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ORCIDTristan Vanderbruggen
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2020 – today
- 2023
[c15]Le Chen
, Pei-Hung Lin, Tristan Vanderbruggen, Chunhua Liao, Murali Emani, Bronis R. de Supinski:
LM4HPC: Towards Effective Language Model Application in High-Performance Computing. IWOMP 2023: 18-33- [c14]Le Chen, Xianzhong Ding, Murali Emani, Tristan Vanderbruggen, Pei-Hung Lin, Chunhua Liao:
Data Race Detection Using Large Language Models. SC Workshops 2023: 215-223 - [c13]Xianzhong Ding, Le Chen, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Zhen Xie, Alberto Cerpa, Wan Du:
HPC-GPT: Integrating Large Language Model for High-Performance Computing. SC Workshops 2023: 951-960 - [i7]Tristan Vanderbruggen, Chunhua Liao, Peter Pirkelbauer, Pei-Hung Lin:
Structured Thoughts Automaton: First Formalized Execution Model for Auto-Regressive Language Models. CoRR abs/2306.10196 (2023) - [i6]Le Chen, Pei-Hung Lin, Tristan Vanderbruggen, Chunhua Liao, Murali Emani, Bronis R. de Supinski:
LM4HPC: Towards Effective Language Model Application in High-Performance Computing. CoRR abs/2306.14979 (2023) - [i5]Le Chen, Xianzhong Ding, Murali Emani, Tristan Vanderbruggen, Pei-Hung Lin, Chunhua Liao:
Data Race Detection Using Large Language Models. CoRR abs/2308.07505 (2023) - [i4]Xianzhong Ding, Le Chen, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Zhen Xie, Alberto E. Cerpa, Wan Du:
HPC-GPT: Integrating Large Language Model for High-Performance Computing. CoRR abs/2311.12833 (2023) - 2022
- [c12]Winson Chen, Tristan Vanderbruggen, Pei-Hung Lin, Chunhua Liao, Murali Emani:
Early Experience with Transformer-Based Similarity Analysis for DataRaceBench. Correctness@SC 2022: 45-53 - [c11]Patrick J. Flynn, Tristan Vanderbruggen, Chunhua Liao, Pei-Hung Lin, Murali Emani, Xipeng Shen:
Finding Reusable Machine Learning Components to Build Programming Language Processing Pipelines. ECSA (Tracks and Workshops) 2022: 402-417 - [c10]Zifan Nan, Mithil Dave, Xipeng Shen, Chunhua Liao, Tristan Vanderbruggen, Pei-Hung Lin, Murali Emani:
Interactive NLU-Powered Ontology-Based Workflow Synthesis for FAIR Support of HPC. HUST@SC 2022: 29-40 - [c9]Pei-Hung Lin, Chunhua Liao, Winson Chen, Tristan Vanderbruggen, Murali Emani, Hailu Xu:
Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study. TransAI 2022: 128-134 - [i3]Patrick J. Flynn, Tristan Vanderbruggen, Chunhua Liao, Pei-Hung Lin, Murali Emani, Xipeng Shen:
Finding Reusable Machine Learning Components to Build Programming Language Processing Pipelines. CoRR abs/2208.05596 (2022) - [i2]Pei-Hung Lin, Chunhua Liao, Winson Chen, Tristan Vanderbruggen, Murali Emani, Hailu Xu:
Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study. CoRR abs/2211.02092 (2022) - [i1]Sixing Yu, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Xipeng Shen, Ali Jannesari:
Towards Seamless Management of AI Models in High-Performance Computing. CoRR abs/2212.06352 (2022) - 2021
- [c8]Gaurav Verma, Murali Emani, Chunhua Liao, Pei-Hung Lin, Tristan Vanderbruggen, Xipeng Shen, Barbara M. Chapman:
HPCFAIR: Enabling FAIR AI for HPC Applications. MLHPC@SC 2021: 58-68 - [c7]Chunhua Liao, Pei-Hung Lin, Gaurav Verma, Tristan Vanderbruggen, Murali Emani, Zifan Nan, Xipeng Shen:
HPC Ontology: Towards a Unified Ontology for Managing Training Datasets and AI Models for High-Performance Computing. MLHPC@SC 2021: 69-80 - 2020
- [c6]Konstantinos Parasyris, Ignacio Laguna, Harshitha Menon, Markus Schordan, Daniel Osei-Kuffuor, Giorgis Georgakoudis, Michael O. Lam, Tristan Vanderbruggen:
HPC-MixPBench: An HPC Benchmark Suite for Mixed-Precision Analysis. IISWC 2020: 25-36 - [c5]Peter Pirkelbauer, Pei-Hung Lin, Tristan Vanderbruggen, Chunhua Liao:
XPlacer: Automatic Analysis of Data Access Patterns on Heterogeneous CPU/GPU Systems. IPDPS 2020: 997-1007
2010 – 2019
- 2019
- [c4]Michael O. Lam, Tristan Vanderbruggen, Harshitha Menon, Markus Schordan:
Tool Integration for Source-Level Mixed Precision. CORRECTNESS@SC 2019: 27-35 - 2017
- [c3]Robert Searles, Lifan Xu, William Killian, Tristan Vanderbruggen, Teague Forren, John Howe, Zachary Pearson, Corey Shannon, Joshua Simmons, John Cavazos:
Parallelization of Machine Learning Applied to Call Graphs of Binaries for Malware Detection. PDP 2017: 69-77 - [c2]Tristan Vanderbruggen, John Cavazos, Chunhua Liao, Daniel J. Quinlan:
Directive-based tile abstraction to distribute loops on accelerators. GPGPU@PPoPP 2017: 53-62 - 2014
- [c1]Tristan Vanderbruggen, John Cavazos:
Generating OpenCL C kernels from OpenACC. IWOCL 2014: 9:1-9:10
Coauthor Index
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