Process control and scheduling issues for multiprogrammed shared-memory multiprocessors
SOSP '89 Proceedings of the twelfth ACM symposium on Operating systems principles
International Journal of High Speed Computing
The performance of multiprogrammed multiprocessor scheduling algorithms
SIGMETRICS '90 Proceedings of the 1990 ACM SIGMETRICS conference on Measurement and modeling of computer systems
SIGMETRICS '91 Proceedings of the 1991 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Using processor affinity in loop scheduling on shared-memory multiprocessors
Proceedings of the 1992 ACM/IEEE conference on Supercomputing
A dynamic processor allocation policy for multiprogrammed shared-memory multiprocessors
ACM Transactions on Computer Systems (TOCS)
Data locality and load balancing in COOL
PPOPP '93 Proceedings of the fourth ACM SIGPLAN symposium on Principles and practice of parallel programming
Hardware and software for functional and fine grain parallelism
Hardware and software for functional and fine grain parallelism
Cilk: an efficient multithreaded runtime system
PPOPP '95 Proceedings of the fifth ACM SIGPLAN symposium on Principles and practice of parallel programming
On the implementation and effectiveness of autoscheduling for shared-memory multiprocessors
On the implementation and effectiveness of autoscheduling for shared-memory multiprocessors
Proceedings of the Workshop on Micro-kernels and Other Kernel Architectures
A Library Implementation of the Nano-Threads Programming Model
Euro-Par '96 Proceedings of the Second International Euro-Par Conference on Parallel Processing-Volume II
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The authors present the analysis, in a dynamic processor allocation environment, of four scheduling algorithms running on top of the nano-threads programming model. Three of them are well-known: uniform-sized chunking, guided self-scheduling and trapezoid self-scheduling. The fourth is their proposal: adaptable size chunking. In that environment, applications are automatically decomposed into tasks by a parallelizing compiler which uses the hierarchical task graph to represent the source application. The parallel code is an executable representation of this graph with the support of a user-level library (the nano-threads library). The execution environment includes a user-level process (CPU manager) which controls the allocation of processors to applications. The analysis of the scheduling algorithms shows it is possible to provide enough information to the library to allow a fast adaptation to dynamic changes in the processors allocated to the application.