Analogues of the 3 x + 1 Problem in Polynomial Rings of Characteristic 2. - Daniel Nichols (Exp. Math., 2018)

MagmaDNN: Towards High-Performance Data Analytics and Machine Learning for Data-Driven Scientific Computing. - Daniel Nichols; Nathalie-Sofia Tomov; Frank Betancourt; Stanimire Tomov; Kwai Wong; Jack J. Dongarra (ISC Workshops, 2019)

openDIEL: A Parallel Workflow Engine and Data Analytics Framework. - Frank Betancourt; Kwai Wong; Efosa Asemota; Quindell Marshall; Daniel Nichols; Stanimire Tomov (PEARC, 2019)

MagmaDNN: Accelerated Deep Learning Using MAGMA. - Daniel Nichols; Kwai Wong; Stanimire Tomov; Lucien Ng; Sihan Chen; Alex Gessinger (PEARC, 2019)

Integrating Deep Learning in Domain Sciences at Exascale. - Rick Archibald; Edmond Chow; Eduardo F. D'Azevedo; Jack J. Dongarra; Markus Eisenbach 002; Rocco Febbo; Florent Lopez; Daniel Nichols; Stanimire Tomov; Kwai Wong; Junqi Yin (SMC, 2020)

How to Train Your Neural Network: A Comparative Evaluation. - Shu-Huai Lin; Daniel Nichols; Siddharth Singh; Abhinav Bhatele (CoRR, 2021)

Resource Utilization Aware Job Scheduling to Mitigate Performance Variability. - Daniel Nichols; Aniruddha Marathe; Kathleen Shoga; Todd Gamblin; Abhinav Bhatele (IPDPS, 2022)

Porting a Computational Fluid Dynamics Code with AMR to Large-scale GPU Platforms. - Joshua Hoke Davis; Justin Shafner; Daniel Nichols; Nathan Grube; Pino Martin; Abhinav Bhatele (IPDPS, 2023)

Modeling Parallel Programs using Large Language Models. - Daniel Nichols; Aniruddha Marathe; Harshitha Menon; Todd Gamblin; Abhinav Bhatele (CoRR, 2023)

Relative Performance Prediction Using Few-Shot Learning. - Arunavo Dey; Aakash Dhakal; Tanzima Z. Islam; Jae-Seung Yeom; Tapasya Patki; Daniel Nichols; Alexander Movsesyan; Abhinav Bhatele (COMPSAC, 2024)

Can Large Language Models Write Parallel Code? - Daniel Nichols; Joshua Hoke Davis; Zhaojun Xie; Arjun Rajaram; Abhinav Bhatele (HPDC, 2024)

Predicting Cross-Architecture Performance of Parallel Programs. - Daniel Nichols; Alexander Movsesyan; Jae-Seung Yeom; Abhik Sarkar; Daniel Milroy; Tapasya Patki; Abhinav Bhatele (IPDPS, 2024)

Learning to Predict and Improve Build Successes in Package Ecosystems. - Harshitha Menon; Daniel Nichols; Abhinav Bhatele; Todd Gamblin (MSR, 2024)

A Probabilistic Approach To Selecting Build Configurations in Package Managers. - Daniel Nichols; Harshitha Menon; Todd Gamblin; Abhinav Bhatele (SC, 2024)

HPC-Coder: Modeling Parallel Programs using Large Language Models. - Daniel Nichols; Aniruddha Marathe; Harshitha Menon; Todd Gamblin; Abhinav Bhatele (ISC, 2024)

Automated Programmatic Performance Analysis of Parallel Programs. - Onur Cankur; Aditya Tomar; Daniel Nichols; Connor Scully-Allison; Katherine E. Isaacs; Abhinav Bhatele (CoRR, 2024)

Performance-Aligned LLMs for Generating Fast Code. - Daniel Nichols; Pranav Polasam; Harshitha Menon; Aniruddha Marathe; Todd Gamblin; Abhinav Bhatele (CoRR, 2024)

The Shortcomings of Code LLMs in Modeling Code Properties. - Srivishnu Pyda; Daniel Nichols; Abhinav Bhatele (LLM4Code@ICSE, 2025)

HPC-Coder-v2: Studying Code LLMs Across Low-Resource Parallel Languages. - Aman Chaturvedi; Daniel Nichols; Siddharth Singh; Abhinav Bhatele (ISC, 2025)

Leveraging AI for Productive and Trustworthy HPC Software: Challenges and Research Directions. - Keita Teranishi; Harshitha Menon; William F. Godoy; Prasanna Balaprakash; David Bau; Tal Ben-Nun; Abhinav Bhatele; Franz Franchetti; Michael E. Franusich; Todd Gamblin; Giorgis Georgakoudis; Tom Goldstein; et al. (CoRR, 2025)

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks. - Joshua Hoke Davis; Daniel Nichols; Ishan Khillan; Abhinav Bhatele (CoRR, 2025)

Modeling Code: Is Text All You Need? - Daniel Nichols; Konstantinos Parasyris; Harshitha Menon; Brian R. Bartoldson; Giorgis Georgakoudis; Tal Ben-Nun; Abhinav Bhatele (CoRR, 2025)