SEARCH · Search NASA
Results for “Parallelization”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Dynamical regimes of vortex flow in type-II superconductors with parallel twin boundaries
We explore the dynamics of driven magnetic flux lines in disordered type-II superconductors in the presence of twin boundaries oriented parallel to the direction of the applied magnetic field, using a three-dimensional elastic line model simulated with Langevin molecular dynamics. The lines are driven perpendicular to the planes to model the effect of an electric current applied parallel to the planes and perpendicular to the magnetic field. A study of the long-time non-equilibrium steady states for varying sample orientation and thickness reveals a rich collection of dynamical regimes spanning the depinning crossover region that separates the pinned and moving-lattice states of vortex matter. We observe the emergence of a preferred direction for the ordering of the Abrikosov lattice in the free- owing vortex regime due to asymmetric pinning by the planar defects. Furthermore, we have performed novel direct measurements of flux line excitations such as half-loops and double kinks to aid the characterization of the topologically rich flux flow profile.
PapyrusKV: a high-performance parallel key-value store for distributed NVM architectures
This paper introduces PapyrusKV, a parallel embedded key-value store (KVS) for distributed high-performance computing (HPC) architectures that offer potentially massive pools of nonvolatile memory (NVM). PapyrusKV stores keys with their values in arbitrary byte arrays across multiple NVMs in a distributed system. PapyrusKV provides standard KVS operations such as put, get, and delete. More importantly, PapyrusKV provides advanced features for HPC such as dynamic consistency control, zero-copy workflow, and asynchronous checkpoint/restart. Beyond filesystems, PapyrusKV provides HPC programmers with a high-level interface to exploit distributed NVM in the system, and it transparently organizes data to achieve high performance. Also, it allows HPC applications to specialize PapyrusKV to meet their specific requirements. We empirically evaluate PapyrusKV on three HPC systems with real NVM devices: OLCF's Summitdev, TACC's Stampede, and NERSC's Cori. Our results show that PapyrusKV can offer high performance, scalability, and portability across these various distributed NVM architectures.
Parallel simulated annealing with embedded machine learning and multifidelity models for reactor core design
This paper presents extensions to a penalty-free, parallel simulated annealing (SA) algorithm for multi-constrained combinatorial optimization with the aim of embedding multi-fidelity physics models into the annealing procedure. The method uses a low-fidelity, quickly executing model for rapid design space exploration and a high-fidelity model for detailed constraint resolution and on-the-fly bias correction. Machine learning models updated within the annealing procedure were used to bridge the gap between the multi-fidelity models, which led to accurate rapid exploration and efficient detailed constraint resolution. A software implementation of the new multi-fidelity optimization methods, called ML-PSA, was demonstrated on a continuous multi-fidelity optimization problem and a constrained combinatorial PWR lattice design problem. These problems demonstrate some of the features, parallel performance characteristics, and extensible nature of the multi-fidelity SA methods. This paper shows that the developed software and procedure are a general optimization tool that can be applied to a wide variety of scientific and engineering design optimization applications. (authors)
Optimizing Irregular Communication with Neighborhood Collectives and Locality-Aware Parallelism
Irregular communication often limits both the performance and scalability of parallel applications. Typically, applications individually implement irregular communication as point-to-point, and any optimizations are integrated directly into the application. As a result, these optimizations lack portability. It is difficult to optimize point-to-point messages within MPI, as the interface for single messages provides no information on the collection of all communication to be performed. However, the persistent neighbor collective API, released in the MPI 4 standard, provides an interface for portable optimizations of irregular communication within MPI libraries. This paper presents methods for implementing existing optimizations for irregular communication within neighborhood collectives, analyzes the impact of replacing point-to-point communication in existing codebases such as Hypre BoomerAMG with neighborhood collectives, and finally shows up to a 1.38x speedup on sparse matrix-vector multiplication communication within a BoomerAMG solve through the use of our optimized neighbor collectives. Here, the authors analyze three implementations of persistent neighborhood collectives for Alltoallv: an unoptimized wrapper of standard point-to-point communication, and two locality-aware aggregating methods. The second locality-aware implementation exposes an non-standard interface to perform additional optimization, and the authors present the additional 0.07x speedup from the extended interface. All optimizations are available in an open-source codebase, MPI Advance, which sits on top of MPI, allowing for optimizations to be added into existing codebases regardless of the system MPI install.
HyLiPoD: Parallel Particle Advection via a Hybrid of Lifeline Scheduling and Parallelization-Over-Data
Performance characteristics of parallel particle advection algorithms can vary greatly based on workload.With this short paper, we build a new algorithm based on results from a previous bake-off study which evaluated the performance of four algorithms on a variety of workloads. Our algorithm, called HyLiPoD, is a ''meta-algorithm,'' i.e., it considers the desired workload to choose from existing algorithms to maximize performance. To demonstrate HyliPoD's benefit, we analyze results from 162 tests including concurrencies of up to 8192 cores, meshes as large as 34 billion cells, and particle counts as large as 300 million. Our findings demonstrate that HyLiPoD's adaptive approach allows it to match the best performance of existing algorithms across diverse workloads.
Simulation of thermal hydraulic performance of multiple parallel micropin arrays for concentrating solar thermal applications with supercritical carbon dioxide
Concentrated solar power (CSP) plants have the potential to provide 24 h, renewable electricity. Current CSP systems have high capital and operational costs which makes the levelized cost of electricity uncompetitive with conventional techniques. Recent experimental research has shown the potential of small unit cells (up to 2 × 2 cm) containing micropin arrays (D H < 1 mm) to operate efficiently at high incident flux (>140 W cm -2 ) using supercritical carbon dioxide as the working fluid. Applying this technology to CSP systems would result in a smaller central receiver, which would reduce thermal losses, increase receiver efficiency and reduce the capital cost of the receiver component. This study investigates and addresses the practical thermal and hydraulic issues in numbering up these small unit cells into numerous parallel cells within an integrated module design. A thermal hydraulic network model is developed to quantify the distribution and the overall receiver efficiency of an integrated module. This model is used to specify maximum allowable unit cell size and header dimensions to maintain acceptable thermal performance and pressure loss. Once a module design was finalized, parametric studies were performed to study the effects of varying incident flux on flow distribution and thermal performance of the module. Finally, the results show that an integrated module design can be achieved with less than 5% flow maldistribution and a pressure drop acceptable to the remainder of the system.
Medium amplitude parallel superposition (MAPS) rheology. Part 2: Experimental protocols and data analysis
An experimental protocol is developed to directly measure the new material functions revealed by medium amplitude parallel superposition (MAPS) rheology. This protocol measures the medium amplitude response of a material to a simple shear deformation composed of three sine waves at different frequencies, revealing a rich dataset consisting of up to 19 measurements of the third-order complex modulus at distinct three-frequency coordinates. We discuss how the choice of input frequencies influences the features of the MAPS domain studied by the experiment. A polynomial interpolation method for reducing the bias of measured values from spectral leakage and reducing variance due to noise is discussed, including a derivation of the optimal range of amplitudes for the input signal. This leads to the conclusion that conducting the experiment in a stress-controlled fashion possesses a distinct advantage to the strain-controlled mode. The experimental protocol is demonstrated through measurements of the MAPS response of a model complex fluid: a surfactant solution of wormlike micelles. The resulting dataset is indeed large and feature-rich, while still acquired in a time comparable to similar medium amplitude oscillatory shear (MAOS) experiments. We demonstrate that the data represent measurements of an intrinsic material function by studying its internal consistency, compatibility with low-frequency predictions for Coleman–Noll simple fluids, and agreement with data obtained via MAOS amplitude sweeps. Finally, the data are compared to predictions from the corotational Maxwell model to demonstrate the power of MAPS rheology in determining whether a constitutive model is consistent with a material’s time-dependent response.
Three-dimensional variational nodal method parallelization for pin resolved neutron transport calculations
Not Available
Parallel Discovery Strategies Provide a Basis for Riboswitch Ligand Design
Abstract not provided
Parallelization of the inverse fast multipole method with an application to boundary element method
Not provided.
Fast spherical centroidal Voronoi mesh generation: A Lloyd-preconditioned LBFGS method in parallel
Not Available
A characterization of soft-error sensitivity in data-parallel and model-parallel distributed deep learning
Not provided.
Excited-state one-neutron halo nuclei within a parallel momentum distribution analysis
Not Available
Exploration of Fine-Grained Parallelism for Load Balancing Eager K-truss on GPU and CPU.
Abstract not provided.