Demo Data from EDBT 2026 / reviewers in the wild / expert
Chih-En Hsu
dblp:421/2242
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0000-0002-9974-8611ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
High-performance computing · 75% Emerging computing paradigms · 25% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational science and engineering · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
High-performance computing › supercomputing
exascale computing |
0.9 | 1 | 2025 | Advancing Quantum Many-Body GW Calculations on Exascale Supercomputing Platforms · SC 2025 |
High-performance computing › performance engineering
performance portability |
0.9 | 1 | 2025 | Advancing Quantum Many-Body GW Calculations on Exascale Supercomputing Platforms · SC 2025 |
Emerging computing paradigms › quantum computing › quantum simulation
quantum many-body simulation |
0.9 | 1 | 2025 | Advancing Quantum Many-Body GW Calculations on Exascale Supercomputing Platforms · SC 2025 |
High-performance computing
scientific computing systems |
0.9 | 1 | 2025 | Advancing Quantum Many-Body GW Calculations on Exascale Supercomputing Platforms · SC 2025 |
Computational science and engineering › materials science
materials science simulation |
0.3 | 1 | 2025 | Advancing Quantum Many-Body GW Calculations on Exascale Supercomputing Platforms · SC 2025 |
Methods — techniques the papers use, named apart from their topics
GW approximation · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Advancing Quantum Many-Body GW Calculations on Exascale Supercomputing PlatformsabstractAdvanced ab initio materials simulations face growing challenges as increasing systems and phenomena complexity requires higher accuracy, driving up computational demands. Quantum many-body GW methods are state-of-the-art for treating electronic excited states and couplings but often hindered due to the costly numerical complexity. Here, we present innovative implementations of advanced GW methods within the BerkeleyGW package, enabling large-scale simulations on Frontier and Aurora exascale platforms. Our approach demonstrates exceptional versatility for complex heterogeneous systems with up to 17,574 atoms, along with achieving true performance portability across GPU architectures. We demonstrate excellent strong and weak scaling to thousands of nodes, reaching double-precision core-kernel performance of 1.069 ExaFLOP/s on Frontier (9,408 nodes) and 707.52 PetaFLOP/s on Aurora (9,600 nodes), corresponding to 59.45% and 48.79% of peak, respectively. Our work demonstrates a breakthrough in utilizing exascale computing for quantum materials simulations, delivering unprecedented predictive capabilities for rational designs of future quantum technologies. Benran Zhang, Daniel Weinberg, Chih-En Hsu, Aaron R. Altman, James B. White, Derek Vigil-Fowler, Steven G. Louie, Jack Deslippe, Felipe H. da Jornada, Zhenglu Li, Mauro Del Ben |
SC | 3 |