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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Optimizing Error-Bounded Lossy Compression for Scientific Data With Diverse Constraints

Vast volumes of data are produced by today's scientific simulations and advanced instruments. These data cannot be stored and transferred efficiently because of limited I/O bandwidth, network speed, and storage capacity. Error-bounded lossy compression can be an effective method for addressing these issues: not only can it significantly reduce data size, but it can also control the data distortion based on user-defined error bounds. In practice, many scientific applications have specific requirements or constraints for lossy compression, in order to guarantee that the reconstructed data are valid for post hoc analysis. For example, some datasets contain irrelevant data that should be isolated in particular and users often have intuition regarding value ranges, geospatial regions, and other data subsets that are crucial for subsequent analysis. Existing state-of-the-art error-bounded lossy compressors, however, do not consider these constraints during compression, resulting in inferior compression ratios with respect to user's post hoc analysis, due to the fact that the data itself provides little or no value for post hoc analysis. In this work we address this issue by proposing an optimized framework that can preserve diverse constraints during the error-bounded lossy compression, e.g., cleaning the irrelevant data, efficiently preserving different precision for multiple value intervals, and allowing users to set diverse precision over both regular and irregular regions. We perform our evaluation on a supercomputer with up to 2,100 cores. Experiments with six real-world applications show that our proposed diverse constraints based error-bounded lossy compressor can obtain a higher visual quality or data fidelity on reconstructed data with the same or even higher compression ratios compared with the traditional state-of-the-art compressor SZ. Furthermore, our experiments also demonstrate very good scalability in compression performance compared with the I/O throughput of the parallel file system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Stability Analysis of Inline ZFP Compression for Floating-Point Data in Iterative Methods

Currently, the dominating constraint in many high performance computing applications is data capacity and bandwidth, in both internode communications and even moreso in intranode data motion. A new approach to address this limitation is to make use of data compression in the form of a compressed data array. Storing data in a compressed data array and converting to standard IEEE-754 types as needed during a computation can reduce the pressure on bandwidth and storage. However, repeated conversions (lossy compression and decompression) introduce additional approximation errors, which need to be shown to not significantly affect the simulation results. Here, we extend recent work that analyzed the error of a single use of compression and decompression of the ZFP compressed data array representation to the case of time-stepping and iterative schemes, where an advancement operator is repeatedly applied in addition to the conversions. We show that the accumulated error for iterative methods involving fixed-point and time evolving iterations is bounded under standard constraints. An upper bound is established on the number of additional iterations required for the convergence of stationary fixed-point iterations. An additional analysis of traditional forward and backward error of stationary iterative methods using ZFP compressed arrays is also presented. The results of several 1D, 2D, and 3D test problems are provided to demonstrate the correctness of the theoretical bounds.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

A Survey on Error-Bounded Lossy Compression for Scientific Datasets

Error-bounded lossy compression has been effective in significantly reducing the data storage/transfer burden while preserving the reconstructed data fidelity very well. Many error-bounded lossy compressors have been developed for a wide range of parallel and distributed use cases for years. They are designed with distinct compression models and principles, such that each of them features particular pros and cons. In this article, we provide a comprehensive survey of emerging error-bounded lossy compression techniques. The key contribution is fourfold. (1) We summarize a novel taxonomy of lossy compression into six classic models. (2) We provide a comprehensive survey of 10 commonly used compression components/modules. (3) We summarized pros and cons of 47 state-of-the-art lossy compressors and present how state-of-the-art compressors are designed based on different compression techniques. (4) We discuss how customized compressors are designed for specific scientific applications and use-cases. We believe this survey is useful to multiple communities including scientific applications, high-performance computing, lossy compression, and big data.

Error-Bounded Lossy Compression↗

DOE OSTI2020

Phase Transitions in (Mg,Fe) 2 SiO 4 Olivine under Shock Compression

The response of forsterite, Mg 2 SiO 4 , under dynamic compression is of fundamental importance for understanding its phase transformations and high-pressure behavior. Here, we have carried out an in situ X-ray diffraction study of laser-shocked polycrystalline and single-crystal forsterite from 19 to 122 GPa using the Matter in Extreme Conditions end-station of the Linac Coherent Light Source. Under laser-based shock loading, forsterite does not transform to the high-pressure equilibrium assemblage of MgSiO 3 bridgmanite and MgO periclase, as has been suggested previously. Instead, we observe forsterite and forsterite III, a metastable polymorph of Mg 2 SiO 4 , coexisting in a mixed-phase region from 33 to 75 GPa for both polycrystalline and single-crystal samples. Densities inferred from X-ray diffraction are consistent with earlier gas-gun shock data. At higher stress, the response is sample-dependent. Polycrystalline samples undergo amorphization above 79 GPa. For [010]- and [001]-oriented crystals, a mixture of crystalline and amorphous material is observed to 108 GPa, whereas the [100]-oriented forsterite adopts an unknown phase at 122 GPa. The first two sharp diffraction peaks of amorphous Mg 2 SiO 4 show a similar trend with compression as those observed for MgSiO 3 in both recent static- and laser-driven shock experiments. This study provides new insight into the transformation of forsterite under nanosecond-duration shock loading. This work emphasizes the importance of formation of metastable phases along the Hugoniot and adds to evidence that the 300-K single-crystal diamond anvil cell experiments have relevance for understanding structures formed under shock compression. In particular, the metastable phase forsterite III has now been shown to form under dynamic compression from 10s to 100s of nanoseconds as well as under 300-K static compression. Upon compression to higher pressures, Mg 2 SiO 4 transforms to an amorphous phase. These results have broad relevance for understanding the behavior of silicates under dynamic compression.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Effect of Part Size, Displacement Rate, and Aging on Compressive Properties of Elastomeric Parts of Different Unit Cell Topologies Formed by Vat Photopolymerization Additive Manufacturing

Due to its ability to achieve geometric complexity at high resolution and low length scales, additive manufacturing (AM) has increasingly been used for fabricating cellular structures (e.g., foams and lattices) for a variety of applications. Specifically, elastomeric cellular structures offer tunability of compliance as well as energy absorption and dissipation characteristics. However, there are limited data available on compression properties for printed elastomeric cellular structures of different designs and testing parameters. In this work, the authors evaluate how unit cell topology, part size, the rate of compression, and aging affect the compressive response of polyurethane-based simple cubic, body-centered, and gyroid structures formed by vat photopolymerization AM. Finite element simulations incorporating hyperelastic and viscoelastic models were used to describe the data, and the simulated results compared well with the experimental data. Of the designs tested, only the parts with the body-centered unit cell exhibited differences in stress–strain responses at different part sizes. Of the compression rates tested, the highest displacement rate (1000 mm/min) often caused stiffer compressive behavior, indicating deviation from the quasi-static assumption and approaching the intermediate rate response. The cellular structures did not change in compression properties across five weeks of aging time, which is desirable for cushioning applications. This work advances knowledge on the structure–property relationships of printed elastomeric cellular materials, which will enable more predictable compressive properties that can be traced to specific unit cell designs.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Lithium plating induced degradation during fast charging of batteries subjected to compressive loading

Here we report the lithium plating associated capacity loss during fast charging of compressively loaded lithium-ion batteries (LIBs). The charging and discharging of LIB under compressive loading during service may affect the cell performance or initiate localized defects in the electrodes. Pouch cells of capacity 20 mAh were compressively loaded to nominal pressures of 0–440 kPa and subjected to 10 cycles of fast charging at 1 C and 4 C. Experimental results show that cells charged at 4 C-rate experienced significant capacity fade, and applying compressive loads exacerbated the capacity loss. The coulombic efficiency study shows that active lithium loss was higher for the initial cycles before gradually reducing to a minimal capacity loss for the tenth charging cycle. The cell voltage relaxation immediately after charging was monitored to identify the stripping of plated lithium after fast charging cycles and showed that the duration of lithium stripping was higher for cells under mechanical compressive loading. Scanning electron microscopy (SEM) and electron paramagnetic resonance spectroscopy (EPR) characterization of the anode showed significantly higher lithium deposits on the anodes charged at a 4 C rate under compressive loads. These results indicate that applied mechanical compression causes increased lithium plating during fast charging of batteries.

25 ENERGY STORAGE↗

DOE OSTI2025

Dynamic compression effects of H 2 ⁡O in a dynamic diamond anvil cell: Origin of metastable ice VII and its crystal growth kinetics

We report on the structural verification of metastable ice VII solidifying in the phase space of ice VI at 1.80 GPa at room temperature. Using time-resolved (TR) x-ray diffraction and TR ruby luminescence paired with high-speed microphotography utilizing a dynamic diamond anvil cell, an initial compression rate range from 0.12 to 95.84 GPa/s was explored. The solidification pressure of metastable ice VII has a potential sigmoidal dependence upon compression rate with a turnover compression rate of ∼80 GPa/s. The preferred crystallization of ice VII in the stability field of ice VI is due to the increased nucleation rate of ice VII over ice VI at 1.77 GPa that is driven by the surface energy difference between the liquid and solid phases along with the change in Gibbs free energy of solidification. The dynamic pressure-volume–compression behaviors of ice phases (VI and VII) show a lattice stiffening in both phases, especially during the compression loading. It is also found that the compression rate greatly affects the solid-solid phase transition between ice VI and VII but does not affect the liquid-solid transition between water and ice VI as much. Lastly, a third phase transition was found to occur after metastable ice VII transforms into high-density amorphous (HDA) ice, which could be a disordered hydrogen-bonded network configuration of ice VII forming out of HDA ice facilitated by the decoupling of the oxygen movement and reorientation of the H 2⁡ O molecule. These results demonstrate the complexity of a seemingly simple molecule H 2⁡ O, how it can readily change its static properties with the modification of (de)compression rate, and highlight the need to use multiple TR structural and spectroscopic probes at higher time resolutions to realize the most comprehensive understanding.

Chemical bonding↗

DOE OSTI2020

Ion versus Electron Heating in Compressively Driven Astrophysical Gyrokinetic Turbulence

The partition of irreversible heating between ions and electrons in compressively driven (but subsonic) collisionless turbulence is investigated by means of nonlinear hybrid gyrokinetic simulations. We derive a prescription for the ion-to-electron heating ratio Q i /Q e as a function of the compressive-to-Alfvénic driving power ratio P compr /P AW , of the ratio of ion thermal pressure to magnetic pressure β i , and of the ratio of ion-to-electron background temperatures T i /T e . It is shown that Q i /Q e is an increasing function of P compr /P AW . When the compressive driving is sufficiently large, Q i /Q e approaches ≃P compr /P AW . This indicates that, in turbulence with large compressive fluctuations, the partition of heating is decided at the injection scales, rather than at kinetic scales. Analysis of phase-space spectra shows that the energy transfer from inertial-range compressive fluctuations to sub-Larmor-scale kinetic Alfvén waves is absent for both low and high β i , meaning that the compressive driving is directly connected to the ion-entropy fluctuations, which are converted into ion thermal energy. This result suggests that preferential electron heating is a very special case requiring low βi and no, or weak, compressive driving. Our heating prescription has wide-ranging applications, including to the solar wind and to hot accretion disks such as M87 and Sgr A*.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

A General Framework for Error-controlled Unstructured Scientific Data Compression

Data compression plays a key role in reducing storage and I/O costs. Traditional lossy methods primarily target data on rectilinear grids and cannot leverage the spatial coherence in unstructured mesh data, leading to suboptimal compression ratios. We present a multi-component, error-bounded compression framework designed to enhance the compression of floating-point unstructured mesh data, which is common in scientific applications. Our approach involves interpolating mesh data onto a rectilinear grid and then separately compressing the grid interpolation and the interpolation residuals. This method is general, independent of mesh types and typologies, and can be seamlessly integrated with existing lossy compressors for improved performance. We evaluated our framework across twelve variables from two synthetic datasets and two real-world simulation datasets. The results indicate that the multi-component framework consistently outperforms state-of-the-art lossy compressors on unstructured data, achieving, on average, a 2.3 − 3.5× improvement in compression ratios, with error bounds ranging from 1 × 10 the −6 to 1×10−2. We further investigate impact of hyperparameters, such as grid spacing and error allocation, to deliver optimal compression ratios in diverse datasets.

Gong, Qian↗

DOE OSTI2022

CEAZ: Accelerating Parallel I/O Via Hardware-Algorithm Co-Designed Adaptive Lossy Compression

As supercomputers continue to grow to exa-scale, the amount of data that needs to be saved or transmitted is exploding. To this end, many previous works have studied using error-bounded lossy compressors to reduce the data size and improve the I/O performance. However, little work has been done for effectively offloading lossy compression onto FPGA-based SmartNICs to reduce the compression overhead. In this paper, we propose a hardware-algorithm co-design of efficient and adaptive lossy compressor for scientific data on FPGAs (called CEAZ) to accelerate parallel I/O. Our contribution is fourfold: (1) We propose an efficient Huffman coding approach that can adaptively update Huffman codewords online based on codewords generated offline (from a variety of representative scientific datasets). (2) We derive a theoretical analysis to support a precise control of compression ratio under an error-bounded compression mode, enabling accurate offline Huffman codewords generation. This also help us create a fixed-ratio compression mode for consistent throughput. (3) We develop an efficient compression pipeline by adopting cuSZ’s dual-quantization algorithm to our hardware use case. (4) We evaluate CEAC on five real-world datasets with both a single FPGA board and 256 nodes from Bridges2 supercomputer. Experiments show that CEAZ outperforms the second-best FPGA-based lossy compressor by 2× of throughput and 9.6× of compression ratio. It also improves MPI_File_write and MPI_Gather throughputs by up to 32.7× and 31.4×, respectively.

Zhang, Chengming↗

DOE OSTI2023

Black-box statistical prediction of lossy compression ratios for scientific data

Lossy compressors are increasingly adopted in scientific research, tackling volumes of data from experiments or parallel numerical simulations and facilitating data storage and movement. In contrast with the notion of entropy in lossless compression, no theoretical or data-based quantification of lossy compressibility exists for scientific data. Users rely on trial and error to assess lossy compression performance. As a strong data-driven effort toward quantifying lossy compressibility of scientific datasets, we provide a statistical framework to predict compression ratios of lossy compressors. Our method is a two-step framework where (i) compressor-agnostic predictors are computed and (ii) statistical prediction models relying on these predictors are trained on observed compression ratios. Proposed predictors exploit spatial correlations and notions of entropy and lossyness via the quantized entropy. We study 8+ compressors on 6 scientific datasets and achieve a median percentage prediction error less than 12%, which is substantially smaller than that of other methods while achieving at least a 8.8× speedup for searching for a specific compression ratio and 7.8× speedup for determining the best compressor out of a collection.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Chapter 22: Compressed Air Evaluation Protocol. The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures (September 2011 - August 2020)

Compressed-air systems are used widely throughout industry for many operations, including pneumatic tools, packaging and automation equipment, conveyors, and other industrial process operations. Compressed-air systems are defined as a group of subsystems composed of air compressors, air treatment equipment, controls, piping, pneumatic tools, pneumatically powered machinery, and process applications using compressed air. A compressed-air system has three primary functional subsystems: supply, distribution, and demand. Air compressors are the primary energy consumers in a compressed-air system and are the primary focus of this protocol. The two compressed-air energy efficiency measures specifically addressed in this protocol are: high-efficiency/variable speed drive (VSD) compressor replacing modulating, load/unload, or constant-speed compressor; compressed-air leak survey and repairs. This protocol provides direction on how to reliably verify savings from these two measures using a consistent approach for each.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Ta compressibility to 20+ Mbar

Developing techniques for experimentally constraining equation of state (EOS) models for important programmatic materials under extreme conditions is vital for advancing our modeling and predictive capabilities. Tantalum is a frequently used standard material for both calibration and testing, and this report describes our work to both measure Ta compressibility to very high pressures and densities using the Ramp Compression Equation of State platform on the National Ignition Facility (NIF). Using a series of seven shots, increasing in peak pressure with each shot, we have made absolute measurements of the compressibility of Ta along the ramp compression path up to 2.3 TPa. Previous experimental measurements constrained the cold compressibility up to ~400 GPa, and there is a spread in the EOS models above that pressure. To improve communication and collaboration between the experimental team and the EOS development group, these new data, along with other experimental and theoretical constraints, were used to develop a Ta equation of state table, M73000. This report first describes the experimental measurements made at the NIF, and then discusses the construction of the EOS model. The ramp compression data can be found in tabular form in Appendix A. Appendix B contains some additional experimental details. In Appendix C we include some additional details on the EOS modeling. At the end of this document, we have attached a detailed report on the NIF ramp compression platform itself and in the main text referenced specific sections for additional details.

36 MATERIALS SCIENCE↗

NASA NTRS1989

Compressible studies on dynamic stall

The purpose of this work is to investigate the effects of compressibility on the dynamic stall phenomenon by numerical simulation of the unsteady flow. The full two-dimensional unsteady compressible Navier-Stokes equations are solved for flows over oscillating airfoils and airfoils pitching rapidly to high angles of attack. The free-stream speeds vary from low subsonic with mild compressibility effects, to moderate subsonic where strong compressibility effects appear close to the leading edge at high angles of attack. An Alternating Direction Implicit scheme is implemented for the numerical solution with the viscous terms retained in both directions. The numerical results are compared with available experimental data for a Sikorsky airfoil for compressible high Reynolds number flows. There is good agreement between the computed and measured unsteady lift and pitching moment coefficient time histories. The computed high-speed subsonic unsteady results give a good picture of the entire flow field, and the dynamic stall progression in the compressible flow regime. It was observed that compressibility effects are more severe close to the leading edge at moderate angles of attack, and that the dynamic stall vortex appears at lower angles of attack as the free-stream speed increases.

Ekaterinaris, J. A.↗

NASA NTRS1990

Data compression applied to HHVT

A task order was written by the High Resolution, High Frame Rate Video Technology (HHVT) project engineers to study data compression techniques that could be applied to the HHVT system. Specifically, the goals of the HHVT data compression study are to accomplish the following: (1) Determine the downlink capabilities of the Space Shuttle and Space Station Freedom to support HHVT data (i.e., determine the maximum data rates and link availability); (2) Determine current and projected capabilities of high speed storage media to support HHVT data by determining their maximum data acquisition/transmission rates and volumes; (3) Identify which experiment in the HHVT Users' Requirement data base need data compression, based on the experiments' imaging requirements; (4) Select the best data compression technique for each of these users by identifying a technique that provides compression but minimizes distortion; and (5) Investigate state-of-the-art technologies for possible implementation of selected data compression techniques. Data compression will be needed because of the high data rates and larger volumes of data that will result from the use of digitized video onboard the Space Shuttle and Space Station Freedom.

Thompson, William K.↗

NASA NTRS1992

Locally adaptive vector quantization: Data compression with feature preservation

A study of a locally adaptive vector quantization (LAVQ) algorithm for data compression is presented. This algorithm provides high-speed one-pass compression and is fully adaptable to any data source and does not require a priori knowledge of the source statistics. Therefore, LAVQ is a universal data compression algorithm. The basic algorithm and several modifications to improve performance are discussed. These modifications are nonlinear quantization, coarse quantization of the codebook, and lossless compression of the output. Performance of LAVQ on various images using irreversible (lossy) coding is comparable to that of the Linde-Buzo-Gray algorithm, but LAVQ has a much higher speed; thus this algorithm has potential for real-time video compression. Unlike most other image compression algorithms, LAVQ preserves fine detail in images. LAVQ's performance as a lossless data compression algorithm is comparable to that of Lempel-Ziv-based algorithms, but LAVQ uses far less memory during the coding process.

Cheung, K. M.↗

NASA NTRS1994

Wavelet compression techniques for hyperspectral data

Hyperspectral sensors are electro-optic sensors which typically operate in visible and near infrared bands. Their characteristic property is the ability to resolve a relatively large number (i.e., tens to hundreds) of contiguous spectral bands to produce a detailed profile of the electromagnetic spectrum. In contrast, multispectral sensors measure relatively few non-contiguous spectral bands. Like multispectral sensors, hyperspectral sensors are often also imaging sensors, measuring spectra over an array of spatial resolution cells. The data produced may thus be viewed as a three dimensional array of samples in which two dimensions correspond to spatial position and the third to wavelength. Because they multiply the already large storage/transmission bandwidth requirements of conventional digital images, hyperspectral sensors generate formidable torrents of data. Their fine spectral resolution typically results in high redundancy in the spectral dimension, so that hyperspectral data sets are excellent candidates for compression. Although there have been a number of studies of compression algorithms for multispectral data, we are not aware of any published results for hyperspectral data. Three algorithms for hyperspectral data compression are compared. They were selected as representatives of three major approaches for extending conventional lossy image compression techniques to hyperspectral data. The simplest approach treats the data as an ensemble of images and compresses each image independently, ignoring the correlation between spectral bands. The second approach transforms the data to decorrelate the spectral bands, and then compresses the transformed data as a set of independent images. The third approach directly generalizes two-dimensional transform coding by applying a three-dimensional transform as part of the usual transform-quantize-entropy code procedure. The algorithms studied all use the discrete wavelet transform. In the first two cases, a wavelet transform coder was used for the two-dimensional compression. The third case used a three dimensional extension of this same algorithm.

Evans, Bruce↗

NASA NTRS1994

An adaptive technique to maximize lossless image data compression of satellite images

Data compression will pay an increasingly important role in the storage and transmission of image data within NASA science programs as the Earth Observing System comes into operation. It is important that the science data be preserved at the fidelity the instrument and the satellite communication systems were designed to produce. Lossless compression must therefore be applied, at least, to archive the processed instrument data. In this paper, we present an analysis of the performance of lossless compression techniques and develop an adaptive approach which applied image remapping, feature-based image segmentation to determine regions of similar entropy and high-order arithmetic coding to obtain significant improvements over the use of conventional compression techniques alone. Image remapping is used to transform the original image into a lower entropy state. Several techniques were tested on satellite images including differential pulse code modulation, bi-linear interpolation, and block-based linear predictive coding. The results of these experiments are discussed and trade-offs between computation requirements and entropy reductions are used to identify the optimum approach for a variety of satellite images. Further entropy reduction can be achieved by segmenting the image based on local entropy properties then applying a coding technique which maximizes compression for the region. Experimental results are presented showing the effect of different coding techniques for regions of different entropy. A rule-base is developed through which the technique giving the best compression is selected. The paper concludes that maximum compression can be achieved cost effectively and at acceptable performance rates with a combination of techniques which are selected based on image contextual information.

Stewart, Robert J.↗