Thorsten Hater

According to our database1, Thorsten Hater authored at least 12 papers between 2013 and 2022.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2022
Exploring Parameter and Hyper-Parameter Spaces of Neuroscience Models on High Performance Computers With Learning to Learn.
Frontiers Comput. Neurosci., 2022

Exploring hyper-parameter spaces of neuroscience models on high performance computers with Learning to Learn.
CoRR, 2022

2020
Archival Data Repository Services to Enable HPC and Cloud Workflows in a Federated Research e-Infrastructure.
Proceedings of the IEEE/ACM International Workshop on Interoperability of Supercomputing and Cloud Technologies, 2020

2019
Performance Comparison for Neuroscience Application Benchmarks.
Proceedings of the High Performance Computing, 2019

2017
Strategies for Forward Modelling of Infrared Radiative Transfer on GPUs.
Proceedings of the Parallel Computing is Everywhere, 2017

2016
Exploring Energy Efficiency for GPU-Accelerated POWER Servers.
Proceedings of the High Performance Computing, 2016

Exploiting In-Memory Processing Capabilities for Density Functional Theory Applications.
Proceedings of the Euro-Par 2016: Parallel Processing Workshops, 2016

Addressing Materials Science Challenges Using GPU-accelerated POWER8 Nodes.
Proceedings of the Euro-Par 2016: Parallel Processing, 2016

2015
Accelerating LBM and LQCD Application Kernels by In-Memory Processing.
Proceedings of the High Performance Computing - 30th International Conference, 2015

A Performance Model for GPU-Accelerated FDTD Applications.
Proceedings of the 22nd IEEE International Conference on High Performance Computing, 2015

2014
Performance Evaluation of Scientific Applications on POWER8.
Proceedings of the High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation, 2014

2013
Characterizing Performance of Applications on Blue Gene/Q.
Proceedings of the Parallel Computing: Accelerating Computational Science and Engineering (CSE), 2013


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