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At least 19 records

Compiling software for a hierarchical distributed processing system

Compiling software for a hierarchical distributed processing system including providing to one or more compiling nodes software to be compiled, wherein at least a portion of the software to be compiled is to be executed by one or more nodes; compiling, by the compiling node, the software; maintaining, by the compiling node, any compiled software to be executed on the compiling node; selecting, by the compiling node, one or more nodes in a next tier of the hierarchy of the distributed processing system in dependence upon whether any compiled software is for the selected node or the selected node's descendents; sending to the selected node only the compiled software to be executed by the selected node or selected node's descendent.

97 MATHEMATICS AND COMPUTING↗

GALACTIC CHEMICAL EVOLUTION: THE IMPACT OF THE {sup 13}C-POCKET STRUCTURE ON THE s -PROCESS DISTRIBUTION

The solar s -process abundances have been analyzed in the framework of a Galactic Chemical Evolution (GCE) model. The aim of this work is to implement the study by Bisterzo et al., who investigated the effect of one of the major uncertainties of asymptotic giant branch (AGB) yields, the internal structure of the {sup 13}C pocket. We present GCE predictions of s -process elements computed with additional tests in the light of suggestions provided in recent publications. The analysis is extended to different metallicities, by comparing GCE results and updated spectroscopic observations of unevolved field stars. We verify that the GCE predictions obtained with different tests may represent, on average, the evolution of selected neutron-capture elements in the Galaxy. The impact of an additional weak s -process contribution from fast-rotating massive stars is also explored.

79 ASTRONOMY AND ASTROPHYSICS↗

Petascale Application of a Coupled CPU-GPU Algorithm for Simulation and Analysis of Multiphase Flow Solutions in Porous Medium Systems, In: 2014 IEEE 28th International Parallel and Distributed Processing Symposium

Large-scale simulation can provide a wide range of information needed to develop and validate theoretical models for multiphase flow in porous medium systems. In this paper, we consider a coupled solution in which a multiphase flow simulator is coupled to an analysis approach used to extract the interfacial geometries as the flow evolves. This has been implemented using MPI to target heterogeneous nodes equipped with GPUs. The GPUs evolve the multiphase flow solution using the lattice Boltzmann method while the CPUs compute up scaled measures of the morphology and topology of the phase distributions and their rate of evolution. Our approach is demonstrated to scale to 4,096 GPUs and 65,536 CPU cores to achieve a maximum performance of 244,754 million-lattice-node updates per second (MLUPS) in double precision execution on Titan. In turn, this approach increases the size of systems that can be considered by an order of magnitude compared with previous work and enables detailed in situ tracking of averaged flow quantities at temporal resolutions that were previously impossible. Furthermore, it virtually eliminates the need for post-processing and intensive I/O and mitigates the potential loss of data associated with node failures.

Computer Science↗

A Step towards Energy Efficient Computing: Redesigning a Hydrodynamic Application on CPU-GPU, In: 2014 IEEE 28th International Parallel and Distributed Processing Symposium

Power and energy consumption are becoming an increasing concern in high performance computing. Compared to multi-core CPUs, GPUs have a much better performance per watt. In this paper we discuss efforts to redesign the most computation intensive parts of BLAST, an application that solves the equations for compressible hydrodynamics with high order finite elements, using GPUs BLAST, Dobrev. In order to exploit the hardware parallelism of GPUs and achieve high performance, we implemented custom linear algebra kernels. We intensively optimized our CUDA kernels by exploiting the memory hierarchy, which exceed the vendor's library routines substantially in performance. We proposed an auto tuning technique to adapt our CUDA kernels to the orders of the finite element method. Compared to a previous base implementation, our redesign and optimization lowered the energy consumption of the GPU in two aspects: 60% less time to solution and 10% less power required. Compared to the CPU-only solution, our GPU accelerated BLAST obtained a 2.5× overall speedup and 1.42× energy efficiency (green up) using 4th order (Q_4) finite elements, and a 1.9× speedup and 1.27× green up using 2nd order (Q2) finite elements.

Computer Science↗

Design for a Soft Error Resilient Dynamic Task-Based Runtime, In: 2015 IEEE International Parallel and Distributed Processing Symposium

As the scale of modern computing systems grows, failures will happen more frequently. On the way to Exactable a generic, low-overhead, resilient extension becomes a desired aptitude of any programming paradigm. In this paper we explore three additions to a dynamic task-based runtime to build a generic framework providing soft error resilience to task-based programming paradigms. The first recovers the application by re-executing the minimum required sub-DAG, the second takes critical checkpoints of the data flowing between tasks to minimize the necessary re-execution, while the last one takes advantage of algorithmic properties to recover the data without re-execution. These mechanisms have been implemented in the PaRSEC task-based runtime framework. Experimental results validate our approach and quantify the overhead introduced by such mechanisms.

Computer Science↗

Overview of the distributed image processing infrastructure to produce the Legacy Survey of Space and Time

The Vera C. Rubin Observatory is preparing to execute the most ambitious astronomical survey ever attempted, the Legacy Survey of Space and Time (LSST). Currently the final phase of construction is under way in the Chilean Andes, with the Observatory’s ten-year science mission scheduled to begin in 2025. Rubin’s 8.4-meter telescope will nightly scan the southern hemisphere collecting imagery in the wavelength range 320–1050 nm covering the entire observable sky every 4 nights using a 3.2 gigapixel camera, the largest imaging device ever built for astronomy. Automated detection and classification of celestial objects will be performed by sophisticated algorithms on high-resolution images to progressively produce an astronomical catalog eventually composed of 20 billion galaxies and 17 billion stars and their associated physical properties. In this article we present an overview of the system currently being constructed to perform data distribution as well as the annual campaigns which reprocess the entire image dataset collected since the beginning of the survey. These processing campaigns will utilize computing and storage resources provided by three Rubin data facilities (one in the US and two in Europe). Each year a Data Release will be produced and disseminated to science collaborations for use in studies comprising four main science pillars: probing dark matter and dark energy, taking inventory of solar system objects, exploring the transient optical sky and mapping the Milky Way. Also presented is the method by which we leverage some of the common tools and best practices used for management of large-scale distributed data processing projects in the high energy physics and astronomy communities. We also demonstrate how these tools and practices are utilized within the Rubin project in order to overcome the specific challenges faced by the Observatory.

79 ASTRONOMY AND ASTROPHYSICS↗

Performance Analysis of Data Processing in Distributed File Systems with Near Data Processing

In the era of big data, the escalating volume and velocity of data generation pose significant challenges in data processing. Traditional systems like Spark and Hadoop manage the increasing amount and velocity of data by improving data placement and processing speeds. However, they face inherent limitations due to the essential data movement required for processing. In this paper, we explore the Skyhook framework, a novel extension of the Ceph distributed system, which significantly reduces the need for data movement. We present an extensive case study using the Skyhook framework, applying it with the TPC-H and K-means clustering algorithms. More specifically, we leverage the TPC-H benchmark to distinguish between CPU-intensive and I/O-intensive tasks. We explore the integration of K-means clustering into SQL, coupled with a near-data processing system to offload the computational burden of the K-means clustering algorithm to storage nodes. We conduct a comprehensive performance evaluation of distributed data processing applications across three processing approaches: traditional layout (baseline), optimized layout, and near-data processing. Additionally, we introduce the use of the FIO tool to simulate real-world system workloads, enabling the measurement of performance metrics such as average latency and CPU utilization. Our research is a significant advance in understanding how to optimize data processing systems to meet the demands of the modern data landscape.

Hou, Shiyue↗

CHARACTERIZING THE HEAVY ELEMENTS IN GLOBULAR CLUSTER M22 AND AN EMPIRICAL s-PROCESS ABUNDANCE DISTRIBUTION DERIVED FROM THE TWO STELLAR GROUPS

We present an empirical s-process abundance distribution derived with explicit knowledge of the r-process component in the low-metallicity globular cluster M22. We have obtained high-resolution, high signal-to-noise spectra for six red giants in M22 using the Magellan Inamori Kyocera Echelle spectrograph on the Magellan-Clay Telescope at Las Campanas Observatory. In each star we derive abundances for 44 species of 40 elements, including 24 elements heavier than zinc (Z = 30) produced by neutron-capture reactions. Previous studies determined that three of these stars (the 'r+s group') have an enhancement of s-process material relative to the other three stars (the 'r-only group'). We confirm that the r+s group is moderately enriched in Pb relative to the r-only group. Both groups of stars were born with the same amount of r-process material, but s-process material was also present in the gas from which the r+s group formed. The s-process abundances are inconsistent with predictions for asymptotic giant branch (AGB) stars with M {<=} 3 M{sub Sun} and suggest an origin in more massive AGB stars capable of activating the {sup 22}Ne({alpha},n){sup 25}Mg reaction. We calculate the s-process 'residual' by subtracting the r-process pattern in the r-only group from the abundances in the r+s group. In contrast to previous r- and s-process decompositions, this approach makes no assumptions about the r- and s-process distributions in the solar system and provides a unique opportunity to explore s-process yields in a metal-poor environment.

79 ASTRONOMY AND ASTROPHYSICS↗

Techniques for collective operations in distributed systems

Various embodiments are generally directed to techniques for collective operations among compute nodes in a distributed processing set, such as by utilizing ring sets and local sets of the distributed processing set. In some embodiments, a ring set may include a subset of the distributed processing set in which each compute node is connected to a network with a separate router. In various embodiments, a local set may include a subset of the distributed processing set in which each compute node is connected to a network with a common router. In one or more embodiments, each compute node in a distributed processing set may belong to one ring set and one local set.

Langer, Akhil↗

Numerical and experimental studies on effects of moisture content on combustion characteristics of simulated municipal solid wastes in a fixed bed

Highlights: • The effects of moisture content on the burning process of MSW are investigated. • A two-dimensional mathematical model was built to simulate the combustion process. • Temperature distributions, process rates, gas species were measured and simulated. • The The conversion ratio of C/CO and N/NO in MSW are inverse to moisture content. - Abstract: In order to reveal the features of the combustion process in the porous bed of a waste incinerator, a two-dimensional unsteady state model and experimental study were employed to investigate the combustion process in a fixed bed of municipal solid waste (MSW) on the combustion process in a fixed bed reactor. Conservation equations of the waste bed were implemented to describe the incineration process. The gas phase turbulence was modeled using the k–ε turbulent model and the particle phase was modeled using the kinetic theory of granular flow. The rate of moisture evaporation, devolatilization rate, and char burnout was calculated according to the waste property characters. The simulation results were then compared with experimental data for different moisture content of MSW, which shows that the incineration process of waste in the fixed bed is reasonably simulated. The simulation results of solid temperature, gas species and process rate in the bed are accordant with experimental data. Due to the high moisture content of fuel, moisture evaporation consumes a vast amount of heat, and the evaporation takes up most of the combustion time (about 2/3 of the whole combustion process). The whole bed combustion process reduces greatly as MSW moisture content increases. The experimental and simulation results provide direction for design and optimization of the fixed bed of MSW.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Multi-Fidelity Gaussian Process for Distribution System Voltage Probabilistic Estimation with PVs

The increasing penetration of behind-the-meter PVs causes challenges to maintain voltage security due to the lack of distribution system visibility. This paper proposes a nonlinear autoregressive Gaussian process (NARGP) approach to fuse limited number of SCADA/AMI data together with historical pseudo measurements for distribution node voltage probabilistic estimation. The high-fidelity SCADA data are fused with the low-fidelity AMI and pseudo measurements by the autoregressive algorithm embedded in the Gaussian process. This allows us to use multi-fidelity data to achieve entire distribution system voltage visibility. Numerical results carried out on the IEEE 123node system demonstrate that the NARGP method is able to obtain high accuracy in estimating bus voltage and quantifying estimation uncertainties as compared to other approaches.

distribution system estimation↗

Investigation of thermochemical biorefinery sizing and environmental sustainability impacts for conventional supply system and distributed pre-processing supply system designs

The 2011 US Billion-Ton Update estimates that by 2030 there will be enough agricultural and forest resources to sustainably provide at least one billion dry tons of biomass annually, enough to displace approximately 30% of the country's current petroleum consumption. A portion of these resources are inaccessible at current cost targets with conventional feedstock supply systems because of their remoteness or low yields. Reliable analyses and projections of US biofuels production depend on assumptions about the supply system and biorefinery capacity, which, in turn, depend upon economic value, feedstock logistics, and sustainability. A cross-functional team has examined combinations of advances in feedstock supply systems and biorefinery capacities with rigorous design information, improved crop yield and agronomic practices, and improved estimates of sustainable biomass availability. A previous report on biochemical refinery capacity noted that under advanced feedstock logistic supply systems that include depots and pre-processing operations there are cost advantages that support larger biorefineries up to 10 000 DMT/day facilities compared to the smaller 2000 DMT/day facilities. This report focuses on analyzing conventional versus advanced depot biomass supply systems for a thermochemical conversion and refinery sizing based on woody biomass. The results of this analysis demonstrate that the economies of scale enabled by advanced logistics offsets much of the added logistics costs from additional depot processing and transportation, resulting in a small overall increase to the minimum ethanol selling price compared to the conventional logistic supply system. While the overall costs do increase slightly for the advanced logistic supply systems, the ability to mitigate moisture and ash in the system will improve the storage and conversion processes. In addition, being able to draw on feedstocks from further distances will decrease the risk of biomass supply to the conversion facility.

99 GENERAL AND MISCELLANEOUS↗

Evaluation of negative ion distribution changes by image processing diagnostic

Distributions of hydrogen Balmer-α (H{sub α}) intensity and its reduction behavior close to a plasma grid (PG) surface have been observed by a spectrally selective imaging system in an arc discharge type negative hydrogen ion source in National Institute for Fusion Science. H{sub α} reduction indicates a reduction of negative hydrogen ions because the mutual neutralization process between H{sup +} and H{sup −} ions causes the dominant excitation process for H{sub α} emission in the rich H{sup −} condition such as in ionic plasma. We observed a significant change in H{sub α} reduction distribution due to change in the bias voltage, which is used to suppress the electron influx. Small H{sub α} reduction in higher bias is likely because the production of negative ions is suppressed by the potential difference between the plasma and PG surface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗