High-precision numerical data from computer simulations, observations, and experiments is often represented in floating point and can easily reach terabytes to petabytes of storage.
Topic: Data Compression
LLNL is participating in the 34th annual Supercomputing Conference (SC22), which will be held both virtually and in Dallas on November 13–18, 2022.
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Data Compression | Data Movement and Memory | Data Science | Debugging and Correctness | Emerging Architectures | Events | HPC Architectures | HPC Systems and Software | Hybrid/Heterogeneous | Outreach | Performance, Portability, and Productivity | Programming Languages and Models | Quantum Computing | Resource and Workflow Management | Software Build and Installation
The new oneAPI Center of Excellence will involve the Center for Applied Scientific Computing and accelerate ZFP compression software to advance exascale computing.
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zfp is an open-source C/C++ library for compressed floating-point and integer arrays that support high throughput read and write random access.
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The Department of Energy's Office of Science interviewed LLNL computer scientist Peter Lindstrom about his work since receiving the 2011 Early Career Award.
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An LLNL-led effort in data compression was one of nine projects recently funded by the DOE for research aimed at shrinking the amount of data needed to advance scientific discovery.
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fpzip is a library for lossless or lossy compression of multidimensional floating-point arrays. It was primarily designed for lossless compression.
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Highlights include the directorate's annual external review, machine learning for ALE simulations, CFD modeling for low-carbon solutions, seismic modeling, and an in-line floating point compression tool.
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hzip 1.0.1 is a C++ library for lossless compression of structured and unstructured meshes composed of cells with hypercube topology.
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