Qing Liu

Liu, Qing (2022). Locality-based transfer learning on compression autoencoder for efficient scientific data lossy compression. Journal of Network and Computer Applications,

Liu, Qing (2021). MGARD+: Optimizing Multilevel Methods for Error-bounded Scientific Data Reduction. IEEE Transactions on Computers,

Liu, Qing (2021). The Exascale Framework for High Fidelity coupled Simulations (EFFIS): Enabling whole device modeling in fusion science. The International Journal of High Performance Computing Applications,

Liu, Qing (2021). High-Ratio Lossy Compression: Exploring the Autoencoder to Compress Scientific Data. IEEE Transactions on Big Data,

Liu, Qing (2020). ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management. SoftwareX,

Liu, Qing (2020). Enhancing Proportional IO Sharing on Containerized Big Data File Systems. IEEE Transactions on Computers,

Liu, Qing (2020). Estimating Lossy Compressibility of Scientific Data Using Deep Neural Networks. IEEE Letters of the Computer Society,

Liu, Qing (2020). Fine-grained resource provisioning and task scheduling for heterogeneous applications in distributed green clouds. IEEE/CAA Journal of Automatica Sinica,

Liu, Qing (2019). An Embedded Feature Selection Method for Imbalanced Data Classification. IEEE/CAA Journal of Automatica Sinica,

Liu, Qing (2019). Bi-objective Task Scheduling for Distributed Green Data Centers. IEEE Transactions on Automation Science and Engineering,

Liu, Qing (2019). Can I/O Variability be Reduced on QoS-less HPC Storage Systems?. IEEE Transactions on Computers,

Liu, Qing (2019). Compression Ratio Modeling and Estimation Across Error Bounds for Lossy Compression. IEEE Transactions on Parallel and Distributed Systems,

Liu, Qing (2019). Time-Dependent Cloud Workload Prediction via Multi-Task Learning. IEEE Robotics and Automation Letters,

Liu, Qing (2018). DuoModel: Leveraging Reduced Model for Data Reduction and Re-computation on HPC Storage. IEEE Letters of Computer Society,

Liu, Qing (2018). Write Energy Reduction for PCM via Pumping Efficiency Improvement. ACM Transactions on Storage,

Error-controlled, Progressive, and Adaptable Retrieval of Scientific Data with Multilevel Decomposition
32nd ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, November 2021

Reducing the Training Overhead of the HPC Compression Autoencoder via Dataset Proportioning
15th IEEE International Conference on Networking, Architecture, and Storage , October (4th Quarter/Autumn) 2021

Accelerating Multigrid-based Hierarchical ScientificData Refactoring on GPUs
35th IEEE International Parallel and Distributed Processing Symposium, May 2021

zMesh: Exploring Application Characteristics to Improve Lossy Compression Ratio for Adaptive Mesh Refinement
35th IEEE International Parallel and Distributed Processing Symposium, May 2021

A Comprehensive Study of In-Memory Computing on Large HPC Systems
40th IEEE International Conference on Distributed Computing Systems (ICDCS), December 2020

Taming I/O Variation on QoS-less HPC Storage: What Can Applications do?
31st ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, November 2020

Exploring Transfer Learning to Reduce Training Overhead of HPC Data in Machine Learning
IEEE International Conference on Networking, Architecture, and Storage, 2019

Identifying Latent Reduced Models to Precondition Lossy Compression
33rd IEEE International Parallel and Distributed Processing Symposium, 2019

Load-aware Elastic Data Reduction and Re-computation for Adaptive Mesh Refinement
IEEE International Conference on Networking, Architecture, and Storage , 2019

A View from ORNL: Scientific Data Research Opportunities in the Big Data Age
International Conference on Distributed Computing Systems, 2018

Understanding and Modeling Lossy Compression Schemes on HPC Scientific Data
IEEE International Parallel & Distributed Processing Symposium, 2018

Canopus: A Paradigm Shift Towards Elastic Extreme-Scale Data Analytics on HPC Storage
IEEE International Conference on Cluster Computing (CLUSTER), September 2017

Canopus: Enabling Extreme-Scale Data Analytics on Big HPC Storage via Progressive Refactoring
USENIX Hotstorage, July (3rd Quarter/Summer) 2017

Computing Just What You Need: Online Data Analysis and Reduction at Extreme Scales
EuroPar'17, August 2017

DFS-Container: Achieving Containerized Block I/O for Distributed File Systems
ACM SOCC'17, September 2017

Exacution: Enhancing Scientific Data Management for Exascale
IEEE ICDCS, June 2017

SELF: A High Performance and Bandwidth Efficient Approach to Exploiting Die-stacked DRAM as Part of Memory
IEEE MASCOT, September 2017

StoreRush: An Application-Level Approach to Harvesting Idle Storage in a Best Effort Environment
International Conference on Computational Science, June 2017

TGE: Machine Learning Based Task Graph Embedding for Large-scale Topology Mapping
IEEE International Conference on Cluster Computing (CLUSTER),, September 2017