61 citations
- KTH Royal Institute of TechnologySE6 papers
- Culham Centre for Fusion EnergyGB2 papers
- Jülich Supercomputing CentreDE2 papers
- Seagate (Ireland)IE2 papers
- ARM (United Kingdom)GB1 paper
- Center for Integrated Quantum Science and TechnologyDE1 paper
- Element Six (United Kingdom)GB1 paper
- Instituto Superior TécnicoPT1 paper
- Max Planck Institute for Solid State ResearchDE1 paper
- Oak Ridge National LaboratoryUS1 paper
- Seagate (United States)US1 paper
- Universität für Weiterbildung KremsAT1 paper
10 papers
Self-Consistent Computation of Spin Torques and Magneto-Resistance in Tunnel Junctions and Magnetic Read-Heads with Metallic Pinhole Defects
Serban Lepadatu, Alexey Dobrynin
A three-dimensional self-consistent spin transport model is developed, which includes both tunnelling transport, as well as metallic transport. Using the spin accumulation computed…
Enhanced Gilbert Damping in Re doped FeCo Films: A Combined Experimental and Theoretical Study
Serkan Akansel, Ankit Kumar, Vijayahahan A. Venugopal +10
The effects of rhenium doping in the range 0 to 10 atomic percent on the static and dynamic magnetic properties of Fe65Co35 thin films have been studied experimentally as well as w…
Decoupled Strategy for Imbalanced Workloads in MapReduce Frameworks
Sergio Rivas-Gomez, Sai Narasimhamurthy, Keeran Brabazon +3
In this work, we consider the integration of MPI one-sided communication and non-blocking I/O in HPC-centric MapReduce frameworks. Using a decoupled strategy, we aim to overlap the…
MPI Windows on Storage for HPC Applications
Sergio Rivas-Gomez, Roberto Gioiosa, Ivy Bo Peng +4
Upcoming HPC clusters will feature hybrid memories and storage devices per compute node. In this work, we propose to use the MPI one-sided communication model and MPI windows as un…
Characterizing Deep-Learning I/O Workloads in TensorFlow
Steven W. D. Chien, Stefano Markidis, Chaitanya Prasad Sishtla +4
The performance of Deep-Learning (DL) computing frameworks rely on the performance of data ingestion and checkpointing. In fact, during the training, a considerable high number of…
The SAGE Project: a Storage Centric Approach for Exascale Computing
Sai Narasimhamurthy, Nikita Danilov, Sining Wu +8
SAGE (Percipient StorAGe for Exascale Data Centric Computing) is a European Commission funded project towards the era of Exascale computing. Its goal is to design and implement a B…