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09/07/2023
SRN-SZ: Deep Leaning-Based Scientific Error-bounded Lossy Compression with Super-resolution Neural Networks
The fast growth of computational power and scales of modern super-comput...
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07/13/2023
AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications
As supercomputers advance towards exascale capabilities, computational i...
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04/06/2023
Mutual Interference Mitigation for MIMO-FMCW Automotive Radar
This paper considers mutual interference mitigation among automotive rad...
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01/05/2023
TAC+: Drastically Optimizing Error-Bounded Lossy Compression for 3D AMR Simulations
Today's scientific simulations require a significant reduction of data v...
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11/01/2022
SOLAR: A Highly Optimized Data Loading Framework for Distributed Training of CNN-based Scientific Surrogates
CNN-based surrogates have become prevalent in scientific applications to...
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06/29/2022
Accelerating Parallel Write via Deeply Integrating Predictive Lossy Compression with HDF5
Lossy compression is one of the most efficient solutions to reduce stora...
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04/01/2022
TAC: Optimizing Error-Bounded Lossy Compression for Three-Dimensional Adaptive Mesh Refinement Simulations
Today's scientific simulations require a significant reduction of data v...
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11/18/2021
Improving Prediction-Based Lossy Compression Dramatically Via Ratio-Quality Modeling
Error-bounded lossy compression is one of the most effective techniques ...
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11/18/2021
COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression
Training wide and deep neural networks (DNNs) require large amounts of s...
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06/24/2021
CEAZ: Accelerating Parallel I/O via Hardware-Algorithm Co-Design of Efficient and Adaptive Lossy Compression
As supercomputers continue to grow to exascale, the amount of data that ...
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05/27/2021
Characterizing Impacts of Storage Faults on HPC Applications: A Methodology and Insights
In recent years, the increasing complexity in scientific simulations and...
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05/27/2021
cuSZ(x): Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs
Error-bounded lossy compression is a critical technique for significantl...
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05/25/2021
Exploring Autoencoder-Based Error-Bounded Compression for Scientific Data
Error-bounded lossy compression is becoming an indispensable technique f...
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04/01/2021
Adaptive Configuration of In Situ Lossy Compression for Cosmology Simulations via Fine-Grained Rate-Quality Modeling
Extreme-scale cosmological simulations have been widely used by today's ...
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11/18/2020
A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression
Deep neural networks (DNNs) are becoming increasingly deeper, wider, and...
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07/19/2020
cuSZ: An Efficient GPU-Based Error-Bounded Lossy Compression Framework for Scientific Data
Error-bounded lossy compression is a state-of-the-art data reduction tec...
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04/01/2020
Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological Simulations
To help understand our universe better, researchers and scientists curre...
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05/05/2019
Optimization-based Decentralized Coded Caching for Files and Caches with Arbitrary Size
Existing decentralized coded caching solutions cannot guarantee small lo...
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01/26/2019