A data-centric approach to extreme-scale
            <i>ab initio</i>
            dissipative quantum transport simulations

Ziogas, Alexandros Nikolaos; Ben-Nun, Tal; Fernández, Guillermo Indalecio; Schneider, Timo; Luisier, Mathieu; Hoefler, Torsten

doi:10.1145/3295500.3357156

Cited by 35 publications

(26 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The OMEN [ 61 ] quantum transport simulator was used to compute the device characteristics. It self-consistently solves the Schrödinger and Poisson equations for electrons and a dynamical equation for phonons via the non-equilibrium Green’s function (NEGF) formalism [ 62 ].…”

Section: Methodsmentioning

confidence: 99%

Influence of the hBN Dielectric Layers on the Quantum Transport Properties of MoS2 Transistors

et al. 2022

Self Cite

View full text Add to dashboard Cite

The encapsulation of single-layer 2D materials within hBN has been shown to improve the mobility of these compounds. Nevertheless, the interplay between the semiconductor channel and the surrounding dielectrics is not yet fully understood, especially their electron–phonon interactions. Therefore, here, we present an ab initio study of the coupled electrons and phonon transport properties of MoS2-hBN devices. The characteristics of two transistor configurations are compared to each other: one where hBN is treated as a perfectly insulating, non-vibrating layer and one where it is included in the ab initio domain as MoS2. In both cases, a reduction of the ON-state current by about 50% is observed as compared to the quasi-ballistic limit. Despite the similarity in the current magnitude, explicitly accounting for hBN leads to additional electron–phonon interactions at frequencies corresponding to the breathing mode of the MoS2-hBN system. Moreover, the presence of an hBN layer around the 2D semiconductor affects the Joule-induced temperature distribution within the transistor.

show abstract

Section: Methodsmentioning

confidence: 99%

Influence of the hBN Dielectric Layers on the Quantum Transport Properties of MoS2 Transistors

et al. 2022

Self Cite

View full text Add to dashboard Cite

show abstract

“…We adapt an N-Body simulation program (nbody) of star orbits according to Newton's Law of Gravity [34]. We adapt two samples, coninteg and sselfeng from the OMEN quantum transport simulator [48,53]. The two samples represent computation patterns that appear in the simulation of nano-devices' thermal characteristics.…”

Section: Digital Signal Processingmentioning

confidence: 99%

NPBench

Ziogas

Ben-Nun

Schneider

et al. 2021

Proceedings of the ACM International Conference on Supercomputing

Self Cite

View full text Add to dashboard Cite

Python, already one of the most popular languages for scientific computing, has made significant inroads in High Performance Computing (HPC). At the center of Python's ecosystem is NumPy, an efficient implementation of the multi-dimensional array (tensor) structure, together with basic arithmetic and linear algebra. Compared to traditional HPC languages, the relatively low performance of Python and NumPy has spawned significant research in compilers and frameworks that decouple Python's compact representation from the underlying implementation. However, it is challenging to compare language compatibility and performance among different frameworks and architectures without a standard set of benchmarks and metrics. To that end, we introduce NPBench, a set of NumPy code samples representing a large variety of HPC applications. We use NPBench to test popular NumPy-accelerating compilers and frameworks on a variety of metrics. NPBench will guide both end-users and framework developers focusing on performance and will drive further use of Python in the high-performance scientific domains.

show abstract

“…DaCe [14], a data-centric approach, is presented to scale ab initio quantum transport simulations to extreme-scale, reaching an extraordinary performance of 85.45 PFLOPs/s (42.55% of the peak) in double precision on 4560 nodes of Summit. This study optimizes Ab initio quantum transport solver by analyzing data dependence.…”

Section: Performancementioning

confidence: 99%

Research trend of large-scale supercomputers and applications from the TOP500 and Gordon Bell Prize

Zheng

2020

Sci. China Inf. Sci.

View full text Add to dashboard Cite

China is playing an increasingly important role in international supercomputing. In highperformance computing domain, there are two famous awards: The TOP500 list for the fastest 500 supercomputers in the world and the Gordon Bell Prize for the best HPC (high-performance computing) applications. China has been awarded in both TOP500 list and Gordon Bell Prize. In this paper, we review the supercomputers in the latest TOP500 list and seven Gordon Bell Prize applications to show the research trend of the large-scale supercomputers and applications. The first trend we observe is that heterogeneous architectures are widely used in the construction of supercomputing systems. The second trend is that artificial intelligence applications are expected to become one of the main stream applications of supercomputing. The third trend is that applying heterogeneous systems to complex scientific simulation applications will be more difficult.

show abstract

A data-centric approach to extreme-scale ab initio dissipative quantum transport simulations

Cited by 35 publications

References 22 publications

Influence of the hBN Dielectric Layers on the Quantum Transport Properties of MoS2 Transistors

Influence of the hBN Dielectric Layers on the Quantum Transport Properties of MoS2 Transistors

NPBench

Research trend of large-scale supercomputers and applications from the TOP500 and Gordon Bell Prize

Contact Info

Product

Resources

About