Posts by Collection

Graphics Basics

Notes on computer graphics basics

Probability and Random Variables

Notes on computer probability and random variables.

Reproducing Kernel Hilbert Spaces

Notes on reproducing kernel hilbert spaces and applications in machine learning

Statistical Pattern Recognition

Notes on statistical pattern recognition and machine learning foundations.

MagmaDNN: High Performance Deep Learning

A High Performance Deep Learning Package

MagmaDNN: Towards High-Performance Data Analytics and Machine Learning for Data-Driven Scientific Computing

D. Nichols, N.-S. Tomov, F. Betancourt, S. Tomov, K. Wong, en J. Dongarra, "MagmaDNN: Towards High-Performance Data Analytics and Machine Learning for Data-Driven Scientific Computing", ISC. 2019.

MagmaDNN: Accelerated Deep Learning Using Magma

Daniel Nichols, Kwai Wong, Stan Tomov, Lucien Ng, Sihan Chen, and Alex Gessinger. 2019. MagmaDNN: Accelerated Deep Learning Using MAGMA. In Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) (PEARC 19). ACM, New York, NY, USA, Article 71, 6 pages. DOI: https://doi.org/10.1145/3332186.3333047

openDIEL: A Parallel Workflow Engine And Data Analytics Framework

Frank Betancourt, Kwai Wong, Efosa Asemota, Quindell Marshall, Daniel Nichols, and Stanimire Tomov. 2019. openDIEL: A Parallel Workflow Engine and Data Analytics Framework. In Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning) (PEARC 19). ACM, New York, NY, USA, Article 20, 7 pages. DOI: https://doi.org/10.1145/3332186.3333051

Integrating Deep Learning in Domain Sciences at Exascale

R. Archibald, E. Chow, E. D’Azevedo, J. Dongarra, M. Eisenbach, R. Febbo, F. Lopez, D. Nichols, S. Tomov, K. Wong, and J. Yin, SMC 2020, (2020)

Resource Utilization Aware Job Scheduling to Mitigate Performance Variability

D. Nichols, A. Marathe, K. Shoga, T. Gamblin, A. Bhatele, “Resource Utilization Aware Job Scheduling to Mitigate Performance Variability”, International Parallel & Distributed Processing Symposium (IPDPS). 2022.

A Survey and Empirical Evaluation of Parallel Deep Learning Frameworks

D. Nichols, S. Singh, S.-H. Lin, en A. Bhatele, “A Survey and Empirical Evaluation of Parallel Deep Learning Frameworks”, arXiv [cs.LG]. 2022.

Teaching Assistant

Course, University of Tennessee, Department of Computer Science, 2019

Teaching assistant for Computer Science 140: Data Structures and Algorithms I.