Incisor uses program analysis and frontier LLMs to select working AWS EC2 instances ex ante for 100% of first-time HPC runs of C/C++/Fortran and Python codes, cutting runtime 54% and costs 44% versus an expert-constrained SkyPilot baseline.
Mixed citations
LAMMPS-a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales
Mixed citation behavior. Most common role is method (50%).
7
Pith papers citing it
Method
50% of classified citations
citation-role summary
method 3
background 1
baseline 1
dataset 1
citation-polarity summary
years
2026 7representative citing papers
A 1.62-trillion-atom molecular dynamics simulation achieves ab initio accuracy with 100x speedup over prior machine learning force fields and 86.9% weak scaling to 45,000 GPGPUs.
An ontology-aligned framework for atomistic simulations that integrates over 750,000 triples to enable interoperable data querying and automated provenance tracking.
An accelerated hpcanalysis framework ingests performance data from 100,000 MPI ranks in 9.69 seconds, delivers up to 314x GPU speedup, maps network congestion on Aurora, and uses a new tri-dimensional model to identify 32.28% potential speedup in a GAMESS workload on Frontier.
Molecular dynamics simulations show that higher densities of extended defects in 3C-SiC reduce average elastic moduli by up to 6% with the Vashishta potential and 4% with ABOP.
The paper reviews key computational methods for ultrastable glasses, discusses their efficiency and limitations, and compares the stability levels achieved.
A critical review of AI surrogate models for multiscale combustion that compares supervised, unsupervised, and physics-guided methods, identifies transferability and consistency challenges, and outlines future opportunities.
citing papers explorer
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Incisor: Ex Ante Cloud Instance Selection for HPC Jobs
Incisor uses program analysis and frontier LLMs to select working AWS EC2 instances ex ante for 100% of first-time HPC runs of C/C++/Fortran and Python codes, cutting runtime 54% and costs 44% versus an expert-constrained SkyPilot baseline.
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Trillion-atom molecular dynamics simulations with ab initio accuracy
A 1.62-trillion-atom molecular dynamics simulation achieves ab initio accuracy with 100x speedup over prior machine learning force fields and 86.9% weak scaling to 45,000 GPGPUs.
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Ontology-based knowledge graph infrastructure for interoperable atomistic simulation data
An ontology-aligned framework for atomistic simulations that integrates over 750,000 triples to enable interoperable data querying and automated provenance tracking.
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Enhancing Performance Insight at Scale: A Heterogeneous Framework for Exascale Diagnostics
An accelerated hpcanalysis framework ingests performance data from 100,000 MPI ranks in 9.69 seconds, delivers up to 314x GPU speedup, maps network congestion on Aurora, and uses a new tri-dimensional model to identify 32.28% potential speedup in a GAMESS workload on Frontier.
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Molecular dynamics simulation study of mechanical properties of 3C-SiC with extended defects
Molecular dynamics simulations show that higher densities of extended defects in 3C-SiC reduce average elastic moduli by up to 6% with the Vashishta potential and 4% with ABOP.
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Computational Methods towards Ultrastable Glasses
The paper reviews key computational methods for ultrastable glasses, discusses their efficiency and limitations, and compares the stability levels achieved.
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AI-Powered Surrogate Modelling for Multiscale Combustion: A Critical Review and Opportunities
A critical review of AI surrogate models for multiscale combustion that compares supervised, unsupervised, and physics-guided methods, identifies transferability and consistency challenges, and outlines future opportunities.