Helgi I. Ingólfsson

According to our database, Helgi I. Ingólfsson authored at least 10 papers between 2016 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2022

A biology-informed similarity metric for simulated patches of human cell membrane.

Harsh Bhatia, Jayaraman J. Thiagarajan, Rushil Anirudh, T. S. Jayram, Tomas Oppelstrup, Helgi I. Ingólfsson, Felice C. Lightstone, Peer-Timo Bremer

Mach. Learn. Sci. Technol., 2022

Identifying Orientation-specific Lipid-protein Fingerprints using Deep Learning.

Fikret Aydin, Konstantia Georgouli, Gautham Dharuman, James N. Glosli, Felice C. Lightstone, Helgi I. Ingólfsson, Peer-Timo Bremer, Harsh Bhatia

CoRR, 2022

Emerging Patterns in the Continuum Representation of Protein-Lipid Fingerprints.

Konstantia Georgouli, Helgi I. Ingólfsson, Fikret Aydin, Mark Heimann, Felice C. Lightstone, Peer-Timo Bremer, Harsh Bhatia

CoRR, 2022

2021

Machine-learning-based dynamic-importance sampling for adaptive multiscale simulations.

Harsh Bhatia, Timothy S. Carpenter, Helgi I. Ingólfsson, Gautham Dharuman, Piyush Karande, Shusen Liu, Tomas Oppelstrup, Chris Neale, Felice C. Lightstone, Brian Van Essen, James N. Glosli, Peer-Timo Bremer

Nat. Mach. Intell., 2021

Generalizable coordination of large multiscale workflows: challenges and learnings at scale.

Harsh Bhatia, Francesco Di Natale, Joseph Y. Moon, Xiaohua Zhang, Joseph R. Chavez, Fikret Aydin, Christopher B. Stanley, Tomas Oppelstrup, Chris Neale, Sara Kokkila Schumacher, Dong H. Ahn, Stephen Herbein, Timothy S. Carpenter, Sandrasegaram Gnanakaran, Peer-Timo Bremer, James N. Glosli, Felice C. Lightstone, Helgi I. Ingólfsson

Proceedings of the International Conference for High Performance Computing, 2021

2020

Predicting Small Molecule Transfer Free Energies by Combining Molecular Dynamics Simulations and Deep Learning.

W. F. Drew Bennett, Stewart He, Camille L. Bilodeau, Derek Jones, Delin Sun, Hyojin Kim, Jonathan E. Allen, Felice C. Lightstone, Helgi I. Ingólfsson

J. Chem. Inf. Model., 2020

Flux: Overcoming scheduling challenges for exascale workflows.

Dong H. Ahn, Ned Bass, Albert Chu, Jim Garlick, Mark Grondona, Stephen Herbein, Helgi I. Ingólfsson, Joseph Koning, Tapasya Patki, Thomas R. W. Scogland, Becky Springmeyer, Michela Taufer

Future Gener. Comput. Syst., 2020

2019

Comparing GPU Power and Frequency Capping: A Case Study with the MuMMI Workflow.

Tapasya Patki, Zachary Frye, Harsh Bhatia, Francesco Di Natale, James N. Glosli, Helgi I. Ingólfsson, Barry Rountree

Proceedings of the 2019 IEEE/ACM Workflows in Support of Large-Scale Science, 2019

A massively parallel infrastructure for adaptive multiscale simulations: modeling RAS initiation pathway for cancer.

Francesco Di Natale, Harsh Bhatia, Timothy S. Carpenter, Chris Neale, Sara Kokkila Schumacher, Tomas Oppelstrup, Liam Stanton, Xiaohua Zhang, Shiv Sundram, Thomas R. W. Scogland, Gautham Dharuman, Michael P. Surh, Yue Yang, Claudia Misale, Lars Schneidenbach, Carlos H. A. Costa, Changhoan Kim, Bruce D'Amora, Sandrasegaram Gnanakaran, Dwight V. Nissley, Frederick H. Streitz, Felice C. Lightstone, Peer-Timo Bremer, James N. Glosli, Helgi I. Ingólfsson

Proceedings of the International Conference for High Performance Computing, 2019

2016

Martini straight: Boosting performance using a shorter cutoff and GPUs.

Djurre H. De Jong, Svetlana Baoukina, Helgi I. Ingólfsson, Siewert J. Marrink

Comput. Phys. Commun., 2016