of the First IEEE/ACM International Workshop on Grid Computing
Measuring Consistency Costs for Distributed Shared Data
LCR '00 Selected Papers from the 5th International Workshop on Languages, Compilers, and Run-Time Systems for Scalable Computers
Integrated scheduling: the best of both worlds
Journal of Parallel and Distributed Computing
Non-clair voy ant multiprocessor scheduling of jobs with changing execution characteristics
Journal of Scheduling - Special issue: On-line scheduling
Adaptive work stealing with parallelism feedback
Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming
Proceedings of the 13th international conference on Architectural support for programming languages and operating systems
Adaptive work-stealing with parallelism feedback
ACM Transactions on Computer Systems (TOCS)
Realistic workload scheduling policies for taming the memory bandwidth bottleneck of SMPs
HiPC'04 Proceedings of the 11th international conference on High Performance Computing
| Hi-index | 0.00 |
We address the problem of maximizing application speedup through runtime, self-selection of an appropriate number of processors on which to run. Automatic, runtime selection of processor allocations is important because many parallel applications exhibit peak speedups at allocations that are data or time dependent. We propose the use of a runtime system that: (a) dynamically measures job efficiencies at different allocations, (b) uses these measurements to calculate speedups, and (c) automatically adjusts a job's processor allocation to maximize its speedup. Using a set of 10 applications that includes both hand-coded parallel programs and compiler-parallelized sequential programs, we show that our runtime system can reliably determine dynamic allocations that match the best possible static allocation, and that it has the potential to find dynamic allocations that outperform any static allocation.