Ke Wang

Affiliations:
  • Intel
  • Illinois Institute of Technology, Chicago, IL, USA


According to our database1, Ke Wang authored at least 21 papers between 2013 and 2016.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2016
Exploring the Design Tradeoffs for Extreme-Scale High-Performance Computing System Software.
IEEE Trans. Parallel Distributed Syst., 2016

Toward high-performance key-value stores through GPU encoding and locality-aware encoding.
J. Parallel Distributed Comput., 2016

Load-balanced and locality-aware scheduling for data-intensive workloads at extreme scales.
Concurr. Comput. Pract. Exp., 2016

A convergence of key-value storage systems from clouds to supercomputers.
Concurr. Comput. Pract. Exp., 2016

Albatross: An efficient cloud-enabled task scheduling and execution framework using distributed message queues.
Proceedings of the 12th IEEE International Conference on e-Science, 2016

2015
Towards Scalable Distributed Workload Manager with Monitoring-Based Weakly Consistent Resource Stealing.
Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing, 2015

A Dynamically Scalable Cloud Data Infrastructure for Sensor Networks.
Proceedings of the 6th Workshop on Scientific Cloud Computing, 2015

Overcoming Hadoop Scaling Limitations through Distributed Task Execution.
Proceedings of the 2015 IEEE International Conference on Cluster Computing, 2015

GRAPH/Z: A Key-Value Store Based Scalable Graph Processing System.
Proceedings of the 2015 IEEE International Conference on Cluster Computing, 2015

MHT: A light-weight scalable zero-hop MPI enabled distributed key-value store.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

A flexible QoS fortified distributed key-value storage system for the cloud.
Proceedings of the 2015 IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, CA, USA, October 29, 2015

FaBRiQ: Leveraging Distributed Hash Tables towards Distributed Publish-Subscribe Message Queues.
Proceedings of the 2nd IEEE/ACM International Symposium on Big Data Computing, 2015

2014
Next generation job management systems for extreme-scale ensemble computing.
Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing, 2014

Achieving Efficient Distributed Scheduling with Message Queues in the Cloud for Many-Task Computing and High-Performance Computing.
Proceedings of the 14th IEEE/ACM International Symposium on Cluster, 2014

FusionFS: Toward supporting data-intensive scientific applications on extreme-scale high-performance computing systems.
Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

Optimizing load balancing and data-locality with data-aware scheduling.
Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

2013
Exploring reliability of exascale systems through simulations.
Proceedings of the 2013 Spring Simulation Multiconference, SpringSim '13, 2013

SimMatrix: SIMulator for MAny-Task computing execution fabRIc at eXascale.
Proceedings of the 2013 Spring Simulation Multiconference, SpringSim '13, 2013

Using simulation to explore distributed key-value stores for extreme-scale system services.
Proceedings of the International Conference for High Performance Computing, 2013

Modeling Many-Task Computing Workloads on a Petaflop IBM Blue Gene/P Supercomputer.
Proceedings of the 2013 IEEE International Symposium on Parallel & Distributed Processing, 2013

ZHT: A Light-Weight Reliable Persistent Dynamic Scalable Zero-Hop Distributed Hash Table.
Proceedings of the 27th IEEE International Symposium on Parallel and Distributed Processing, 2013


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