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At least 451 records · Page 25

Improving the performance of medical imaging applications using SYCL

As opposed to the Open Computing Language (OpenCL) programming model, in which host and device codes are generally written in different programming languages, SYCL can combine host and device codes for an application in a type-safe way to improve development productivity and performance portability. Hence, this report shows the experimental results of applying the SYCL programming model to medical imaging applications for a study on performance portability and programming productivity between OpenCL and SYCL. Rodinia is a widely used open-source benchmark suite for heterogeneous computing. We choose two medical imaging applications (Heart Wall and Particle Filter) in the benchmark suite, migrate the OpenCL implementations of the applications to the SYCL implementations, and evaluate their performance and productivity on Intel® microprocessors that contain a central processing unit (CPU) and an integrated graphics processing unit (GPU). The maturing SYCL compilers, which are based on a conformant implementation of the SYCL 1.2.1 Khronos specification, have been actively optimized for Intel® computing platforms. The experimental results are promising in terms of the raw performance and productivity. Although the SYCL implementation of the Heart Wall application does not execute successfully on a CPU, the SYCL implementations of the application can achieve comparable or better performance than the OpenCL implementation on Intel® integrated GPUs. For the Particle Filter application, the performance difference between the SYCL and OpenCL implementations is comparable on the GPUs for most cases, but the SYCL implementations are on average 4X faster than the OpenCL implementations on Intel® Xeon® CPUs. For programming productivity, we arguably use lines of code as a way to measure programming productivity in software. The SYCL programs reduce the lines of code of the OpenCL programs by 52% and 38% for the Heart Wall and Particle Filter, respectively. The results indicate that SYCL is a promising programming model for heterogeneous computing with the maturing compilers. We organize the remainder of the report as follows. Section II introduces the SYCL programming model, compares the major differences between an OpenCL program and a SYCL program, and describes the characteristics of the two applications. Section III describes the SYCL programming model in more details, and shows the SYCL implementation of a kernel function in the Particle Filter application as an example. In Section IV, we evaluate the performance of the applications on the CPUs and GPUs. Section V concludes the report.

59 BASIC BIOLOGICAL SCIENCES↗

The Design and Evaluation of "CAPTools"--A Computer Aided Parallelization Toolkit

Writing applications for high performance computers is a challenging task. Although writing code by hand still offers the best performance, it is extremely costly and often not very portable. The Computer Aided Parallelization Tools (CAPTools) are a toolkit designed to help automate the mapping of sequential FORTRAN scientific applications onto multiprocessors. CAPTools consists of the following major components: an inter-procedural dependence analysis module that incorporates user knowledge; a 'self-propagating' data partitioning module driven via user guidance; an execution control mask generation and optimization module for the user to fine tune parallel processing of individual partitions; a program transformation/restructuring facility for source code clean up and optimization; a set of browsers through which the user interacts with CAPTools at each stage of the parallelization process; and a code generator supporting multiple programming paradigms on various multiprocessors. Besides describing the rationale behind the architecture of CAPTools, the parallelization process is illustrated via case studies involving structured and unstructured meshes. The programming process and the performance of the generated parallel programs are compared against other programming alternatives based on the NAS Parallel Benchmarks, ARC3D and other scientific applications. Based on these results, a discussion on the feasibility of constructing architectural independent parallel applications is presented.

Yan, Jerry↗

Feature Extraction for Pipeline Defects Inspection Based Upon Distributed Acoustic Fiber Optic Sensing Data

Fiber-optic distributed acoustic sensing (DAS) is becoming an increasingly important tool for real-time monitoring of energy and civil infrastructure structural health such as pipelines. We present a systematic theoretical study of the potential for DAS to be directly coupled with guided ultrasonic waves typically used in conventional acoustic non-destructive evaluation (NDE) methods for real-time pipeline health monitoring. We are referring to this innovative new NDE technique as ultrasonic guided wave and optical fiber sensor fusion. In the practical application of DAS coupled with guided ultrasonic waves, the structural design of (1) the specific guided waves excited, (2) the physical installation of the acoustic transducers and the fiber optic sensors, and (3) the functional performance specifications (gauge length, sensitivity, Etc.) of fiber optic DAS have an important influence on overall capabilities of the monitoring system. Meanwhile, physics-based analysis of acoustic waves is still a challenge due to the complex nature of the Lamb wave when it propagates, scatters, and disperses in the presence of structural defects. In this work, we simulate carbon steel pipes relevant for oil and gas pipeline applications with diameters of approximately 6-12” and wall thickness of 0.5” as the objects to be monitored. By establishing and implementing these capabilities, we seek to pursue an in-depth study on structural parameter optimization of DAS network, measurement range, and signal processing with an ultimate goal of increasing the sensitivity and efficacy of DAS to defect identification for various modes of corrosion expected in practice. To study the characteristics of scattered acoustic waves and performance of DAS for defect identification, we simulated the response of DAS for multiple pipe structures, defect types, and DAS sensor network configuration using finite element software Ansys, then the properties of signal response are extracted to construct defect-sensitive features. The raw data simulated, and the associated features extracted can ultimately be utilized as annotated training data to benchmark various designs for DAS applications, guided acoustic excitation sources, and learning model parameters to enhance early detection of potentially problematic defects.

Pipeline Defects Inspection, Fiber-optic sensors, ↗

Virtual machine-based simulation platform for mobile ad-hoc network-based cyber infrastructure

In modeling and simulating complex systems such as mobile ad-hoc networks (MANETs) in de-fense communications, it is a major challenge to reconcile multiple important considerations: the rapidity of unavoidable changes to the software (network layers and applications), the difficulty of modeling the critical, implementation-dependent behavioral effects, the need to sustain larger scale scenarios, and the desire for faster simulations. Here we present our approach in success-fully reconciling them using a virtual time-synchronized virtual machine(VM)-based parallel ex-ecution framework that accurately lifts both the devices as well as the network communications to a virtual time plane while retaining full fidelity. At the core of our framework is a scheduling engine that operates at the level of a hypervisor scheduler, offering a unique ability to execute multi-core guest nodes over multi-core host nodes in an accurate, virtual time-synchronized manner. In contrast to other related approaches that suffer from either speed or accuracy issues, our framework provides MANET node-wise scalability, high fidelity of software behaviors, and time-ordering accuracy. The design and development of this framework is presented, and an ac-tual implementation based on the widely used Xen hypervisor system is described. Benchmarks with synthetic and actual applications are used to identify the benefits of our approach. The time inaccuracy of traditional emulation methods is demonstrated, in comparison with the accurate execution of our framework verified by theoretically correct results expected from analytical models of the same scenarios. In the largest high fidelity tests, we are able to perform virtual time-synchronized simulation of 64-node VM-based full-stack, actual software behaviors of MANETs containing a mix of static and mobile (unmanned airborne vehicle) nodes, hosted on a 32-core host, with full fidelity of unmodified ad-hoc routing protocols, unmodified application executables, and user-controllable physical layer effects including inter-device wireless signal strength, reachability, and connectivity.

97 MATHEMATICS AND COMPUTING↗

RECONSTRUCTION OF THE CORONAL MAGNETIC FIELD USING THE CESE-MHD METHOD

We present a new implementation of the MHD relaxation method for reconstruction of the nearly force-free coronal magnetic field from a photospheric vector magnetogram. A new numerical MHD scheme is proposed to solve the full MHD equations by using the spacetime conservation-element and solution-element method. The bottom boundary condition is prescribed in a similar way as in the stress-and-relax method, by changing the transverse field incrementally to match the magnetogram, and other boundaries of the computational box are set by the nonreflecting boundary conditions. Applications to the well-known benchmarks for nonlinear force-free-field reconstruction, the Low and Lou force-free equilibria, validate the method and confirm its capability for future practical application, with observed magnetograms as inputs.

79 ASTRONOMY AND ASTROPHYSICS↗

Deploy production sliding mesh capability with linear solver benchmarking (ECP Milestone Report, Ver. 1.0)

Wind applications require the ability to simulate rotating blades. To support this use-case, a novel design-order sliding mesh algorithm has been developed and deployed. The hybrid method combines the control volume finite element methodology (CVFEM) with concepts found within a discontinuous Galerkin (DG) finite element method (FEM) to manage a sliding mesh. The method has been demonstrated to be design-order for the tested polynomial basis (P=1 and P=2) and has been deployed to provide production simulation capability for a Vestas V27 (225 kW) wind turbine. Other stationary and canonical rotating flow simulations are also presented. As the majority of wind-energy applications are driving extensive usage of hybrid meshes, a foundational study that outlines near-wall numerical behavior for a variety of element topologies is presented. Results indicate that the proposed nonlinear stabilization operator (NSO) is an effective stabilization methodology to control Gibbs phenomena at large cell Peclet numbers. The study also provides practical mesh resolution guidelines for future analysis efforts. Application-driven performance and algorithmic improvements have been carried out to increase robustness of the scheme on hybrid production wind energy meshes. Specifically, the Kokkos-based Nalu Kernel construct outlined in the FY17/Q4 ExaWind milestone has been transitioned to the hybrid mesh regime. This code base is exercised within a full V27 production run. Simulation timings for parallel search and custom ghosting are presented. As the low-Mach application space requires implicit matrix solves, the cost of matrix reinitialization has been evaluated on a variety of production meshes. Results indicate that at low element counts, i.e., fewer than 100 million elements, matrix graph initialization and preconditioner setup times are small. However, as mesh sizes increase, e.g., 500 million elements, simulation time associated with "setup-up" costs can increase to nearly 50% of overall simulation time when using the full Tpetra solver stack and nearly 35% when using a mixed Tpetra- Hypre-based solver stack. The report also highlights the project achievement of surpassing the 1 billion element mesh scale for a production V27 hybrid mesh. A detailed timing breakdown is presented that again suggests work to be done in the setup events associated with the linear system. In order to mitigate these initialization costs, several application paths have been explored, all of which are designed to reduce the frequency of matrix reinitialization. Methods such as removing Jacobian entries on the dynamic matrix columns (in concert with increased inner equation iterations), and lagging of Jacobian entries have reduced setup times at the cost of numerical stability. Artificially increasing, or bloating, the matrix stencil to ensure that full Jacobians are included is developed with results suggesting that this methodology is useful in decreasing reinitialization events without loss of matrix contributions. With the above foundational advances in computational capability, the project is well positioned to begin scientific inquiry on a variety of wind-farm physics such as turbine/turbine wake interactions.

Domino, Stefan P.↗

High Performance Anion Exchange Membrane Fuel Cells Enabled by Fluoropoly(olefin) Membranes

Abstract Although the peak power density of anion exchange membrane fuel cells (AEMFCs) has been raised from ≈0.1 to ≈1.4 W cm −2 over the last decade, a majority of AEMFCs reported in the literature have not been demonstrated to achieve consistently high performance and steady‐state operation. Poly(olefin)‐based AEMs with fluorine substitution on the aromatic comonomer show considerably higher dimensional stability compared to samples that do not contain fluorine. More importantly, fluorinated poly(olefin)‐based AEMs exhibit high hydroxide conductivity without excessive hydration due to a new proposed mechanism where the fluorinated dipolar monomer facilitates increased hydroxide dissociation and transport. Using this new generation of AEMs, a stable, high‐performance AEMFC is operated for 120 h. When the fuel cell configuration is subjected to a constant current density of 600 mA cm −2 under H 2 /O 2 flow, the cell voltage declines only 11% (from 0.75 to 0.67 V) for the first 20 h during break‐in and the cell voltage loss is low (0.2 mV h −1 ) over the subsequent 100 h of cell testing. The ease of synthesis, potential for low‐cost commercialization, and remarkable ex situ properties and in situ performance of fluoropoly(olefin)‐based AEM renders this material a benchmark membrane for practical AEMFC applications.

Zhu, Liang↗

Adaptive time stepping for fluid-structure interaction solvers

In this work, a novel adaptive time stepping scheme for fluid-structure interaction (FSI) problems is proposed that allows for controlling the accuracy of the time-discrete solution. Furthermore, it eases practical computations by providing an efficient and very robust time step size selection. This has proven to be very useful, especially when addressing new physical problems, where no educated guess for an appropriate time step size is available. The fluid and the structure field, but also the fluid-structure interface are taken into account for the purpose of a posteriori error estimation, rendering it easy to implement and only adding negligible additional cost. The adaptive time stepping scheme is incorporated into a monolithic solution framework, but can straightforwardly be applied to partitioned solvers as well. The basic idea can be extended to the coupling of an arbitrary number of physical models. Accuracy and efficiency of the proposed method are studied in a variety of numerical examples ranging from academic benchmark tests to complex biomedical applications like the pulsatile blood flow through an abdominal aortic aneurysm. Finally, the demonstrated accuracy of the time-discrete solution in combination with reduced computational cost make this algorithm very appealing in all kinds of FSI applications.

97 MATHEMATICS AND COMPUTING↗

Additively manufactured β-Ti5553 with laser powder bed fusion: Microstructures and mechanical properties of bulk and lattice parts

Ti5553 (Ti-5Al-5Mo-5V-3Cr wt%) is a titanium alloy widely used for its high strength-to-weight ratio and good formability at elevated temperatures. Unlike Ti-6Al-4V, Ti5553 does not undergo martensitic transformation, preventing cracking of brittle martensite upon rapid cooling. This makes it a strong candidate for additive manufacturing (AM), particularly laser powder bed fusion (L-PBF). L-PBF offers the unique opportunity to make fine lattice structures to reduce component weight. Despite the growing field of AM, there have been limited studies on L-PBF Ti5553 lattices and how their properties differ from the bulk. Here the present work addresses this knowledge gap by investigating microstructures and properties of L-PBF bulk and lattice parts and the effect of post L-PBF heat treatments. Electron microscopy and mechanical testing show that the high dislocation density formed during L-PBF increases bulk part’s yield strength by approximately 100 MPa compared to the conventional alloy. Digital image correlation during compression testing of octet truss lattices reveals a layer-by-layer failure mode. Compared to the bulk, the lattice contains copious ω nanoprecipitation, weaker <001> texture, smaller average grain sizes, and larger content of high-angle grain boundaries. These features elicit differences in Taylor factor distributions for the lattice depending on load direction, underlining challenges in predicting lattice mechanical response based on bulk properties. By examining the processing-structure-property relationships in the bulk and lattice, the present results delineate their microstructural and mechanical differences and establish a benchmark for the future design applications of L-PBF Ti5553.

36 MATERIALS SCIENCE↗

Trajectory-guided configuration interaction simulations of multidimensional quantum dynamics

We propose an approach to modelling multidimensional quantum systems which uses direct-dynamics trajectories to guide wavefunction propagation. First, trajectory simulations are used to generate a sample of dynamically relevant configurations on the potential energy surface (PES). Second, the sampled configurations are used to construct an n-mode representation of the PES using a greedy algorithm. Finally, the time-dependent Schroedinger equation is solved using a configuration interaction expansion of the wavefunction, with individual basis functions derived directly from the 1-mode contributions to the n-mode PES. This approach is successfully demonstrated by application to a 20-dimensional benchmark problem describing tunnelling in the presence of coupled degrees of freedom.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CHARMM-GUI Glycan Modeler for modeling and simulation of carbohydrates and glycoconjugates

Characterizing glycans and glycoconjugates in the context of three-dimensional structures is important in understanding their biological roles and developing efficient therapeutic agents. Computational modeling and molecular simulation have become an essential tool complementary to experimental methods. In this work, we present a computational tool, Glycan Modeler for in silico N–/O –glycosylation of the target protein and generation of carbohydrate-only systems. In our previous study, we developed Glycan Reader , a web-based tool for detecting carbohydrate molecules from a PDB structure and generation of simulation system and input files. As integrated into Glycan Reader in CHARMM-GUI, Glycan Modeler (Glycan Reader & Modeler) enables to generate the structures of glycans and glycoconjugates for given glycan sequences and glycosylation sites using PDB glycan template structures from Glycan Fragment Database (http://glycanstructure.org/fragment-db). Our benchmark tests demonstrate the universal applicability of Glycan Reader & Modeler to various glycan sequences and target proteins. We also investigated the structural properties of modeled glycan structures by running 2-μs molecular dynamics simulations of HIV envelope protein. The simulations show that the modeled glycan structures built by Glycan Reader & Modeler have the similar structural features compared to the ones solved by X-ray crystallography. We also describe the representative examples of glycoconjugate modeling with video demos to illustrate the practical applications of Glycan Reader & Modeler . Glycan Reader & Modeler is freely available at http://charmm-gui.org/input/glycan.

59 BASIC BIOLOGICAL SCIENCES↗

Low-energy fine-structure resonances in photoionization of O ii

Resonant features in low-energy photoionization cross sections are reported in coupled-channel calculations for O ii including relativistic fine structure. The calculations reveal extensive near-threshold resonant structures in the small energy region between the fine structure levels of the ground state 2p{sup 2}({sup 3}P{sub 0,1,2}) of the residual ion O iii. Although the resonances have not yet been observed, they are similar to other experimentally observed features. They are expected to significantly enhance the very-low-temperature dielectronic recombination rates, potentially leading to the resolution of an outstanding nebular abundances anomaly. Higher energy partial and total photoionization cross sections of the ground configuration levels 2p{sup 3}({sup 4}S{sub 3/2}{sup o},{sup 2}D{sub 3/2,5/2}{sup o},{sup 2}P{sub 1/2,3/2}{sup o}) are found to be in agreement with experimental measurements on synchrotron-based photon sources [1-3], thereby identifying the excited O iii levels present in the ion beams. These are also the first results from a recently developed version of Breit-Pauli R-matrix (BPRM) codes, with inclusion of two-body magnetic interaction terms. The improved relativistic treatment could be important for other astrophysical applications and for more precise benchmarking of experimental measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Trilepton signals in the inert doublet model

In this work, we investigate the prospects for detecting the Inert Doublet Model via the trilepton channel at the LHC. We present a set of representative benchmark scenarios in which all applicable constraints are satisfied, and show that in some of these scenarios, it is possible to obtain a signal at the 5{sigma} significance level or better with integrated luminosity of 300 fb{sup -1}.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Experimental quantum learning of a spectral decomposition

Currently available quantum hardware allows for small-scale implementations of quantum machine learning algorithms. Such experiments aid the search for applications of quantum computers by benchmarking the near-term feasibility of candidate algorithms. Here we demonstrate the quantum learning of a two-qubit unitary by a sequence of three parameterized quantum circuits containing a total of 21 variational parameters. Moreover, we variationally diagonalize the unitary to learn its spectral decomposition, i.e., its eigenvalues and eigenvectors. We illustrate how this can be used as a subroutine to compress the depth of dynamical quantum simulations. One can view our implementation as a demonstration of entanglement-enhanced machine learning, as only a single (entangled) training data pair is required to learn a 4 × 4 unitary matrix.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

HAPPA: A Modular Platform for HPC Application Resilience Analysis with LLMs Embedded

High-performance computing (HPC) systems are increasingly vulnerable to soft errors, which pose significant challenges in maintaining computational accuracy and reliability. Predicting the resilience of HPC applications to these errors is crucial for robust code protection and detailed resilience analysis. In this study, we present HAppA, a modular platform designed for HPC Application Resilience Analysis. Embedding Large Language Models (LLMs), HAppA addresses understanding the context information of long code sequences typical in HPC applications. HAppA implements a novel code representation module that chunks the code into fixed-size segments and aggregates the embeddings of these segments. Three aggregation methods have been explored: MeanPooling, MaxPooling, and LSTM-based techniques. We built a DAtaset for REsilience analysis using Fault Injection (FI), named DARE. Using our DARE dataset, HAppA is trained for regression prediction tasks. Our evaluation results demonstrate the predictive accuracy of HAppA compared to other models, particularly noting that the LSTM-based aggregation method -- HAppA-LSTM -- achieves a mean squared error (MSE) of 0.078 for SDC prediction, surpassing the existing state-of-the-art PARIS model, which recorded an MSE of 0.1172. Additionally, HAppA with the KeyBERT model extracts a list of keywords representing the source code. A comprehensive importance analysis of these keywords further elucidates the code patterns contributing to the error rate. These findings highlight the effectiveness of HAppA in analyzing the resilience of HPC applications and establish a new benchmark for predictive accuracy in resilience.

Jiang, Hailong [Kent State University]↗

A Relaxed Physical Factorization Preconditioner for Mixed Finite Element Coupled Poromechanics

In this work, we introduce a relaxed physical factorization (RPF) preconditioner for the efficient iterative solution of the linearized algebraic system arising from the mixed finite element discretization of coupled poromechanics equations. The preconditioner is obtained by using a proper factorization of the $3\times3$ block matrix and setting a relaxation parameter $\alpha$. The preconditioner is inspired by the relaxed dimensional factorization introduced by Benzi et al. [J. Comput. Phys., 230 (2011), pp. 6185--6202; Comput. Methods Appl. Mech. Engrg., 300 (2016), pp. 129--145]. A stable algorithm is advanced to compute the optimal value of $\alpha$, along with a lower bound to control the possible ill-conditioning of the $\alpha$ dependent inner blocks. Lastly, numerical experiments in both theoretical benchmarks and real-world applications are presented and discussed to investigate the RPF properties, performance, and robustness.

97 MATHEMATICS AND COMPUTING↗

Distributed Halide

Many image processing tasks are naturally expressed as a pipeline of small computational kernels known as stencils. Halide is a popular domain-specific language and compiler designed to implement image processing algorithms. Halide uses simple language constructs to express what to compute and a separate scheduling co-language for expressing when and where to perform the computation. This approach has demonstrated performance comparable to or better than hand-optimized code. Until now, however, Halide has been restricted to parallel shared memory execution, limiting its performance for memory-bandwidth-bound pipelines or large-scale image processing tasks. We present an extension to Halide to support distributed-memory parallel execution of complex stencil pipelines. These extensions compose with the existing scheduling constructs in Halide, allowing expression of complex computation and communication strategies. Existing Halide applications can be distributed with minimal changes, allowing programmers to explore the tradeoff between recomputation and communication with little effort. Approximately 10 new of lines code are needed even for a 200 line, 99 stage application. On nine image processing benchmarks, our extensions give up to a 1.4× speedup on a single node over regular multithreaded execution with the same number of cores, by mitigating the effects of non-uniform memory access. The distributed benchmarks achieve up to 18× speedup on a 16 node testing machine and up to 57× speedup on 64 nodes of the NERSC Cori supercomputer.

97 MATHEMATICS AND COMPUTING↗