Daniel Nichols

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 15

Top Topics

Orthogonal Polynomials

Intracranial Aneurysms

Top Venues

Publications

Onur Cankur, Aditya Tomar, Daniel Nichols, Connor Scully-Allison, Katherine E. Isaacs, Abhinav Bhatele
Automated Programmatic Performance Analysis of Parallel Programs. CoRR (2024)
Daniel Nichols, Joshua Hoke Davis, Zhaojun Xie, Arjun Rajaram, Abhinav Bhatele
Can Large Language Models Write Parallel Code? CoRR (2024)
Harshitha Menon, Daniel Nichols, Abhinav Bhatele, Todd Gamblin
Learning to Predict and Improve Build Successes in Package Ecosystems. MSR (2024)
Daniel Nichols, Pranav Polasam, Harshitha Menon, Aniruddha Marathe, Todd Gamblin, Abhinav Bhatele
Performance-Aligned LLMs for Generating Fast Code. CoRR (2024)
Daniel Nichols, Alexander Movsesyan, Jae-Seung Yeom, Abhik Sarkar, Daniel Milroy, Tapasya Patki, Abhinav Bhatele
Predicting Cross-Architecture Performance of Parallel Programs. IPDPS (2024)
Joshua Hoke Davis, Justin Shafner, Daniel Nichols, Nathan Grube, Pino Martin, Abhinav Bhatele
Porting a Computational Fluid Dynamics Code with AMR to Large-scale GPU Platforms. IPDPS (2023)
Daniel Nichols, Aniruddha Marathe, Harshitha Menon, Todd Gamblin, Abhinav Bhatele
Modeling Parallel Programs using Large Language Models. CoRR (2023)
Daniel Nichols, Aniruddha Marathe, Kathleen Shoga, Todd Gamblin, Abhinav Bhatele
Resource Utilization Aware Job Scheduling to Mitigate Performance Variability. IPDPS (2022)
Shu-Huai Lin, Daniel Nichols, Siddharth Singh, Abhinav Bhatele
How to Train Your Neural Network: A Comparative Evaluation. CoRR (2021)
Rick Archibald, Edmond Chow, Eduardo F. D'Azevedo, Jack J. Dongarra, Markus Eisenbach, Rocco Febbo, Florent Lopez, Daniel Nichols, Stanimire Tomov, Kwai Wong, Junqi Yin
Integrating Deep Learning in Domain Sciences at Exascale. CoRR (2020)
Rick Archibald, Edmond Chow, Eduardo F. D'Azevedo, Jack J. Dongarra, Markus Eisenbach, Rocco Febbo, Florent Lopez, Daniel Nichols, Stanimire Tomov, Kwai Wong, Junqi Yin
Integrating Deep Learning in Domain Sciences at Exascale. SMC (2020)
Frank Betancourt, Kwai Wong, Efosa Asemota, Quindell Marshall, Daniel Nichols, Stanimire Tomov
openDIEL: A Parallel Workflow Engine and Data Analytics Framework. PEARC (2019)
Daniel Nichols, Kwai Wong, Stanimire Tomov, Lucien Ng, Sihan Chen, Alex Gessinger
MagmaDNN: Accelerated Deep Learning Using MAGMA. PEARC (2019)
Daniel Nichols, Nathalie-Sofia Tomov, Frank Betancourt, Stanimire Tomov, Kwai Wong, Jack J. Dongarra
MagmaDNN: Towards High-Performance Data Analytics and Machine Learning for Data-Driven Scientific Computing. ISC Workshops (2019)
Daniel Nichols
Analogues of the 3 x + 1 Problem in Polynomial Rings of Characteristic 2. Exp. Math. 27 (1) (2018)