A bridging model for parallel computation
Communications of the ACM
Direct bulk-synchronous parallel algorithms
Journal of Parallel and Distributed Computing
Performance of the NAS parallel benchmarks on PVM-based networks
Journal of Parallel and Distributed Computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
The design, implementation and evaluation of SMART: a scheduler for multimedia applications
Proceedings of the sixteenth ACM symposium on Operating systems principles
Scheduling with implicit information in distributed systems
SIGMETRICS '98/PERFORMANCE '98 Proceedings of the 1998 ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
A feedback-driven proportion allocator for real-rate scheduling
OSDI '99 Proceedings of the third symposium on Operating systems design and implementation
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Impact of job mix on optimizations for space sharing schedulers
Supercomputing '96 Proceedings of the 1996 ACM/IEEE conference on Supercomputing
Performance characteristics of gang scheduling in multiprogrammed environments
SC '97 Proceedings of the 1997 ACM/IEEE conference on Supercomputing
The Linux-SRT Integrated Multimedia Operating System: Bringing QoS to the Desktop
RTAS '01 Proceedings of the Seventh Real-Time Technology and Applications Symposium (RTAS '01)
Feedback Control Scheduling in Distributed Real-Time Systems
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
Dynamic Integrated Scheduling of Hard Real-Time, Soft Real-Time and Non-Real-Time Processes
RTSS '03 Proceedings of the 24th IEEE International Real-Time Systems Symposium
Feedback Utilization Control in Distributed Real-Time Systems with End-to-End Tasks
IEEE Transactions on Parallel and Distributed Systems
VSched: Mixing Batch And Interactive Virtual Machines Using Periodic Real-time Scheduling
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
A comparison of local and gang scheduling on a Beowulf cluster
CLUSTER '04 Proceedings of the 2004 IEEE International Conference on Cluster Computing
Automatic, run-time and dynamic adaptation of distributed applications executing in virtual environments
Increasing application performance in virtual environments through run-time inference and adaptation
HPDC '05 Proceedings of the High Performance Distributed Computing, 2005. HPDC-14. Proceedings. 14th IEEE International Symposium
Enabling self-management of component-based high-performance scientific applications
HPDC '05 Proceedings of the High Performance Distributed Computing, 2005. HPDC-14. Proceedings. 14th IEEE International Symposium
Human-driven optimization
Black box methods for inferring parallel applications' properties in virtual environments
Black box methods for inferring parallel applications' properties in virtual environments
Autonomic Provisioning of Backend Databases in Dynamic Content Web Servers
ICAC '06 Proceedings of the 2006 IEEE International Conference on Autonomic Computing
CPU Service Classes for Multimedia Applications
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Performance specifications and metrics for adaptive real-time systems
RTSS'10 Proceedings of the 21st IEEE conference on Real-time systems symposium
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
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Most parallel machines, such as clusters, are space-shared in order to isolate batch parallel applications from each other and optimize their performance. However, this leads to low utilization or potentially long waiting times. We propose a self-adaptive approach to time-sharing such machines that provides isolation and allows the execution rate of an application to be tightly controlled by the administrator. Our approach combines a periodic real-time scheduler on each node with a global feedback-based control system that governs the local schedulers. We have developed an online system that implements our approach. The system takes as input a target execution rate for each application, and automatically and continuously adjusts the applications' real-time schedules to achieve those rates with proportional CPU utilization. Target rates can be dynamically adjusted. Applications are performance-isolated from each other and from other work that is not using our system. We present an extensive evaluation that shows that the system remains stable with low response times, and that our focus on CPU isolation and control does not come at the significant expense of network I/O, disk I/O, or memory isolation.