Search Results for author: Piotr Luszczek

Found 3 papers, 1 papers with code

SpikeRL: A Scalable and Energy-efficient Framework for Deep Spiking Reinforcement Learning

no code implementations21 Feb 2025 Tokey Tahmid, Mark Gates, Piotr Luszczek, Catherine D. Schuman

In our initial implementation of SpikeRL framework, we depended on the population encoding from the Population-coded Spiking Actor Network (PopSAN) method for our SNN model and implemented distributed training with Message Passing Interface (MPI) through mpi4py.

continuous-control Continuous Control +1

Materials Fingerprinting Classification

1 code implementation14 Jan 2021 Adam Spannaus, Kody J. H. Law, Piotr Luszczek, Farzana Nasrin, Cassie Putman Micucci, Peter K. Liaw, Louis J. Santodonato, David J. Keffer, Vasileios Maroulas

Significant progress in many classes of materials could be made with the availability of experimentally-derived large datasets composed of atomic identities and three-dimensional coordinates.

Classification General Classification +1

Task-Graph Scheduling Extensions for Efficient Synchronization and Communication

no code implementations6 Nov 2020 Seonmyeong Bak, Oscar Hernandez, Mark Gates, Piotr Luszczek, Vivek Sarkar

Task graphs have been studied for decades as a foundation for scheduling irregular parallel applications and incorporated in programming models such as OpenMP.

Distributed, Parallel, and Cluster Computing

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