Patrick Finnerty

Orcid: 0000-0002-9037-967X

According to our database1, Patrick Finnerty authored at least 12 papers between 2020 and 2024.

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

Timeline

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Bibliography

2024
On the Performance of Malleable APGAS Programs and Batch Job Schedulers.
SN Comput. Sci., April, 2024

BLE-Based Outdoor Localization With Two-Ray Ground-Reflection Model Using Optimization Algorithms.
IEEE Access, 2024

HAC: Hierarchical Agglomerative Clustering With Linear Programming for Wireless Sensor Networks.
IEEE Access, 2024

2023
Automatically balancing relocatable distributed collections.
Concurr. Comput. Pract. Exp., 2023

Distributed Cell Set : A Library for Space-Dependent Communication/Computation Overlap on Manycore Cluster.
Proceedings of the 14th International Workshop on Programming Models and Applications for Multicores and Manycores, 2023

Enhancing Supercomputer Performance with Malleable Job Scheduling Strategies.
Proceedings of the Euro-Par 2023: Parallel Processing Workshops - Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28, 2023

Malleable APGAS Programs and Their Support in Batch Job Schedulers.
Proceedings of the Euro-Par 2023: Parallel Processing Workshops - Euro-Par 2023 International Workshops, Limassol, Cyprus, August 28, 2023

2022
Supercharging the APGAS Programming Model with Relocatable Distributed Collections.
CoRR, 2022

A self-adjusting task granularity mechanism for the Java lifeline-based global load balancer library on many-core clusters.
Concurr. Comput. Pract. Exp., 2022

Optimization of Polling-based MAC Schedule Considering Data Aggregation for In-vehicle UWB Wireless Networks.
Proceedings of the 8th IEEE World Forum on Internet of Things, 2022

Integrating a global load balancer to an APGAS distributed collections library.
Proceedings of the PMAM@PPoPP 2022: Proceedings of the Thirteenth International Workshop on Programming Models and Applications for Multicores and Manycores, Virtual Event / Seoul, Republic of Korea, April 2, 2022

2020
Self-adjusting task granularity for Global load balancer library on clusters of many-core processors.
Proceedings of the PMAM@PPoPP '20: Eleventh International Workshop on Programming Models and Applications for Multicores and Manycores colocated with the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2020


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