Global MINMAX Interframe Bit Allocation for Embedded Video Coding. - Michael F. Ringenburg; Richard E. Ladner; Eve A. Riskin (Data Compression Conference, 2004)

Group Testing for Video Compression. - Gidon Shavit; Michael F. Ringenburg; Jeff West; Richard E. Ladner; Eve A. Riskin (Data Compression Conference, 2004)

Preventing format-string attacks via automatic and efficient dynamic checking. - Michael F. Ringenburg; Dan Grossman (CCS, 2005)

AtomCaml: first-class atomicity via rollback. - Michael F. Ringenburg; Dan Grossman (ICFP, 2005)

Types for describing coordinated data structures. - Michael F. Ringenburg; Dan Grossman (TLDI, 2005)

MultiStage: A MINMAX Bit Allocation Algorithm for Video Coders. - Neva Cherniavsky; Gidon Shavit; Michael F. Ringenburg; Richard E. Ladner; Eve A. Riskin (IEEE Trans. Circuits Syst. Video Technol., 2007)

Dynamic Analyses of Result Quality in Energy-Aware Approximate Programs. - Michael F. Ringenburg (2014)

Monitoring and Debugging the Quality of Results in Approximate Programs. - Michael F. Ringenburg; Adrian Sampson; Isaac Ackerman; Luis Ceze; Dan Grossman (ASPLOS, 2015)

Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies. - Alex Gittens; Aditya Devarakonda; Evan Racah; Michael F. Ringenburg; Lisa Gerhardt; Jey Kottalam; Jialin Liu 002; Kristyn J. Maschhoff; Shane Canon; Jatin Chhugani; Pramod Sharma; Jiyan Yang; et al. (IEEE BigData, 2016)

A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark. - Alex Gittens; Jey Kottalam; Jiyan Yang; Michael F. Ringenburg; Jatin Chhugani; Evan Racah; Mohitdeep Singh; Yushu Yao; Curt Fischer; Oliver Rübel; Benjamin P. Bowen; Norman G. Lewis; et al. (IPDPS Workshops, 2016)

Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies. - Alex Gittens; Aditya Devarakonda; Evan Racah; Michael F. Ringenburg; Lisa Gerhardt; Jey Kottalam; Jialin Liu 002; Kristyn J. Maschhoff; Shane Canon; Jatin Chhugani; Pramod Sharma; Jiyan Yang; et al. (CoRR, 2016)

Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist. - Alex Gittens; Kai Rothauge; Shusen Wang; Michael W. Mahoney; Lisa Gerhardt; Prabhat; Jey Kottalam; Michael F. Ringenburg; Kristyn J. Maschhoff (KDD, 2018)

CosmoFlow: using deep learning to learn the universe at scale. - Amrita Mathuriya; Deborah Bard; Peter Mendygral; Lawrence Meadows; James Arnemann; Lei Shao; Siyu He; Tuomas Kärnä; Diana Moise; Simon J. Pennycook; Kristyn J. Maschhoff; Jason Sewall; et al. (SC, 2018)

Alchemist: An Apache Spark ⇔ MPI interface. - Alex Gittens; Kai Rothauge; Shusen Wang; Michael W. Mahoney; Jey Kottalam; Lisa Gerhardt; Prabhat; Michael F. Ringenburg; Kristyn J. Maschhoff (Concurr. Comput. Pract. Exp., 2019)

Running Alchemist on Cray XC and CS Series Supercomputers: Dask and PySpark Interfaces, Deployment Options, and Data Transfer Times. - Kai Rothauge; Haripriya Ayyalasomayajula; Kristyn J. Maschhoff; Michael F. Ringenburg; Michael W. Mahoney (CoRR, 2019)

Scalable reinforcement learning on Cray XC. - Ananda V. Kommaraju; Kristyn J. Maschhoff; Michael F. Ringenburg; Benjamin Robbins (Concurr. Comput. Pract. Exp., 2020)