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At least 1,531 records · Page 85

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DOE OSTI2020

Off-shell effective energy theory: A unified treatment of the Hubbard model from $\textit{d} = 1$ to $\textit{d = ∞}$

Here we propose an exact formalism, off-shell effective energy theory (OET), which provides a thermodynamic description of a generic quantum Hamiltonian. The OET is based on a partitioning of the Hamiltonian and a corresponding density matrix ansatz constructed from an off-shell extension of the equilibrium density matrix; and there are dual realizations based on a given partitioning. To approximate OET, we introduce the central point expansion (CPE), which is an expansion of the density matrix ansatz, and we renormalize the CPE using a standard expansion of the ground-state energy. In this work we showcase the OET for the one-band Hubbard model in $\textit{d}$ = 1 , 2, and $\infty$, using a partitioning between kinetic and potential energy, yielding two realizations denoted as $\mathcal{K}$ and $\mathcal{X}$. OET shows favorable agreement with exact or state-of-the-art results over all parameter space, and has a negligible computational cost. Physically, $\mathcal{K}$ describes the Fermi liquid, while $\mathcal{X}$ gives an analogous description of both the Luttinger liquid and the Mott insulator. Our approach should find broad applicability in lattice model Hamiltonians, in addition to real materials systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

Be 7 and Li 7 nuclei within the no-core shell model with continuum

The production of $^7Be$ and $^7Li$ nuclei plays an important role in primordial nucleosynthesis, nuclear astrophysics, and fusion energy generation. The $^3He(α,γ) ^7Be$ and $^3H(α,γ) 7Li$ radiative-capture processes are important to determine the $^7Li$ abundance in the early universe and to predict the correct fraction of $pp$ -chain branches resulting in $^7Be$ versus $^8B$ neutrinos. The $^6Li(p,γ) ^7Be$ has been investigated recently hinting at a possible cross section enhancement near the threshold. The $^6Li (n,^3H) ^4He$ process can be utilized for tritium breeding in machines dedicated to fusion energy generation through the deuteron-tritium reaction, and is a neutron cross section standard used in the measurement and evaluation of fission cross sections. In this work we study the properties of $^7Be$ and $^7Li$ within the no-core shell model with continuum (NCSMC) method, using chiral nucleon-nucleon interactions as the only input, and analyze all the binary mass partitions involved in the formation of these systems. The NCSMC is an ab initio method applicable to light nuclei that provides a unified description of bound and scattering states and thus is well suited to investigate systems with many resonances and pronounced clustering like $^7Be$ and $^7Li$. Our calculations reproduce all the experimentally known states of the two systems and provide predictions for several new resonances of both parities. Some of these new possible resonances are built on the ground states of $^6Li$ and $^6He$, and thus represent a robust prediction. We do not find any resonance in the $p + ^6Li$ mass partition near the threshold. On the other hand, in the $p + ^6He$ mass partition of $^7Li$ we observe an $S$ -wave resonance near the threshold producing a very pronounced peak in the calculated $S$ factor of the $^6He (p,γ)$ $^7Li$ radiative-capture reaction. While we do not find a resonance near the threshold in the $p + ^6Li$ channel, in the case of $^6He + p$ reaction a resonant S -wave state is predicted at a very low energy above the reaction threshold, which could be relevant for astrophysics and its implications should be investigated. We note though that this state lies above the three-body breakup threshold not included in our method and may be influenced by three-body continuum correlations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2018

Neutron-neutron angular correlations in spontaneous fission of Cf 252 and Pu 240

Background: Angular anisotropy has been observed between prompt neutrons emitted during the fission process. Such an anisotropy arises because the emitted neutrons are boosted along the direction of the parent fragment. Purpose: To measure the neutron-neutron angular correlations from the spontaneous fission of 252 Cf and 240 Pu oxide samples using a liquid scintillator array capable of pulse-shape discrimination. To compare these correlations to simulations combining the Monte Carlo radiation transport code MCNPX with the fission event generator FREYA. Method: Two different analysis methods were used to study the neutron-neutron correlations with varying energy thresholds. The first is based on setting a light output threshold while the second imposes a time-of-flight cutoff. The second method has the advantage of being truly detector independent. Results: The neutron-neutron correlation modeled by FREYA depends strongly on the sharing of the excitation energy between the two fragments. The measured asymmetry enabled us to adjust the FREYA parameter x in 240 Pu , which controls the energy partition between the fragments and is so far inaccessible in other measurements. The 240 Pu data in this analysis was the first available to quantify the energy partition for this isotope. The agreement between data and simulation is overall very good for 252 Cf ( sf ) and 240 Pu ( sf ). Conclusions: The asymmetry in the measured neutron-neutron angular distributions can be predicted by FREYA. The shape of the correlation function depends on how the excitation energy is partitioned between the two fission fragments. Lastly, experimental data suggest that the lighter fragment is disproportionately excited.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Scattering neutrinos, spin models, and permutations

We consider a class of Heisenberg all-to-all coupled spin models inspired by neutrino interactions in a supernova with N degrees of freedom. These models are characterized by a coupling matrix that is relatively simple in the sense that there are only a few, relative to N , nontrivial eigenvalues, in distinction to the classic Heisenberg spin-glass models, leading to distinct behavior in both the high-temperature and low-temperature regimes. When the momenta of the neutrinos are uniform and random in directions, we can calculate the large- N partition function for the quantum Heisenberg model. In particular, the high-temperature partition function predicts a non-Gaussian density of states, providing interesting counterexamples showing the limits of general theorems on the density of states for quantum spin models. We can repeat the same argument for classical Heisenberg models, also known as rotor models, and we find the high-temperature expansion is completely controlled by the eigenvalues of the coupling matrix, and again predicts non-Gaussian behavior for the density of states as long as the number of eigenvalues does not scale linearly with N . Indeed, we derive the amusing fact that these partition functions are essentially the generating function for counting permutations in the high-temperature regime. Finally, for the case relevant to neutrinos in a supernova, we identify the low-temperature phase as a unique state with the direction of the momenta of the neutrino dictating its coherent state in flavor-space, a state we dub the “flavor-momentum-locked” state. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

MassiveGNN: Efficient Training via Prefetching for Massively Connected Distributed Graphs

Graph Neural Networks (GNN) are indispensable in learning from graph-structured data, yet their rising computational costs, especially on massively connected graphs, pose significant challenges in terms of execution performance. To tackle this, distributed-memory solutions such as partitioning the graph to concurrently train multiple replicas of GNNs are in practice. However, approaches requiring a partitioned graph usually suffer from communication overhead and load imbalance, even under optimal partitioning and communication strategies due to irregularities in the neighborhood minibatch sampling. This paper proposes practical trade-offs for improving the sampling and communication overheads for representation learn- ing on distributed graphs (using popular GraphSAGE architecture) by developing a parameterized prefetch and eviction scheme on top of the state-of-the-art Amazon DistDGL distributed GNN framework, demonstrating about 15–40% improvement in end-to-end training performance on the NERSC Perlmutter supercomputer for various OGB datasets.

Machine Leanring, high performance comptuing, grap↗

DOE OSTI2024

BCSR on GPU: A Way Forward Extreme-scale Graph Processing on Accelerator-enabled Frontier Supercomputer

Handling large graphs in a distributed environment requires effective partitioning across processors and efficient management of local partitions. In 2D partitioning, local graphs often become too sparse, making memory-efficient data structures crucial. Using the Compressed Sparse Row (CSR) format wastes space, especially for > 83% of vertices with empty edges for the sparse graphs. This study explores bit-CSR (BCSR), a modified CSR representation, on GPUs to reduce memory usage in graph computations. We achieved 16.67% memory savings on a sparse rmat dataset with 268 million vertices and 357 million edges, without performance degradation, supported by both theoretical and experimental storage savings of 33%. However, we observed a 1.7× slowdown in degree lookup times due to bitwise operations on AMD CPUs. This analysis highlights the potential of BCSR on GPUs for improving Graph500 benchmark performance on GPU-accelerated systems, such as the Frontier supercomputer.

Sattar, Naw Safrin↗

DOE OSTI2021

Trust: Triangle Counting Reloaded on GPUs

Triangle counting is a building block for a wide range of graph applications. Here, traditional wisdom suggests that i) hashing is not suitable for triangle counting, ii) edge-centric triangle counting beats vertex-centric design, and iii) communication-free and workload balanced graph partitioning is a grand challenge for triangle counting. On the contrary, we advocate that i) hashing can help the key operations for scalable triangle counting on Graphics Processing Units (GPUs), i.e., list intersection and graph partitioning, ii) vertex-centric option reduces both hash table construction cost and memory consumption, which is limited on GPUs. In addition, iii) we exploit graph and workload collaborative, and hash-based 2D partitioning to scale vertex-centric triangle counting over 1,000 GPUs with sustained scalability. In this work, we present TRUST, which performs triangle counting with the hash operation and vertex-centric paradigm. To the best of our knowledge, TRUST is the first work that achieves over one trillion Traversed Edges Per Second (TEPS) rate for triangle counting.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Emergence of soil bacterial ecotypes along a climate gradient: Soil ecotypes along a climate gradient

The high diversity of soil bacteria is attributed to the spatial complexity of soil systems, where habitat heterogeneity promotes niche partitioning among bacterial taxa. This premise remains challenging to test, however, as it requires quantifying the traits of closely related soil bacteria and relating these traits to bacterial abundances and geographic distributions. In this work, we sought to investigate whether the widespread soil taxon Curtobacterium consists of multiple coexisting ecotypes with differential geographic distributions. We isolated Curtobacterium strains from six sites along a climate gradient and assayed four functional traits that may contribute to niche partitioning in leaf litter, the top layer of soil. Our results revealed that cultured isolates separated into fine-scale genetic clusters that reflected distinct suites of phenotypic traits, denoting the existence of multiple ecotypes. We then quantified the distribution of Curtobacterium by analysing metagenomic data collected across the gradient over 18 months. Six abundant ecotypes were observed with differential abundances along the gradient, suggesting fine-scale niche partitioning. However, we could not clearly explain observed geographic distributions of ecotypes by relating their traits to environmental variables. Thus, while we can resolve soil bacterial ecotypes, the traits delineating their distinct niches in the environment remain unclear.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Sulfur Solubility in Low Activity Waste Glass and its Correlation to Melter Tolerance

Hanford low-activity waste (LAW) glasses with high sulfur concentrations are subject to salt segregation in the melter. Segregated salts hinder melter operation by corroding melter components and potentially shortening the life of the melter. To better predict the point at which salt accumulates on the melt surface, the development of sulfate solubility models are needed. Using a sulfur saturation method, crucible scale melts for 13 LAW glasses with varying sulfur solubilities were conducted. The resulting salt and glass compositions were reported and the change in component partitioning following the saturation process was examined to better understand potential changes in overall glass composition. It was shown that both Cr2O3 and Cl experience significant losses post saturation, with ~28% of Cr2O3 partitioning into the salt phase and Cl primarily volatilizing out of the melt (~23% partitioned to salt and ~40% lost as offgas). Due to the consistency in compositional changes between glasses these patterns can be accounted for during model development. Measured sulfur solubilities were also compared to previously reported melter tolerance data. It was found that crucible sulfur solubility ranged from 0.947 to 2.137 wt% SO3. The correlation between the crucible solubility and melter tolerance was high ( = 0.94), with the data showing a constant offset of -0.328 ± 0.021 wt% SO3. These results suggest that crucible scale sulfate solubility data can be used to accurately predict SO3 tolerance in the melter feed.

Skidmore, Chloe H.↗

DOE OSTI2019

Role of Caulobacter Cell Surface Structures in Colonization of the Air-Liquid Interface

In aquatic environments, Caulobacter spp. can be found at the boundary between liquid and air known as the neuston. I report an approach to study temporal features of Caulobacter crescentus colonization and pellicle biofilm development at the air-liquid interface and have defined the role of cell surface structures in this process. At this interface, C. crescentus initially forms a monolayer of cells bearing a surface adhesin known as the holdfast. When excised from the liquid surface, this monolayer strongly adheres to glass. The monolayer subsequently develops into a three-dimensional structure that is highly enriched in clusters of stalked cells known as rosettes. As this pellicle film matures, it becomes more cohesive and less adherent to a glass surface. A mutant strain lacking a flagellum does not efficiently reach the surface, and strains lacking type IV pili exhibit defects in organization of the three-dimensional pellicle. Strains unable to synthesize the holdfast fail to accumulate at the boundary between air and liquid and do not form a pellicle. Phase-contrast images support a model whereby the holdfast functions to trap C. crescentus cells at the air-liquid boundary. Unlike the holdfast, neither the flagellum nor type IV pili are required for C. crescentus to partition to the air-liquid interface. While it is well established that the holdfast enables adherence to solid surfaces, this study provides evidence that the holdfast has physicochemical properties that allow partitioning of nonmotile mother cells to the air-liquid interface and facilitate colonization of this microenvironment. In aquatic environments, the boundary at the air interface is often highly enriched with nutrients and oxygen. Colonization of this niche likely confers a significant fitness advantage in many cases. This study provides evidence that the cell surface adhesin known as a holdfast enables Caulobacter crescentus to partition to and colonize the air-liquid interface. Additional surface structures, including the flagellum and type IV pili, are important determinants of colonization and biofilm formation at this boundary. Considering that holdfast-like adhesins are broadly conserved in Caulobacter spp. and other members of the diverse class Alphaproteobacteria , these surface structures may function broadly to facilitate colonization of air-liquid boundaries in a range of ecological contexts, including freshwater, marine, and soil ecosystems

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

ECO2N V2.0

ECO2N V2.0 is a fluid property module for the TOUGH2 simulator (Version 2.1) that was designed for applications to geologic sequestration of CO2 in saline aquifers and enhanced geothermal reservoirs. ECO2N V2.0 is an enhanced version of the previous ECO2N V1.0 module (Pruess, 2005). It expands the temperature range up to about 300oC whereas V1.0 can only be used for temperatures below about 110oC. V2.0 includes a comprehensive description of the thermodynamic and thermophysical properties of H2O - NaCl - CO2 mixtures, that reproduces fluid properties largely within experimental error for the temperature, pressure and salinity conditions 10 °C < T < 300 °C, P < 600 bar, and salinity up to halite saturation. This includes density, viscosity, and specific enthalpy of fluid phases as functions of temperature, pressure, and composition, as well as partitioning of mass components H2O, NaCl and CO2 among the different phases. In particular, V2.0 accounts for the effects of water on the thermophysical properties of the CO2-rich phase, which was ignored in V1.0, using a model consistent with the solubility models developed by Spycher and Pruess (2005, 2010). In terms of solubility models, V2.0 uses the same model for partitioning of mass components among the different phases (Spycher and Pruess, 2005) as V1.0 for the low temperature range (<99oC) but uses a new model (Spycher and Pruess, 2010) for the high temperature range (>109oC). In the transition range (99-109oC), a smooth interpolation is applied to estimate the partitioning as a function of the temperature. Flow processes can be modeled isothermally or non-isothermally, and phase conditions represented may include a single (aqueous or CO2-rich) phase, as well as two-phase (brine-CO2) mixtures. Fluid phases may appear or disappear in the course of a simulation, and solid salt may precipitate or dissolve. Note that the model cannot be applied to subcritical conditions that involves both liquid and gaseous CO2 unless thermol process is ignored (i.e.,isothermal run). For those cases, a user may use the fluid property module ECO2M (Pruess, 2011) instead.

Pan, Lehua↗

DOE OSTI2020

Sphynx

Sphynx is a software library for parallel graph partitioning and load balancing. It partitions a set of vertices in a graph such that the vertex parts are balanced, and the edge cut is approximately minimized. The primary use case is to partition a computational graph into smaller tasks that can be assigned to processors (cores) for efficient parallel computing. Sphynx is based on the Trilinos scientific computing toolkit so can run on both multi-CPU and multi-GPU systems. SAND2020-12183 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Boman, Erik↗

DOE OSTI2016

An Improved Convective Ice Parameterization for the NASA GISS Global Climate Model and Impacts on Cloud Ice Simulation

Partitioning of convective ice into precipitating and detrained condensate presents a challenge for GCMs since partitioning depends on the strength and microphysics of the convective updraft. It is an important issue because detrainment of ice from updrafts influences the development of stratiform anvils, impacts radiation, and can affect GCM climate sensitivity. Recent studies have shown that the CMIP5 configurations of the Goddard Institute for Space Studies (GISS) GCM simulated upper-tropospheric ice water content (IWC) that exceeded an estimated upper bound by a factor of 2. Partly in response to this bias, a new GCM parameterization of convective cloud ice has been developed that incorporates new ice particle fall speeds and convective outflow particle size distributions (PSDs) from the NASA African Monsoon Multidisciplinary Analyses (NAMMA), NASA Tropical Composition, Cloud and Climate Coupling (TC4), DOE ARM–NASA Midlatitude Continental Convective Clouds Experiment (MC3E), and DOE ARM Small Particles in Cirrus (SPARTICUS) field campaigns. The new parameterization assumes a normalized gamma PSD with two novel developments: no explicit assumption for particle habit in the calculation of mass distributions, and a formulation for translating ice particle fall speeds as a function of maximum diameter into fall speeds as a function of melted-equivalent diameter. Two parameters (particle volume– and projected area–weighted equivalent diameter) are diagnosed as a function of temperature and IWC in the convective plume, and these parameters constrain the shape and scale of the normalized gamma PSD. The diagnosed fall speeds and PSDs are combined with the GCM’s parameterized convective updraft vertical velocity to partition convective updraft condensate into precipitating and detrained components. A 5-yr prescribed sea surface temperature GCM simulation shows a 30%–50% decrease in upper-tropospheric deep convective IWC, bringing the tropical and global mean ice water path into closer agreement with CloudSat best estimates.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Cyclic dynamics of misfires and partial burns in a dilute spark-ignition engine

Here, this study investigates the cyclic dynamics of cumulative heat release data past the edge of stability in a dilute spark-ignition engine. Emphasis is placed on analyzing the cyclic dynamics near the dilute limit where partial burns and misfires are frequent. These events are often followed by a higher-energy cycle due to the feed-forward mechanism present in the residual gases. These patterns are deterministic and increase the coefficient of variation to undesirable levels. Symbol sequence analysis was used to investigate the cyclic dynamics of these low–high patterns. The heat release was partitioned on an energy basis to give physical meaning to each partition and each sequence created when analyzing the symbol sequence results. This partitioning method provided insight into the differences in the dynamics when operating in the misfire or partial burn regime. These differences could impact the control method used.

42 ENGINEERING↗

DOE OSTI2026

Off-gas capture: a promising strategy for removal and recovery of toxic bioproducts in aerobic fermentation

In many bioprocesses, maximum achievable titers are limited below economically viable levels by toxic accumulation of the primary end-product. To combat end-product inhibition, a variety of in situ product removal technologies have been developed to selectively remove or partition toxic bioproducts, thereby prolonging fermentation and improving overall process efficiency. Use of an in situ organic overlay to partition toxic hydrophobic products is a commonly employed approach, but this technique occupies valuable space in the fermentor, imposes replacement costs for unrecovered solvent, and increases downstream separation due to formation of stable emulsions. In addition, for many volatile hydrophobic products produced under aerobic conditions—including medium-chain alcohols, esters, monoterpenes, and other aviation fuel precursors—a significant fraction of the product is volatilized to the fermentor off-gas and must be recovered separately to maximize product yield. To address these challenges, we explore the viability of leveraging existing aeration energy to fully strip and recover volatile products from the fermentor off-gas. We compare two strategies of in situ product removal—liquid–liquid extraction and direct recovery from fermentation off-gas—for the production and recovery of intermediates used to generate isoprene and DMCO (1,4-dimethylcyclooctane), a high-performance jet fuel. We evaluate product toxicity, solvent toxicity, solvent partitioning, and the impact of aeration and internal overlay configurations on product volatilization rates. We then optimize product recovery from fermentor off-gas via condensation in chilled solvent, achieving 84% capture efficiency. In addition to greatly simplifying downstream processing, relying on aeration for product volatilization in the absence of an internal overlay enables continuous removal of toxic fermentation products up to maximum isoprenol titers of 20.4 g/L, the highest reported to date.

isoprene↗

DOE OSTI2022

Profile Images and Annotations for Vehicle Re-identification Algorithms (PRIMAVERA)

This dataset contains 636,246 profile images of vehicles representing 13,963 unique vehicles. The data was collected by a set of roadside sensors over the course of three years. Each time a vehicle passed by one of the sensors, a series of images was collected. The images were processed to detect and localize each vehicle, and a license plate reader collocated with the sensor was used to provide a unique ID for the vehicle. Actual license plate numbers have been obfuscated by replacing with an arbitrary numerical ID for each vehicle. After localizing the vehicle in each image, the original RGB image was rotated, scaled, and shifted to produce a new RGB image of size 234x234 pixels such that the outermost two wheels are located at predetermined pixel locations in the image. In this way, all vehicle images are aligned to one another. This registration process occasionally results in a portion of certain vehicles being cutoff at the edges of the image. The dataset has been partitioned into two sets called training and validation. The two partitions no common vehicles, i.e., a vehicle present in one partition is guaranteed not to be present in the other. In this way, an algorithm can be validated against a set of new vehicles that were not seen during the training process. The training set contains 543,926 images from 64,440 vehicle passes representing 11,918 unique vehicles, while the validation set contains 92,320 images from 10,991 vehicle passes representing 2,045 unique vehicles. Vehicle images are organized by directories corresponding to unique vehicles. The file naming scheme is as follows: veh_{vehID}_tr_{passID}_{frameID}_{elevation}_{timeofday}.jpg where {vehID} is the vehicle ID (unique across the entire dataset), {passID} is an identifier for each tracked vehicle pass (unique across the entire dataset), {frameID} is the index of the frame within the given vehicle pass starting at 0, {elevation} is a two-letter string indicating whether the sensor was elevated (el) or at ground-level (gl), and {timeofday} is a two-letter string indicating whether the image was captured during daytime (dt) or nighttime (nt).

image↗

DOE OSTI2020

Detecting multiple communities using quantum annealing on the D-Wave system

A very important problem in combinatorial optimization is the partitioning of a network into communities of densely connected nodes; where the connectivity between nodes inside a particular community is large compared to the connectivity between nodes belonging to different ones. This problem is known as community detection, and has become very important in various fields of science including chemistry, biology and social sciences. The problem of community detection is a twofold problem that consists of determining the number of communities and, at the same time, finding those communities. This drastically increases the solution space for heuristics to work on, compared to traditional graph partitioning problems. In many of the scientific domains in which graphs are used, there is the need to have the ability to partition a graph into communities with the “highest quality” possible since the presence of even small isolated communities can become crucial to explain a particular phenomenon. We have explored community detection using the power of quantum annealers, and in particular the D-Wave 2X and 2000Q machines. It turns out that the problem of detecting at most two communities naturally fits into the architecture of a quantum annealer with almost no need of reformulation. This paper addresses a systematic study of detecting two or more communities in a network using a quantum annealer.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

FRIEDA: Flexible Robust Intelligent Elastic Data Management Framework

Scientific applications are increasingly using cloud resources for their data analysis workflows. However, managing data effectively and efficiently over these cloud resources is challenging due to the myriad storage choices with different performance, cost trade-offs, complex application choices and complexity associated with elasticity, failure rates in these environments. The different data access patterns for data-intensive scientific applications require a more flexible and robust data management solution than the ones currently in existence. FRIEDA is a Flexible Robust Intelligent Elastic Data Management framework that employs a range of data management strategies in cloud environments. FRIEDA can manage storage and data lifecycle of applications in cloud environments. There are four different stages in the data management lifecycle of FRIEDA – (i) storage planning, (ii) provisioning and preparation, (iii) data placement, and (iv) execution. FRIEDA defines a data control plane and an execution plane. The data control plane defines the data partition and distribution strategy, whereas the execution plane manages the execution of the application using a master-worker paradigm. FRIEDA also provides different data management strategies, either to partition the data in real-time, or predetermine the data partitions prior to application execution.

97 MATHEMATICS AND COMPUTING↗