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20232025
most citedLASSI: An LLM-based Automated Self-Correcting Pipeline for Translating Parallel Scientific Codes

8 citations · 9 across the 8 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

physics.ins-det2024

Co-Design of 2D Heterojunctions for Data Filtering in Tracking Systems

Tupendra Oli, Wilkie Olin-Ammentorp, Xingfu Wu +5

As particle physics experiments evolve to achieve higher energies and resolutions, handling the massive data volumes produced by silicon pixel detectors, which are used for charged…

cs.SE2024★ 8 cited

LASSI: An LLM-based Automated Self-Correcting Pipeline for Translating Parallel Scientific Codes

Matthew T. Dearing, Yiheng Tao, Xingfu Wu +2

This paper addresses the problem of providing a novel approach to sourcing significant training data for LLMs focused on science and engineering. In particular, a crucial challenge…

cs.DC2024

Modeling Performance of Data Collection Systems for High-Energy Physics

Wilkie Olin-Ammentorp, Xingfu Wu, Andrew A. Chien

Exponential increases in scientific experimental data are outstripping the rate of progress in silicon technology. As a result, heterogeneous combinations of architectures and proc…

cs.LG2024

An Autotuning-based Optimization Framework for Mixed-kernel SVM Classifications in Smart Pixel Datasets and Heterojunction Transistors

Xingfu Wu, Tupendra Oli, Justin H. Qian +3

Support Vector Machine (SVM) is a state-of-the-art classification method widely used in science and engineering due to its high accuracy, its ability to deal with high dimensional…

cs.PF2024

Integrating ytopt and libEnsemble to Autotune OpenMC

Xingfu Wu, John R. Tramm, Jeffrey Larson +7

ytopt is a Python machine-learning-based autotuning software package developed within the ECP PROTEAS-TUNE project. The ytopt software adopts an asynchronous search framework that…