Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “parallel methods”

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.

At least 667 records · Page 37

HPC4Mobilty w/ UCB

The purpose of this project is to examine the energy impact of urban-scale traffic for the Los Angeles Basin by developing and implementing a scalable traffic assignment model. An energy optimization function will be posed and when integrated into the optimization code for travel assignment it can be mathematically proven to converge. The energy optimization function can then be compared to the typical travel time optimization that is traditionally used in traffic assignment models. The analysis will begin with static traffic assignment models with the routing for all origin and destinations computed in parallel on high performance computing facilities. Convergence of the numerical methods rely on the solution of convex programs (or extensions of these). This step will mostly consist of demonstrating the ability to parallelize the Frank Wolfe algorithm on various platforms. This work will contribute to LBNL’s efforts to develop new processes, analytical tools, program designs, and business models to advance the state of the art in next-generation sustainable transportation solutions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

MO-G-BRE-01: A Real-Time Virtual Delivery System for Photon Radiotherapy Delivery Monitoring

Purpose: Treatment delivery monitoring is important for radiotherapy, which enables catching dosimetric error at the earliest possible opportunity. This project develops a virtual delivery system to monitor the dose delivery process of photon radiotherapy in real-time using GPU-based Monte Carlo (MC) method. Methods: The simulation process consists of 3 parallel CPU threads. A thread T1 is responsible for communication with a linac, which acquires a set of linac status parameters, e.g. gantry angles, MLC configurations, and beam MUs every 20 ms. Since linac vendors currently do not offer interface to acquire data in real time, we mimic this process by fetching information from a linac dynalog file at the set frequency. Instantaneous beam fluence map (FM) is calculated. A FM buffer is also created in T1 and the instantaneous FM is accumulated to it. This process continues, until a ready signal is received from thread T2 on which an inhouse developed MC dose engine executes on GPU. At that moment, the accumulated FM is transferred to T2 for dose calculations, and the FM buffer in T1 is cleared. Once the calculation finishes, the resulting 3D dose distribution is directed to thread T3, which displays it in three orthogonal planes overlaid on the CT image for treatment monitoring. This process continues to monitor the 3D dose distribution in real-time. Results: An IMRT and a VMAT cases used in our patient-specific QA are studied. Maximum dose differences between our system and treatment planning system are 0.98% and 1.58% for the two cases, respectively. The average time per MC calculation is 0.1sec with <2% relative uncertainty. The update frequency of ∼10Hz is considered as real time. Conclusion: By embedding a GPU-based MC code in a novel data/work flow, it is possible to achieve real-time MC dose calculations to monitor delivery process.

60 APPLIED LIFE SCIENCES↗

A Sparse Distributed Gigascale Resolution Material Point Method

In this paper, we present a four-layer distributed simulation system and its adaptation to the Material Point Method (MPM). The system is built upon a performance portable C++ programming model targeting major High-Performance-Computing (HPC) platforms. A key ingredient of our system is a hierarchical block-tile-cell sparse grid data structure that is distributable to an arbitrary number of Message Passing Interface (MPI) ranks. We additionally propose strategies for efficient dynamic load balance optimization to maximize the efficiency of MPI tasks. Our simulation pipeline can easily switch among backend programming models, including OpenMP and CUDA, and can be effortlessly dispatched onto supercomputers and the cloud. Finally, we construct benchmark experiments and ablation studies on supercomputers and consumer workstations in a local network to evaluate the scalability and load balancing criteria. We demonstrate massively parallel, highly scalable, and gigascale resolution MPM simulations of up to 1.01 billion particles for less than 323.25 seconds per frame with 8 OpenSSH-connected workstations.

97 MATHEMATICS AND COMPUTING↗

CAST: Contraction Algorithm for Symmetric Tensors

Tensor contractions represent the most compute-intensive core kernels in ab initio computational quantum chemistry and nuclear physics. Symmetries in these tensor contractions makes them difficult to load balance and scale to large distributed systems. In this paper, we develop an efficient and scalable algorithm to contract symmetric tensors. We introduce a novel approach that avoids data redistribution in contracting symmetric tensors while also avoiding redundant storage and maintaining load balance. We present experimental results on two parallel supercomputers for several symmetric contractions that appear in the CCSD quantum chemistry method. We also present a novel approach to tensor redistribution that can take advantage of parallel hyperplanes when the initial distribution has replicated dimensions, and use collective broadcast when the final distribution has replicated dimensions, making the algorithm very efficient.

distributed memory↗

High-Power Targetry R&D Roadmap for High Energy Physics

Designing a reliable target is already a challenge for MW-class facilities today and has led several major accelerator facilities to operate at lower power due to target concerns. With present plans to increase beam power for next-generation accelerator facilities in the next decade, timely R&D in support of robust high-power targets is critical to secure the full physics benefits of ambitious accelerator power upgrades. The next generation of high-power targets and beam-intercepting devices (beam dumps, absorbers, collimators ) will have more complex geometries, novel materials, and new concepts that allow for use of improved high-heat-flux cooling methods. Advanced numerical simulations need to be developed to support design of reliable high-power beam targets. In parallel, development of radiation-hardened beam instrumentation is needed. Irradiation methods for high-power targets must be further developed, and new irradiation facilities are needed since only a few facilities worldwide offer beams suitable for target testing. A comprehensive R&D program must be implemented to address the many complex challenges faced by multi-MW beam intercepting devices.

Pellemoine, Frederique [Fermilab]↗

Scalable Incremental Checkpointing using GPU-Accelerated De-Duplication

Writing large amounts of data concurrently to stable storage is a typical I/O pattern of many HPC workflows. This pattern introduces high I/O overheads and results in increased storage space utilization especially for workflows that need to capture the evolution of data structures with high frequency as checkpoints. In this context, many applications, such as graph pattern matching, perform sparse updates to large data structures between checkpoints. For these applications, incremental checkpointing techniques that save only the differences from one checkpoint to another can dramatically reduce the checkpoint sizes, I/O bottlenecks, and storage space utilization. However, such techniques are not without challenges: it is non-trivial to transparently determine what data has changed since a previous checkpoint and assemble the differences in a compact fashion that does not result in excessive metadata. State-of-art data reduction techniques (e.g., compression and de-duplication) have significant limitations when applied to modern HPC applications that leverage GPUs: slow at detecting the differences, generate a large amount of metadata to keep track of the differences, and ignore crucial spatiotemporal checkpoint data redundancy. This paper addresses these challenges by proposing a Merkle tree-based incremental checkpointing method to exploit GPUs' high memory bandwidth and massive parallelism. Experimental results at scale show a significant reduction of the I/O overhead and space utilization of checkpointing compared with state-of-the-art incremental checkpointing and compression techniques.

Tan, Nigel↗

Algebraic multigrid domain and range decomposition (AMG-DD / AMG-RD)*

In modern large-scale supercomputing applications, algebraic multigrid (AMG) is a leading choice for solving matrix equations. However, the high cost of communication relative to that of computation is a concern for the scalability of traditional implementations of AMG on emerging architectures. This paper introduces two new algebraic multilevel algorithms, algebraic multigrid domain decomposition (AMG-DD) and algebraic multigrid range decomposition (AMG-RD), that replace traditional AMG V-cycles with a fully overlapping domain decomposition approach. While the methods introduced here are similar in spirit to the geometric methods developed by Brandt and Diskin [Multigrid solvers on decomposed domains, in Domain Decomposition Methods in Science and Engineering, Contemp. Math. 157, AMS, Providence, RI, 1994, pp. 135--155], Mitchell [Electron. Trans. Numer. Anal., 6 (1997), pp. 224--233], and Bank and Holst [SIAM J. Sci. Comput., 22 (2000), pp. 1411--1443], they differ primarily in that they are purely algebraic: AMG-RD and AMG-DD trade communication for computation by forming global composite “grids” based only on the matrix, not the geometry. (As is the usual AMG convention, “grids” here should be taken only in the algebraic sense, regardless of whether or not it corresponds to any geometry.) Another important distinguishing feature of AMG-RD and AMG-DD is their novel residual communication process that enables effective parallel computation on composite grids, avoiding the all-to-all communication costs of the geometric methods. The main purpose of this paper is to study the potential of these two algebraic methods as possible alternatives to existing AMG approaches for future parallel machines. As a result, this paper develops some theoretical properties of these methods and reports on serial numerical tests of their convergence properties over a spectrum of problem parameters.

97 MATHEMATICS AND COMPUTING↗

The use of electrical impedance spectroscopy for monitoring the hydration products of Portland cement mortars with high percentage of pozzolans

In this paper, mortars and pastes containing large replacement of pozzolan were studied by mechanical strength, thermogravimetric analysis (TGA), scanning electronic microscopy (SEM), mercury intrusion porosimetry (MIP) and electrical impedance spectroscopy (EIS). The effect of metakaolin (35%) and fly ash (60%) was evaluated and compared with an inert mineral addition (andalusite). The portlandite content was measured, finding that the pozzolanic reaction produced cementing systems with all portlandite fixed. The EIS measurements were analyzed by the equivalent electrical circuit (EEC) method. An EEC with three branches in parallel was applied. The dc resistance was related to the degree of hydration and allowed us to characterize plain and blended mortars. A constant phase element (CPE) quantified the electrical properties of the hydration products located in the solid–solution interface and was useful to distinguish the role of inert and pozzolanic admixtures present in the cement matrix.

36 MATERIALS SCIENCE↗

A new limiting procedure for discontinuous Galerkin methods applied to compressible multiphase flows with shocks and interfaces

Although the Discontinuous Galerkin (dg) method has seen widespread use for compressible flow problems in a single fluid with constant material properties, it has yet to be implemented in a consistent fashion for compressible multiphase flows with shocks and interfaces. Specifically, it is challenging to design a scheme that meets the following requirements: conservation, high-order accuracy in smooth regions and non-oscillatory behavior at discontinuities (in particular, material interfaces). Following the interface-capturing approach of Abgrall [1], we model flows of multiple fluid components or phases using a single equation of state with variable material properties; discontinuities in these properties correspond to interfaces. Here, to represent compressible phenomena in solids, liquids, and gases, we present our analysis for equations of state belonging to the Mie–Grüneisen family. Within the dg framework, we propose a conservative, high-order accurate, and non-oscillatory limiting procedure, verified with simple multifluid and multiphase problems. We show analytically that two key elements are required to prevent spurious pressure oscillations at interfaces and maintain conservation: (i) the transport equation(s) describing the material properties must be solved in a non-conservative weak form, and (ii) the suitable variables must be limited (density, momentum, pressure, and appropriate properties entering the equation of state), coupled with a consistent reconstruction of the energy. Further, we introduce a physics-based discontinuity sensor to apply limiting in a solution-adaptive fashion. We verify this approach with one- and two-dimensional problems with shocks and interfaces, including high pressure and density ratios, for fluids obeying different equations of state to illustrate the robustness and versatility of the method. Lastly, the algorithm is implemented on parallel graphics processing units (gpu) to achieve high speedup.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Towards scaling community detection on distributed-memory heterogeneous systems

Distributed multi-GPU systems pose significant challenges and opportunities for efficient execution of parallel applications. Graph algorithms are generally characterized by irregular memory accesses, low computation to communication ratios, and load balancing problems that are especially hard to address on multi-GPU systems. Graph community detection is an important problem in the emerging domain of graph analytics with numerous applications. In this paper, we present our ongoing work on distributed-memory multi-GPU implementation for graph community detection. Our work parallelizes the widely used (albeit serial) Louvain method on distributed multi-GPU platforms. Supported by an extensive set of experiments on a multi-GPU enabled supercomputer (OLCF Summit) and a single compute node (Nvidia DGX-2®), we demonstrate competitive performance to existing distributed-memory CPU-based implementation, and up to 6.5 better results than Nvidia RAPIDS® CUGRAPH. To the best of our knowledge, this work represents the first effort for community detection on distributed multi-GPU systems. Our approach and related findings can be extended to numerous other iterative graph algorithms on multi-GPU systems.

97 MATHEMATICS AND COMPUTING↗

CP2K: An Electronic Structure and Molecular Dynamics Software Package - Quickstep: Efficient and Accurate Electronic Structure Calculations

CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular and biological systems. It is especially aimed at massively-parallel and linear-scaling electronic structure methods and state-of-the-art ab-initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension. TDK has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 716142). VRR has been supported by the Swiss National Science Foundation in the form of Ambizione grant No. PZ00P2 174227 and RZK by the Natural Sciences and Engineering Research Council of Canada (NSERC) through Discovery Grants (RGPIN-2016-0505). GKS and CJM are supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. UK based work was funded under the embedded CSE programme of the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk), grants eCSE03-011, eCSE06-6, eCSE08-9, eCSE13-17 and the EPSRC (EP/P022235/1) grant “Surface and Interface Toolkit for the Materials Chemistry Community". Computational resources were provided by the Swiss National Supercomputing Centre (CSCS) and Compute Canada. The generous allocation of computing time on the FPGA-based supercomputer “Noctua" at PC2 is kindly acknowledged.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A fast, dense Chebyshev solver for electronic structure on GPUs

Matrix diagonalization is almost always involved in computing the density matrix needed in quantum chemistry calculations. In the case of modest matrix sizes (≲4000), performance of traditional dense diagonalization algorithms on modern GPUs is underwhelming compared to the peak performance of these devices. This motivates the exploration of alternative algorithms better suited to these types of architectures. We newly derive, and present in detail, an existing Chebyshev expansion algorithm whose number of required matrix multiplications scales with the square root of the number of terms in the expansion. Focusing on dense matrices of modest size, our implementation on GPUs results in large speed ups when compared to diagonalization. Additionally, we improve upon this existing method by capitalizing on the inherent task parallelism and concurrency in the algorithm. Furthermore, this improvement is implemented on GPUs by using CUDA and HIP streams via the MAGMA library and leads to a significant speed up over the serial-only approach for smaller (≲1000) matrix sizes. Finally, we apply our technique to a model system with a high density of states around the Fermi level, which typically presents significant challenges.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Latent Twins

Over the past decade, scientific machine learning has transformed the development of mathematical and computational frameworks for analyzing, modeling, and predicting complex systems. From inverse problems to numerical partial differential equations (PDEs), dynamical systems, and model reduction, these advances have pushed the boundaries of what can be simulated. Yet they have often progressed in parallel, with representation learning and algorithmic solution methods evolving largely as separate pipelines. With Latent Twins, we propose a unifying mathematical framework that creates a hidden surrogate in latent space for the underlying equations. Whereas digital twins mirror physical systems in the digital world, Latent Twins mirror mathematical systems in a learned latent space governed by operators. Through this lens, classical modeling, inversion, model reduction, and operator approximation all emerge as special cases of a single principle. We establish the fundamental approximation properties of Latent Twins for both ordinary differential equations (ODEs) and PDEs and demonstrate the framework across three representative settings: (i) canonical ODEs, capturing diverse dynamical regimes; (ii) a PDE benchmark using the shallow-water equations, contrasting Latent Twin simulations with deep operator network and forecasts with a four-dimensional variational method baseline; and (iii) a challenging real-data geopotential reanalysis dataset, reconstructing and forecasting from sparse, noisy observations. Latent Twins provide a compact, interpretable surrogate for solution operators that evaluate across arbitrary time gaps in a single-shot, while remaining compatible with scientific pipelines such as assimilation, control, and uncertainty quantification. Looking forward, this framework offers scalable, theory-grounded surrogates that bridge data-driven representation learning and classical scientific modeling across disciplines.

Latent Twins↗

Sci—Thur AM: YIS - 01: Dosimetric Analysis of Respiratory Induced Cardiac Intrafraction Motion in Left-sided Breast Cancer Radiotherapy

Introduction: Long-term cardiac side effects in left-sided breast cancer patients (BREL) after post-operative radiotherapy has become one of the most debated issues in radiation oncology. Through breathing-adapted radiotherapy the volume of the heart exposed to radiation can be significantly reduced by delivering the radiation only at the end of inspiration phase of the respiratory cycle, this is referred to as inspiration gating (IG). The purpose of this study is to quantify the potential reduction in cardiac exposure during IG compared to conventional BREL radiotherapy and to assess the dosimetric impact of cardiac motion due to natural breathing. Methods: 24 BREL patients treated with tangential parallel opposed photon beams were included in this study. All patients received a standard fast helical planning CT (FH-CT) and a 4D-CT. Treatment plans were created on the FH-CT using a clinical treatment planning system. The original treatment plan was then superimposed onto the end of inspiration CT and all 10 phases of the 4D-CT to quantify the dosimetric impact of respiratory motion and IG through 4D dose accumulation. Results: Through IG the mean dose to the heart, left ventricle, and left anterior descending artery (LAD) can be reduced in comparison to the clinical standard BREL treatment by as much as 8.39%, 10.11%, and 13.71% respectively (p < 0.05). Conclusion: Failure to account for respiratory motion can lead to under or overestimation in the calculated DVH for the heart, and it's sub-structures. IG can reduce cardiac exposure especially to the LAD during BREL radiotherapy.

60 APPLIED LIFE SCIENCES↗

SU-D-213-05: Design, Evaluation and First Applications of a Off-Site State-Of-The-Art 3D Dosimetry System

Purpose: To design, construct and commission a prototype in-house three dimensional (3D) dose verification system for stereotatic body radiotherapy (SBRT) verification at an off-site partner institution. To investigate the potential of this system to achieve sufficient performance (1mm resolution, 3% noise, within 3% of true dose reading) for SBRT verification. Methods: The system was designed utilizing a parallel ray geometry instigated by precision telecentric lenses and an LED 630nm light source. Using a radiochromic dosimeter, a 3D dosimetric comparison with our gold-standard system and treatment planning software (Eclipse) was done for a four-field box treatment, under gamma passing criteria of 3%/3mm/10% dose threshold. Post off-site installation, deviations in the system’s dose readout performance was assessed by rescanning the four-field box irradiated dosimeter and using line-profiles to compare on-site and off-site mean and noise levels in four distinct dose regions. As a final step, an end-to-end test of the system was completed at the off-site location, including CT-simulation, irradiation of the dosimeter and a 3D dosimetric comparison of the planned (Pinnacle{sup 3}) to delivered dose for a spinal SBRT treatment(12 Gy per fraction). Results: The noise level in the high and medium dose regions of the four field box treatment was relatively 5% pre and post installation. This reflects the reduction in positional uncertainty through the new design. This At 1mm dose voxels, the gamma pass rates(3%,3mm) for our in-house gold standard system and the off-site system were comparable at 95.8% and 93.2% respectively. Conclusion: This work will describe the end-to-end process and results of designing, installing, and commissioning a state-of-the-art 3D dosimetry system created for verification of advanced radiation treatments including spinal radiosurgery.

60 APPLIED LIFE SCIENCES↗

WE-AB-BRB-09: Real Time In Vivo Scintillating Fiber Array Detector for Medical LINACS

Purpose: An in vivo transmission scintillation fiber detector was developed to monitor patient treatment in real time for the enhancement of patient safety and treatment accuracy. The detector system is capable of monitoring each pulse from a medical LINAC during treatment to determine the dose delivered as treatment progresses. Methods: The detector system consists of 60 parallel scintillating fibers coupled to fast data processing optoelectronics that can monitor the beam fluence in real time. Each 2.5mm{sup 2} square fiber is aligned with an MLC leaf pair and is long enough to capture a 40cm field. The fibers are embedded within a water equivalent polymer substrate that is secured in the LINAC accessory tray. The fibers are coupled to high speed photosensors and front end amplifiers that filter noise and pass each pulse to a high speed analog-to-digital converter. The system components are capable of detecting pulse repetition times shorter than what is delivered by a medical LINAC to ensure true real time data acquisition. Results: The system was able to capture and record the signal from each linac pulse and display the information in real time with no pulse pile up. It was found that the fiber array attenuates 2.65% of the beam which can easily be compensated for in treatment planning. The fibers responded linearly with dose, are independent of clinical beam energies, and are independent of dose rate. Calibration of the system was performed as a function of beam energy, beam size, dose rate, and monitor units to optimize beam fluence error detection. Conclusion: The detector system presented provides true real time in vivo beam monitoring to enhance patient safety and treatment delivery accuracy. Furthermore, the detector can be used for current patient specific QA.

60 APPLIED LIFE SCIENCES↗

Advances in global optimization of high brightness beams

High brightness electron beams play an important role in accelerator-based applications such as driving X-ray free electron laser (FEL) radiation.Here in this paper, we report on advances in global beam dynamics optimization of an accelerator design using start-to-end simulations and a new parallel multi-objective differential evolution optimization method. The global optimization results in significant improvement of the final electron beam brightness.

43 PARTICLE ACCELERATORS↗