Analysis of Scheduling Policies for Next-Generation Rabbit Architecture. Keith Bateman (Illinois Institute of Technology, Lawrence Livermore National Laboratory)
Analyzing Performance of File Aggregation in VELOC. Mikaila Gossman (Clemson University)
Analyzing Software Cache Configuration for In-line Data Compression. Sansriti Ranjan (Clemson University)
Application-Based Fault Tolerance for Numerical Linear Algebra at Large Scale. Daniel Alberto Torres Gonzalez (LIPN, CNRS UMR 7030; Institut Galilée - Université Paris 13)
cuSZ(+): Optimizing Error-Bounded Lossy Compression for Scientific Data on Modern GPUs. Jiannan Tian (Washington State University)
Datastore Design for Analysis of Police Broadcast Audio at Scale. Ayah Ahmad (University of California, Berkeley)
Delving Into the Abyss: A Distributed Decompression System for Indexing Compressed Repositories. Ryan Wong (Northwestern University, University of Chicago)
Efficient Parallel Algorithm for Shortest Path Updates in Dynamic Networks at Scale. Arindam Khanda (Missouri University of Science and Technology)
Embeddings Are All You Need: Transfer Learning in Convolutional Neural Networks Using Word Embeddings. Matt Baughman (University of Chicago, Globus)
In-Situ Data Reduction for AMR-Based Cosmology Simulations. Daoce Wang (Washington State University)
Increasing Mini-Batch Size While Preserving Accuracy for Distributed Deep Learning. Marie McCord (Middle Tennessee State University, Oak Ridge National Laboratory (ORNL))
Missing the Trees for the Branches: Graphical-Scripting Interaction with Large-Scale Calling Context Trees. Connor Scully-Allison (University of Arizona, Lawrence Livermore National Laboratory)
Mitigating the Metadata Mess: Autonomous Metadata Extraction Pipelines for Large-Scale Data Repositories. Matthew Chen (University of Illinois, University of Chicago)
One Fish, Two Fish: Choosing Optimal Edge Topologies for Real-Time Autonomous Fish Surveys. Jonathan Tsen (Fatec Shunji Nishimura, Brazil; University of Chicago)
Optimizing Deep Learning Material Interface Reconstruction. Valen Yamamoto (Lawrence Livermore National Laboratory)
Parallel Algorithms and Generalized Frameworks for Learning Large-Scale Bayesian Networks. Ankit Srivastava (Georgia Institute of Technology)
Performance Prediction of Large Data Transfers. Jason Cheung (Stony Brook University, Lawrence Berkeley National Laboratory (LBNL))
Productive, Performant, and Parallel Generic Lossy Data Compression with LibPressio. Victoriana Malvoso (Clemson University)
Regulating Traffic in a Crowded Cache: Overcoming the Container Explosion Problem. Kevin Gao (University of California, Berkeley)
SYMBIOMON: A High Performance, Composable Monitoring Service for Online Application Introspection and Adaptation. Srinivasan Ramesh (University of Oregon)
Toward Access Pattern Aware Checkpointing for Kokkos Applications. Nigel Tan (University of Tennessee, Knoxville)
Using IU Jetstream for OpenMP Offloading and OpenACC Testsuites. Nolan Baker (University of Delaware, Indiana University)
Yin and Yang: Balancing Cloud Computing and HTC Workloads. Zhuangwei Kang (Vanderbilt University)