Speedup Versus Efficiency in Parallel Systems
IEEE Transactions on Computers
Process control and scheduling issues for multiprogrammed shared-memory multiprocessors
SOSP '89 Proceedings of the twelfth ACM symposium on Operating systems principles
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
Analysis of task migration in shared-memory multiprocessor scheduling
SIGMETRICS '91 Proceedings of the 1991 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Scheduler activations: effective kernel support for the user-level management of parallelism
SOSP '91 Proceedings of the thirteenth ACM symposium on Operating systems principles
A dynamic processor allocation policy for multiprogrammed shared-memory multiprocessors
ACM Transactions on Computer Systems (TOCS)
Performance analysis of job scheduling policies in parallel supercomputing environments
Proceedings of the 1993 ACM/IEEE conference on Supercomputing
Efficient scheduling on multiprogrammed shared-memory multiprocessors
Efficient scheduling on multiprogrammed shared-memory multiprocessors
Evaluating the performance of cache-affinity scheduling in shared-memory multiprocessors
Journal of Parallel and Distributed Computing
The SGI Origin: a ccNUMA highly scalable server
Proceedings of the 24th annual international symposium on Computer architecture
Kernel-level scheduling for the nano-threads programming model
ICS '98 Proceedings of the 12th international conference on Supercomputing
First-class user-level threads
SOSP '91 Proceedings of the thirteenth ACM symposium on Operating systems principles
Starfire: Extending the SMP Envelope
IEEE Micro
Exploiting Parallelism Through Directives on the Nano-Threads Programming Model
LCPC '97 Proceedings of the 10th International Workshop on Languages and Compilers for Parallel Computing
Using Runtime Measured Workload Characteristics in Parallel Processor Scheduling
IPPS '96 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
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
(R) Automatic Self - allocation Threads (ASAT) on an SGI Challenge
ICPP '96 Proceedings of the Proceedings of the 1996 International Conference on Parallel Processing - Volume 3
Realistic workload scheduling policies for taming the memory bandwidth bottleneck of SMPs
HiPC'04 Proceedings of the 11th international conference on High Performance Computing
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Scheduling parallel applications on shared--memory multiprocessors is a difficult task that requires a lot of tuning from application programmers, as well as operating system developers and system managers. In this paper, we present the characteristics related to kernel--level scheduling of the NANOS environment and the results we are achieving. The NANOS environment is designed and tuned specifically to achieve high performance in current shared--memory multiprocessors. Taking advantage of the wide and efficient dialog established between applications and the NANOS environment, we are designing powerful scheduling policies. The information exchanged ranges from simply communicating the number of requested processors to providing information of the current speedup achieved by the applications. We have devised several scheduling policies that use this interface, such as Equipartition, Variable Time Quantum DSS and Dynamic Performance Analysis. The results we have obtained with these policies indicate that there is a lot of work to do in the search for a "good" scheduling policy, which can include characteristics like sustainable execution times, fairness and throughput. For instance, we show through several experiments that benefits in execution time range from 15% to 100%, depending on the policy used and the characteristics of the workload.