ACM Transactions on Computer Systems (TOCS)
Gossip-Based Computation of Aggregate Information
FOCS '03 Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science
The peer sampling service: experimental evaluation of unstructured gossip-based implementations
Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware
MRNet: A Software-Based Multicast/Reduction Network for Scalable Tools
Proceedings of the 2003 ACM/IEEE conference on Supercomputing
Using multiple energy gears in MPI programs on a power-scalable cluster
Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming
Gossip-based aggregation in large dynamic networks
ACM Transactions on Computer Systems (TOCS)
Just In Time Dynamic Voltage Scaling: Exploiting Inter-Node Slack to Save Energy in MPI Programs
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Analyzing the Energy-Time Trade-Off in High-Performance Computing Applications
IEEE Transactions on Parallel and Distributed Systems
ACM Transactions on Computer Systems (TOCS)
The promise, and limitations, of gossip protocols
ACM SIGOPS Operating Systems Review - Gossip-based computer networking
Lightweight Online Performance Monitoring and Tuning with Embedded Gossip
IEEE Transactions on Parallel and Distributed Systems
A gossip-style failure detection service
Middleware '98 Proceedings of the IFIP International Conference on Distributed Systems Platforms and Open Distributed Processing
LIBI: A framework for bootstrapping extreme scale software systems
Parallel Computing
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Large-scale server deployments in the commercial internet space have been using group based protocols such as peer-to-peer and gossip to allow coordination of services and data across global distributed data centers. Here we look at applying these methods, which are themselves derived from early work in distributed systems, to large-scale, tightly-coupled systems used in high performance computing. In this paper, we study Gossip protocols and their ability to aggregate data across large-scale systems in support of system services. We report accuracy and performance of these estimated results and then focus on a simulated power-capping service to show the tradeoffs of this approach in practice.