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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Optimizing Error-Bounded Lossy Compression for Scientific Data on GPUs

Error-bounded lossy compression is a critical technique for significantly reducing scientific data volumes. With ever-emerging heterogeneous high-performance computing (HPC) architecture, GPU-accelerated error-bounded compressors (such as CUSZ and cuZFP) have been developed. However, they suffer from either low performance or low compression ratios. To this end, we propose CUSZ+ to target both high compression ratios and throughputs. We identify that data sparsity and data smoothness are key factors for high compression throughputs. Our key contributions in this work are fourfold: (1) We propose an efficient compression workflow to adaptively perform run-length encoding and/or variable-length encoding. (2) We derive Lorenzo reconstruction in decompression as multidimensional partial-sum computation and propose a fine-grained Lorenzo reconstruction algorithm for GPU architectures. (3) We carefully optimize each of CUSZ kernels by leveraging state-of-the-art CUDA parallel primitives. (4) We evaluate CUSZ+ using seven real-world HPC application datasets on V100 and A100 GPUs. Experiments show CUSZ+ improves the compression throughputs and ratios by up to 18.4x and 5.3x, respectively, over CUSZ on the tested datasets.

Tian, Jiannan↗

DOE OSTI2023

Algebraic Compression of Free Fermionic Quantum Circuits: Particle Creation, Arbitrary Lattices and Controlled Evolution

In this work [1], we extend our recently introduced algebraic circuit compression algorithms [2], [3] that can compress time evolution circuits of free fermionic Hamiltonians on an n-site 1D chain, equation H(t)=∑i=1n-1 (hi(t)cici+1+pi(t)cici+1)+h.c., 1 equation in three significant ways: (1) we allow for compression of free fermionic Hamiltonians on arbitrary lattices, (2) we incorporate particle creation/annihilation operators into the compression schemes, and (3) we extend the compression scheme to controlled time-evolution operators. We illustrate the effectiveness of our approach by simulating the dynamics of a fermion on a 4× 4 2D square lattice on ibmq_washington, both in the presence and absence of disorder. Our quantum simulations show a remarkably high fidelity which is enabled through the compressed circuits.

Kökcü, Efekan↗

DOE OSTI2020

TuckerMPI: A Parallel C++/MPI Software Package for Large-scale Data Compression via the Tucker Tensor Decomposition

With this study, our goal is compression of massive-scale grid-structured data, such as the multi-terabyte output of a high-fidelity computational simulation. For such data sets, we have developed a new software package called TuckerMPI, a parallel C++/MPI software package for compressing distributed data. The approach is based on treating the data as a tensor, i.e., a multidimensional array, and computing its truncated Tucker decomposition, a higher-order analogue to the truncated singular value decomposition of a matrix. The result is a low-rank approximation of the original tensor-structured data. Compression efficiency is achieved by detecting latent global structure within the data, which we contrast to most compression methods that are focused on local structure. In this work, we describe TuckerMPI, our implementation of the truncated Tucker decomposition, including details of the data distribution and in-memory layouts, the parallel and serial implementations of the key kernels, and analysis of the storage, communication, and computational costs. We test the software on 4.5 and 6.7 terabyte data sets distributed across 100 s of nodes (1,000 s of MPI processes), achieving compression ratios between 100 and 200,000×, which equates to 99--99.999% compression (depending on the desired accuracy) in substantially less time than it would take to even read the same dataset from a parallel file system. Moreover, we show that our method also allows for reconstruction of partial or down-sampled data on a single node, without a parallel computer so long as the reconstructed portion is small enough to fit on a single machine, e.g., in the instance of reconstructing/visualizing a single down-sampled time step or computing summary statistics. The code is available at https://gitlab.com/tensors/TuckerMPI.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications

As supercomputers advance towards exascale capabilities, computational intensity increases significantly, and the volume of data requiring storage and transmission experiences exponential growth. Adaptive Mesh Refinement (AMR) has emerged as an effective solution to address these two challenges. Concurrently, error-bounded lossy compression is recognized as one of the most efficient approaches to tackle the latter issue. Despite their respective advantages, few attempts have been made to investigate how AMR and error-bounded lossy compression can function together. To this end, this study presents a novel in-situ lossy compression framework that employs the HDF5 filter to improve both I/O costs and boost compression quality for AMR applications. We implement our solution into the AMReX framework and evaluate on two real-world AMR applications, Nyx and WarpX, on the Summit supercomputer. Experiments with 512 cores demonstrate that AMRIC improves the compression ratio by 81X and the I/O performance by 39X over AMReX's original compression solution.

Wang, Daoce↗

DOE OSTI2023

AEflow (Autoencoder fluid flow compression network) [SWR-22-29]

As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.

King, Ryan↗

DOE OSTI2022

Toward Quantity-of-Interest Preserving Lossy Compression for Scientific Data

Today's scientific simulations and instruments are producing a large amount of data, leading to difficulties in storing, transmitting, and analyzing these data. While error-controlled lossy compressors are effective in significantly reducing data volumes and efficiently developing databases for multiple scientific applications, they mainly support error controls on raw data, which leaves a significant gap between the data and user's downstream analysis. This may cause unqualified uncertainties in the outcomes of the analysis, a.k.a quantities of interest (QoIs), which are the major concerns of users in adopting lossy compression in practice. In this paper, we propose rigorous mathematical theories to preserve four families of QoIs that are widely used in scientific analysis during lossy compression along with practical implementations. Specifically, we first develop the error control theory for univariate QoIs which are essential for computing physical properties such as kinetic energy, followed by multivariate QoIs that are more commonly used in real-world applications. The proposed method is integrated into a state-of-the-art compression framework in a modular fashion, which could easily adapt to new QoIs and new compression algorithms. Experiments on real-world datasets demonstrate that the proposed method provides faithful error control on important QoIs including kinetic energy, regional average, and isosurface without trials and errors, while offering compression ratios that are up to 4x of the compression ratios provided by state-of-the-art compressors.

Jiao, Pu↗

DOE OSTI2026

Scientific Data Compression for Large Scale Computational Fluid Dynamics (CFD) Simulations

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and General Electric (GE) investigated methods for reducing the size of large computational fluid dynamics (CFD) simulation datasets using scientific data compression techniques. The work focused on adapting the MultiGrid Adaptive Reduction of Data (MGARD) compression framework and integrating it with high-performance I/O and visualization tools used in CFD workflows. MGARD uses hierarchical multilevel decomposition to enable error-controlled compression of floating-point scientific data while preserving quantities of interest. During the project, MGARD compression was integrated with the ADIOS I/O framework and visualization tools such as ParaView to enable efficient storage, transfer, and analysis of simulation data. The collaboration also explored approaches for improving compression performance for CFD data defined on unstructured meshes. Results demonstrate that scientific data compression can significantly reduce storage requirements and improve data management for large-scale CFD simulations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Small-amplitude Compressible Magnetohydrodynamic Turbulence Modulated by Collisionless Damping in Earth’s Magnetosheath: Observation Matches Theory

Plasma turbulence is a ubiquitous dynamical process that transfers energy across many spatial and temporal scales and affects energetic particle transport. Recent advances in the understanding of compressible magnetohydrodynamic (MHD) turbulence demonstrate the important role of damping in shaping energy distributions on small scales, yet its observational evidence is still lacking. This study provides the first observational evidence of substantial collisionless damping (CD) modulation on the small-amplitude compressible MHD turbulence cascade in Earth’s magnetosheath using four Cluster spacecraft. Based on an improved compressible MHD decomposition algorithm, turbulence is decomposed into three eigenmodes: incompressible Alfvén modes and compressible slow and fast (magnetosonic) modes. Our observations demonstrate that CD enhances the anisotropy of compressible MHD modes because CD has a strong dependence on wave propagation angle. The wavenumber distributions of slow modes are mainly stretched perpendicular to the background magnetic field (B 0 ) and weakly modulated by CD. In contrast, fast modes are subjected to a more significant CD modulation. Fast modes exhibit a weak, scale-independent anisotropy above the CD truncation scale. Below the CD truncation scale, the anisotropy of fast modes enhances as wavenumbers increase. As a result, fast-mode fractions in the total energy of compressible modes decrease with the increase of perpendicular wavenumber (to B 0 ) or wave propagation angle. Our findings reveal how the turbulence cascade is shaped by CD and its consequences for anisotropies in the space environment.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

Impact of Effective Compression Ratio on Gasoline-Diesel Dual-Fuel Combustion in a Heavy-Duty Engine Using Variable Valve Actuation

Dual-fuel combustion using port-injected gasoline with a direct diesel injection has been shown to achieve low-temperature combustion with moderate peak pressure rise rates, low engine-out soot and NOx emissions, and high indicated thermal efficiency. A key requirement for extending high-load operation is moderating the reactivity of the premixed charge prior to the diesel injection. Reducing compression ratio, in conjunction with a higher expansion ratio using alternative valve timings, decreases compressed charge reactivity while maintain a high expansion ratio for maximum work extraction. Experimental testing was conducted on a 13L multi-cylinder heavy-duty diesel engine modified to operate dual-fuel combustion with port gasoline injection to supplement the direct diesel injection. The engine employs intake variable valve actuation (VVA) for early (EIVC) or late (LIVC) intake valve closing to yield reduced effective compression ratio. Testing was conducted at a mid-load operating condition using a gasoline-diesel dual-fuel operating strategy. The impact on dual-fuel engine performance and emissions with respect to varying effective compression ratio is quantified within this study. As effective compression ratio is reduced, overall massflow through the engine decreases, yielding both higher gas exchange efficiencies and increased heat transfer losses. With constant combustion phasing gasoline/diesel fueling fraction, and NOx emissions held constant, overall brake thermal efficiency remains relatively constant across effective compression ratios.

Ickes, Andrew↗

DOE OSTI2016

Finite Element Simulation of Compression Molding of Woven Fabric Carbon Fiber/Epoxy Composites: Part I Material Model Development

Woven fabric carbon fiber/epoxy composites made through compression molding are one of the promising choices of material for the vehicle light-weighting strategy. Previous studies have shown that the processing conditions can have substantial influence on the performance of this type of the material. Therefore the optimization of the compression molding process is of great importance to the manufacturing practice. An efficient way to achieve the optimized design of this process would be through conducting finite element (FE) simulations of compression molding for woven fabric carbon fiber/epoxy composites. However, performing such simulation remains a challenging task for FE as multiple types of physics are involved during the compression molding process, including the epoxy resin curing and the complex mechanical behavior of woven fabric structure. In the present study, the FE simulation of the compression molding process of resin based woven fabric composites at continuum level is conducted, which is enabled by the implementation of an integrated material modeling methodology in LS-Dyna. Specifically, the chemo-thermo-mechanical problem of compression molding is solved through the coupling of three material models, i.e., one thermal model for temperature history in the resin, one mechanical model to update the curing-dependent properties of the resin and another mechanical model to simulate the behavior of the woven fabric composites. Preliminary simulations of the carbon fiber/epoxy woven fabric composites in LS-Dyna are presented as a demonstration, while validations and models with real part geometry are planned in the future work.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Modeling and Simulation of Compression Molding Process for Sheet Molding Compound (SMC) of Chopped Carbon Fiber Composites

Compression molded SMC composed of chopped carbon fiber and resin polymer which balances the mechanical performance and manufacturing cost presents a promising solution for vehicle lightweight strategy. However, the performance of the SMC molded parts highly depends on the compression molding process and local microstructure, which greatly increases the cost for the part level performance testing and elongates the design cycle. ICME (Integrated Computational Material Engineering) approaches are thus necessary tools to reduce the number of experiments required during part design and speed up the deployment of the SMC materials. As the fundamental stage of the ICME workflow, commercial software packages for SMC compression molding exist yet remain not fully validated especially for chopped fiber systems. In this study, SMC plaques are prepared through compression molding process. The corresponding simulation models are built in Autodesk Moldflow with the same part geometry and processing conditions as in the molding tests. The output variables of the compression molding simulations, including press force history and fiber orientation of the part, are compared with experimental data. Influence of the processing conditions to the fiber orientation of the SMC plaque is also discussed. It is found that generally Autodesk Moldflow can achieve a good simulation of the compression molding process for chopped carbon fiber SMC, yet quantitative discrepancies still remain between predicted variables and experimental results.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Bit Grooming: statistically accurate precision-preserving quantization with compression, evaluated in the netCDF Operators (NCO, v4.4.8+)

Abstract. Geoscientific models and measurements generate false precision (scientifically meaningless data bits) that wastes storage space. False precision can mislead (by implying noise is signal) and be scientifically pointless, especially for measurements. By contrast, lossy compression can be both economical (save space) and heuristic (clarify data limitations) without compromising the scientific integrity of data. Data quantization can thus be appropriate regardless of whether space limitations are a concern. We introduce, implement, and characterize a new lossy compression scheme suitable for IEEE floating-point data. Our new Bit Grooming algorithm alternately shaves (to zero) and sets (to one) the least significant bits of consecutive values to preserve a desired precision. This is a symmetric, two-sided variant of an algorithm sometimes called Bit Shaving that quantizes values solely by zeroing bits. Our variation eliminates the artificial low bias produced by always zeroing bits, and makes Bit Grooming more suitable for arrays and multi-dimensional fields whose mean statistics are important. Bit Grooming relies on standard lossless compression to achieve the actual reduction in storage space, so we tested Bit Grooming by applying the DEFLATE compression algorithm to bit-groomed and full-precision climate data stored in netCDF3, netCDF4, HDF4, and HDF5 formats. Bit Grooming reduces the storage space required by initially uncompressed and compressed climate data by 25–80 and 5–65 %, respectively, for single-precision values (the most common case for climate data) quantized to retain 1–5 decimal digits of precision. The potential reduction is greater for double-precision datasets. When used aggressively (i.e., preserving only 1–2 digits), Bit Grooming produces storage reductions comparable to other quantization techniques such as Linear Packing. Unlike Linear Packing, whose guaranteed precision rapidly degrades within the relatively narrow dynamic range of values that it can compress, Bit Grooming guarantees the specified precision throughout the full floating-point range. Data quantization by Bit Grooming is irreversible (i.e., lossy) yet transparent, meaning that no extra processing is required by data users/readers. Hence Bit Grooming can easily reduce data storage volume without sacrificing scientific precision or imposing extra burdens on users.

58 GEOSCIENCES↗

NASA NTRS1973

A zero-error operational video data compression system

A data compression system has been operating since February 1972, using ATS spin-scan cloud cover data. With the launch of ITOS 3 in October 1972, this data compression system has become the only source of near-realtime very high resolution radiometer image data at the data processing facility. The VHRR image data are compressed and transmitted over a 50 kilobit per second wideband ground link. The goal of the data compression experiment was to send data quantized to six bits at twice the rate possible when no compression is used, while maintaining zero error between the transmitted and reconstructed data. All objectives of the data compression experiment were met, and thus a capability of doubling the data throughput of the system has been achieved.

Kutz, R. L.↗

NASA NTRS1974

Compressive strength of fiber reinforced composite materials

Results of an experimental and analytical investigation of the compressive strength of unidirectional boron-epoxy composite material are presented. Observation of fiber coordinates in a boron-epoxy composite indicates that the fibers contain initial curvature. Combined axial compression and torsion tests were conducted on boron-epoxy tubes, and it was shown that the shear modulus is a function of axial compressive stress. An analytical model which includes initial curvature in the fibers and permits an estimate of the effect of curvature on compressive strength is proposed. Two modes of failure which may result from the application of axial compressive stress are analyzed, delamination and shear instability. Based on tests and analysis, failure of boron-epoxy under axial compressive load is due to shear instability.

Davis, J. G., Jr.↗

NASA NTRS1975

Compressive strength of fiber-reinforced composite materials

Results of an experimental and analytical investigation of the compressive strength of unidirectional boron-epoxy composite material are presented. Observation of fiber coordinates in a boron-epoxy composite indicates that the fibers contain initial curvature. Combined axial compression and torsion tests were conducted on boron-epoxy tubes and it was shown that the shear modulus is a function of axial compressive stress. An analytical model which includes initial curvature in the fibers and permits an estimate of the effect of curvature on compressive strength is proposed. Two modes of failure which may result from the application of axial compressive stress are analyzed - delamination and shear instability. Based on tests and analysis, failure of boron-epoxy under axial compressive load is due to shear instability.

Davis, J. G., Jr.↗

NASA NTRS1978

Comparison of video fields and frames for transform compression

Because of the interlaced television scan, the two fields that form an interlaced video frame are generated 1/60 of a second apart. If the two fields are compressed independently, the correlation between adjacent lines is unused. The transmission rate can be reduced by using a field memory to form an interlaced frame. Four test images were processed as fields and as interlaced frames, using both theoretical and experimental compression designs. For comparable mean-square error and subjective appearance, field compression requires about one-half bit per sample more than frame compression. However, the overall transmission rate - the number of bits per image times the number of images per second - is more meaningful than the number of bits per sample. When transform compression at low transmission rates merges the adjacent lines, frame compression becomes similar to field repeating, and the memory can be reduced.

Jones, H. W., Jr.↗

NASA NTRS1981

Compression testing of graphite/epoxy composite materials

Three methods for compression testing coupons of filament-reinforced polymer-matrix composite materials are evaluated, to identify the sensitivity of the test techniques to laminate, specimen, and test parameters. A 'wedge-grip' compression fixture, a face-supported compression fixture, and an end-loaded coupon fixture are described. Specimens of 12.5-, 25-, and 50-mm widths, 8-, 16-, and 24-ply thicknesses, and of various fiber orientations were used to test the 'wedge-grip' compression fixture and the face-supported fixture; the end-loaded coupon fixture was tested using 16-ply specimens. Compressive strain-stress, strength, and modulus data obtained with the fixtures and evaluations showing the effects of all the test parameters are presented. One of the conclusions asserts that the 'wedge-grip' compression fixture provides good stress-strain data to failure for unidirectional and quasi-isotropic laminates.

Clark, R. K.↗

NASA NTRS1983

Tensile and Compressive Constitutive Response of 316 Stainless Steel at Elevated Temperatures

Creep rate in compression is lower by factors of 2 to 10 than in tension if the microstructure of the two specimens is the same and are tested at equal temperatures and equal but opposite stresses. Such behavior is characteristic for monotonic creep and conditions involving cyclic creep. In the latter case creep rate in both tension and compression progressively increases from cycle to cycle, rendering questionable the possibility of expressing a time stabilized constitutive relationship. The difference in creep rates in tension and compression is considerably reduced if the tension specimen is first subjected to cycles of tensile creep (reversed by compressive plasticity), while the compression specimen is first subjected to cycles of compressive creep (reversed by tensile plasticity). In both cases, the test temperature is the same and the stresses are equal and opposite. Such reduction is a reflection of differences in microstructure of the specimens resulting from different prior mechanical history.

Manson, S. S.↗