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At least 73 records · Page 4

A flexible and differentiable coil proxy for stellarator equilibrium optimization

Balancing plasma performance and coil cost is a significant challenge when designing a stellarator power plant. Most current stellarator designs are produced through two-stage optimization: stage-1 for the equilibrium and stage-2 for a coil design that reproduces its magnetic configuration. Because few proxies connect both stages, two-stage optimization can produce plasmas that have high-quality physical properties but overly complex coils. In recent years, single-stage optimization has increasingly been used to optimize the plasma and coils simultaneously in order to improve the plasma–coil balance. However, all existing single-stage tools are specialized for filament coils, cannot model coil systems containing permanent magnets or dipole arrays, and continue to be challenged by numerical problems. The quasi-single-stage optimization finds a middle ground by integrating a coil optimization subproblem into stage-1 optimization. We present a flexible, differentiable coil complexity proxy based on the newly developed QUADCOIL coil optimization code. QUADCOIL is fast and can target realistic coil metrics and constraints that are unavailable to codes with comparable speed. We demonstrate the effectiveness and flexibility of the QUADCOIL proxy by presenting two QSS optimization studies. The first study produces a permanent magnet solution for the MUSE stellarator with 34% fewer magnets than previous solutions. The second study produces a coil solution for the ARIES-CS stellarator with 30% reductions in both peak and root-mean-square force.

Fu, Lanke [Princeton Plasma Physics Laboratory (PP↗

SMT-Aware Instantaneous Footprint Optimization

Modern architectures employ simultaneous multithreading (SMT) to increase thread-level parallelism. SMT threads share many functional units and the whole memory hierarchy of a physical core. Without a careful code design, SMT threads can easily contend with each other for these shared resources, causing severe performance degradation. Minimizing SMT thread contention for HPC applications running on dedicated platforms is very challenging, because they usually spawn threads within Single Program Multiple Data (SPMD) models. To address this important issue, we introduce a simple scheme for SMT-aware code optimization, which aims to reduce the memory contention across SMT threads.

Instantaneous Footprint↗

A new relativistic viscous hydrodynamics code and its application to the Kelvin–Helmholtz instability in high-energy heavy-ion collisions

Here, we construct a new relativistic viscous hydrodynamics code optimized in the Milne coordinates. We also split the conservation equations into an ideal part and a viscous part, using the Strang spitting method. In the code a Riemann solver based on the two-shock approximation is utilized for the ideal part and the Piecewise Exact Solution (PES) method is applied for the viscous part. Furthemore, we check the validity of our numerical calculations by comparing analytical solutions, the viscous Bjorken’s flow and the Israel–Stewart theory in Gubser flow regime. Using the code, we discuss possible development of the Kelvin–Helmholtz instability in high-energy heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Isotope exchange kinetics in metal hydrides I : TPLUG model.

A one-dimensional isobaric reactor model is used to simulate hydrogen isotope exchange processes taking place during flow through a powdered palladium bed. This simple model is designed to serve primarily as a platform for the initial development of detailed chemical mechanisms that can then be refined with the aid of more complex reactor descriptions. The one-dimensional model is based on the Sandia in-house code TPLUG, which solves a transient set of governing equations including an overall mass balance for the gas phase, material balances for all of the gas-phase and surface species, and an ideal gas equation of state. An energy equation can also be solved if thermodynamic properties for all of the species involved are known. The code is coupled with the Chemkin package to facilitate the incorporation of arbitrary multistep reaction mechanisms into the simulations. This capability is used here to test and optimize a basic mechanism describing the surface chemistry at or near the interface between the gas phase and a palladium particle. The mechanism includes reversible dissociative adsorptions of the three gas-phase species on the particle surface as well as atomic migrations between the surface and the bulk. The migration steps are more general than those used previously in that they do not require simultaneous movement of two atoms in opposite directions; this makes possible the creation and destruction of bulk vacancies and thus allows the model to account for variations in the bulk stoichiometry with isotopic composition. The optimization code APPSPACK is used to adjust the mass-action rate constants so as to achieve the best possible fit to a given set of experimental data, subject to a set of rigorous thermodynamic constraints. When data for nearly isothermal and isobaric deuterium-to-hydrogen (D {yields} H) and hydrogen-to-deuterium (H {yields} D) exchanges are fitted simultaneously, results for the former are excellent, while those for the latter show pronounced deviations at long times. These discrepancies can be overcome by postulating the presence of a surface poison such as carbon monoxide, but this explanation is highly speculative. When the method is applied to D {yields} H exchanges intentionally poisoned by known amounts of CO, the fitting results are noticeably degraded from those for the nominally CO-free system but are still tolerable. When TPLUG is used to simulate a blowdown-type experiment, which is characterized by large and rapid changes in both pressure and temperature, discrepancies are even more apparent. Thus, it can be concluded that the best use of TPLUG is not in simulating realistic exchange scenarios, but in extracting preliminary estimates for the kinetic parameters from experiments in which variations in temperature and pressure are intentionally minimized.

99 GENERAL AND MISCELLANEOUS↗

Optimizing legacy molecular dynamics software with directive-based offload

The directive-based programming models are one solution for exploiting many-core coprocessors to increase simulation rates in molecular dynamics. They offer the potential to reduce code complexity with offload models that can selectively target computations to run on the CPU, the coprocessor, or both. In our paper, we describe modifications to the LAMMPS molecular dynamics code to enable concurrent calculations on a CPU and coprocessor. We also demonstrate that standard molecular dynamics algorithms can run efficiently on both the CPU and an x86-based coprocessor using the same subroutines. As a consequence, we demonstrate that code optimizations for the coprocessor also result in speedups on the CPU; in extreme cases up to 4.7X. We provide results for LAMMAS benchmarks and for production molecular dynamics simulations using the Stampede hybrid supercomputer with both Intel (R) Xeon Phi (TM) coprocessors and NVIDIA GPUs: The optimizations presented have increased simulation rates by over 2X for organic molecules and over 7X for liquid crystals on Stampede. The optimizations are available as part of the "Intel package" supplied with LAMMPS. (C) 2015 Elsevier B.V. All rights reserved.

97 MATHEMATICS AND COMPUTING↗

Tau-REx I: A next generation retrieval code for exoplanetary atmospheres

Spectroscopy of exoplanetary atmospheres has become a well established method for the characterization of extrasolar planets. We here present a novel inverse retrieval code for exoplanetary atmospheres. T-REx(Tau Retrieval for Exoplanets) is a line-by-line radiative transfer fully Bayesian retrieval framework. T-REx includes the following features:(1) the optimized use of molecular line lists from the ExoMol project; (2) an unbiased atmospheric composition prior selection, through custom built pattern recognition software; (3) the use of two independent algorithms to fully sample the Bayesian likelihood space: nested sampling as well as a more classical Markov Chain Monte Carlo approach; (4) iterative Bayesian parameter and model selection using the full Bayesian Evidence as well as the Savage–Dickey Ratio for nested models; and (5) the ability to fully map very large parameter spaces through optimal code parallelization and scalability to cluster computing. In this publication we outline the T-REx framework and demonstrate, using a theoretical hot-Jupiter transmission spectrum, the parameter retrieval and model selection. We investigate the impact of signal-to-noise ratio and spectral resolution on the retrievability of individual model parameters, both in terms of error bars on the temperature and molecular mixing ratios as well as its effect on the model’s global Bayesian evidence.

79 ASTRONOMY AND ASTROPHYSICS↗

Global stellarator coil optimization with quadratic constraints and objectives

Most present stellarator designs are produced by costly two-stage optimization: the first for an optimized equilibrium, and the second for a coil design reproducing its magnetic configuration. Few proxies for coil complexity and forces exist at the equilibrium stage. Rapid initial state finding for both stages is a topic of active research. Most present convex coil optimization codes use the least square winding surface method by Merkel (NESCOIL), with recent improvements in conditioning, regularization, sparsity, and physics objectives. While elegant, the method is limited to modeling the norms of linear functions in coil current. We present QUADCOIL, a global coil optimization method that targets combinations of linear and quadratic functions of the current. It can directly constrain and/or minimize a wide range of physics objectives unavailable in NESCOIL and REGCOIL, including the Lorentz force, magnetic energy, curvature, field-current alignment, and the maximum density of a dipole array. QUADCOIL requires no initial guess and runs nearly $10$ 2 x faster than filament optimization. Integrating it in the equilibrium optimization stage can potentially exclude equilibria with difficult-to-design coils, without significantly increasing the computation time per iteration. QUADCOIL finds the exact, global minimum in a large parameter space when possible, and otherwise finds a well-performing approximate global minimum. It supports most regularization techniques developed for NESCOIL and REGCOIL. We demonstrate QUADCOIL’s effectiveness in coil topology control, minimizing non-convex penalties, and predicting filament coil complexity with three numerical examples.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Hyper-Heuristics to Automatically Target Code to Computer Architectures

With each new generation of High Performance Computing (HPC) architecture, the gap between peak theoretical performance and the observed performance is growing. The goal of this research is to develop a tool to utilize hyper-heuristics to target code to a computational environment. In order to test this, sorting algorithms will be evolved on several different architectures. The final solutions will then migrate to all other architectures and their fitnesses compared. If the natively-evolved algorithms out-perform all others, then it can be concluded that the tool successfully targeted its solutions to the architecture of origin. This is the first step towards creating a program-agnostic tool for optimizing code to the native environment. The results are pending testing on the high performance cluster. If it can be shown that the tool is able to optimize solutions for the environment, then the door opens to automatically optimizing entire programs.

97 MATHEMATICS AND COMPUTING↗

Optimizing inference of segmentation on high-resolution images in MLExchange

MLExchange is a machine learning (ML) operations platform providing web user-interfaces (UIs) for data visualization and analysis pipelines at synchrotron facilities. Among these UIs is the segmentation app which helps synchrotron users utilize ML algorithms to automatically segment high-resolution scientific images with minimal manual annotation effort. In this work, we share code optimizations that significantly speed up the segmentation inference workflow of large data in short time. By optimizing the sequence of CPU-GPU data transfers and introducing CPU parallelization to key operations, we improve the per-device, per-image frame computational efficiency and observe close to 3×$$\times$$ speedup over the original segmentation inference workflow run time when utilizing a single GPU. Further adaptations enabling multi-GPU inference yield more than 40×$$\times$$ speedup with 100 GPUs compared to the optimized single GPU inference workflow. This acceleration of the segmentation inference workflow will provide MLExchange users with easy access to segmentation results with little wait time.

Lu, Shizhao↗

Parallel k-means Clustering of Geospatial Data Sets Using Manycore CPU Architectures

The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery and mining of weather, climate, ecological, and other geoscientific data sets fused from disparate sources. Many of the standard tools used on individual workstations are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of parallelism available in state-of-the-art high-performance computing platforms can enable such analysis. Here, we describe pKluster, an open-source tool we have developed for accelerated k-means clustering of geospatial and geospatiotemporal data, and discuss algorithmic modifications and code optimizations we have made to enable it to effectively use parallel machines based on novel CPU architectures—such as the Intel “Knights Landing” Xeon Phi and Skylake Xeon processors—with many cores and hardware threads, and employing significant single instruction, multiple data (SIMD) parallelism. We outline some applications of the code in ecology and climate science contexts and present a detailed discussion of the performance of the code for one such application, LiDAR-derived vertical vegetation structure classification.

Mills, Richard T↗

IEA Wind Energy Task 37 - System Engineering - Aerodynamic Optimization Case Study

This paper presents the results from the first IEA Wind Task 37 aerodynamic optimization case study. 8 participants applied their optimization tools to a purely aerodynamic problem and the results were compared. Overall, the different tools produced widely different designs, while there was better agreement in the improvement achieved. This highlights the fact that further investigation is needed to try to understand these differences and develop best practices. There were too many differences between the different analysis and optimization codes to determine the sources of these differences. However, several potential sources of discrepancy were identified for further investigation. One hypothesis is that one potential source of discrepancy is that the design problem itself is relatively flat in design directions of constant loading. This flatness would impact the convergence in the optimization, while at the same time mean that discrepancies in the design itself would be less severe.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

IEA Wind Energy Task 37 System Engineering Aerodynamic Optimization Case Study: Preprint

This paper presents the results from the first IEA Wind Task 37 aerodynamic optimization case study. Eight participants applied their optimization tools to a purely aerodynamic problem and the results were compared. Overall, the different tools produced widely different designs, while there was better agreement in the improvement achieved. This highlights the fact that further investigation is needed to try to understand these differences and develop best practices. There were too many differences between the different analysis and optimization codes to determine the sources of these differences. However, several potential sources of discrepancy were identified for further investigation. One hypothesis is that one potential source of discrepancy is that the design problem itself is relatively flat in design directions of constant loading. This flatness would impact the convergence in the optimization, and at the same time mean that discrepancies in the design itself would be less severe.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

Exploiting variability for energy optimization of parallel programs

Here in this paper we present optimizations that use DVFS mechanisms to reduce the total energy usage in scientific applications. Our main insight is that noise is intrinsic to large scale parallel executions and it appears whenever shared resources are contended. The presence of noise allows us to identify and manipulate any program regions amenable to DVFS. When compared to previous energy optimizations that make per core decisions using predictions of the running time, our scheme uses a qualitative approach to recognize the signature of executions amenable to DVFS. By recognizing the "shape of variability" we can optimize codes with highly dynamic behavior, which pose challenges to all existing DVFS techniques. We validate our approach using offline and online analyses for one-sided and two-sided communication paradigms. We have applied our methods to NWChem, and we show best case improvements in energy use of 12% at no loss in performance when using online optimizations running on 720 Haswell cores with one-sided communication. With NWChem on MPI two-sided and offline analysis, capturing the initialization, we find energy savings of up to 20%, with less than 1% performance cost.

97 MATHEMATICS AND COMPUTING↗

MO-H-19A-02: Investigation of Modulated Electron Arc (MeArc) Therapy for the Treatment of Scalp Tumors

Purpose: Electron arc therapy has long been proposed as the most suitable technique for the treatment of superficial tumors that follow circularly curved surfaces. However it was challenged by unsuitability of the conventional applicators and the lack of adequate 3-D dose calculation tools for arc electron beams in the treatment planning systems (TPS). Now with the availability of an electron specific multi-leaf collimator (eMLC) and an in-house Monte Carlo (MC) based TPS, we were motivated to investigate more advanced modulated electron arc (MeARC) therapy and its beneficial outcome. Methods: We initiated the study by a film measurement conducted in a head and neck phantom, where we delivered electron arcs in a step and shoot manner using the light field as a guide to avoid fields abutments. This step was done to insure enough clearance for the arcs with eMLC. MCBEAM and MCPLAN MC codes were used for the treatment head simulation and phantom dose calculation, respectively. Treatment plans were generated for targets drawn in real patient CTs and head and neck phantom. We utilized beams eye view available from a commercial planning system to create beamlets having same isocenter and adjoined at the scalp surface. Then dose-deposition coefficients from those beamlets were calculated for all electron energies using MCPLAN. An in-house optimization code was then used to find the optimum weights needed from individual beamlets. Results: MeARC showed a nicely tailored dose distribution around the circular curved target on the scalp. Some hot spots were noticed and could be attributed to fields abutment problem owing to the bulging nature of electron profiles. Brain dose was shown to be at lower levels compared to photon treatment. Conclusion: MeARC was shown to be a promising modality for treating scalp cases and could be beneficial to all superficial tumors with a circular curvature.

60 APPLIED LIFE SCIENCES↗

Reducing turbulent transport in toroidal configurations via shaping

Recent progress in reducing turbulent transport in stellarators and tokamaks by 3D shaping using a stellarator optimization code in conjunction with a gyrokinetic code is presented. The original applications of the method focused on ion temperature gradient transport in a quasi-axisymmetric stellarator design. Here, an examination both of other turbulence channels and other starting configurations is initiated. It is found that the designs evolved for transport from ion temperature gradient turbulence also display reduced transport from other transport channels whose modes are also stabilized by improved curvature, such as electron temperature gradient and ballooning modes. The optimizer is also applied to evolving from a tokamak, finding appreciable turbulence reduction for these devices as well. From these studies, improved understanding is obtained of why the deformations found by the optimizer are beneficial, and these deformations are related to earlier theoretical work in both stellarators and tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reducing Turbulent Transport in Toroidal Configurations via Shaping

Recent progress in reducing turbulent transport in stellarators and tokamaks by 3D shaping using a stellarator optimization code in conjunction with a gyrokinetic code is presented. The original applications of the method focussed on ion temperature gradient transport in a quasi-axisymmetric stellarator design. Here, an examination of both other turbulence channels and other starting configurations is initiated. It is found that the designs evolved for transport from ion temperature gradient turbulence also display reduced transport from other transport channels whose modes are also stabilized by improved curvature, such as electron temperature gradient and ballooning modes. The optimizer is also applied to evolving from a tokamak, finding appreciable turbulence reduction for these devices as well. From these studies, improved understanding is obtained of why the deformations found by the optimizer are beneficial, and these deformations are related to earlier theoretical work in both stellarators and tokamaks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A High Performance Sparse Tensor Algebra Compiler in MLIR

Sparse tensor algebra is widely used in many applications, including scientific computing, machine learning, and data analytics. The performance of sparse tensor algebra kernels strongly depends on the intrinsic characteristics of the input tensors, hence many storage formats are designed for tensors to achieve optimal performance for particular applications/architectures, which makes it challenging to implement and optimize every tensor operation of interest on a given architecture. We propose a tensor algebra domain-specific language (DSL) and compiler framework to automatically generate kernels for mixed sparse-dense tensor algebra operations. The proposed DSL provides high-level programming abstractions that resemble the familiar Einstein notation to represent tensor algebra operations. The compiler introduces a new Sparse Tensor Algebra dialect built on top of LLVM's extensible MLIR compiler infrastructure for efficient code generation while covering a wide range of tensor storage formats. Our compiler also leverages input-dependent code optimization to enhance data locality for better performance. Our results show that the performance of automatically generated kernels outperforms the state-of-the-art sparse tensor algebra compiler, with up to 20.92x, 6.39x, and 13.9x performance improvement over state-of-the-art tensor algebra compilers, for parallel SpMV, SpMM, and TTM, respectively.

Tian, Ruiqin↗

Geometry optimization speedup through a geodesic approach to internal coordinates

We present a new geodesic-based method for geometry optimization in a basis set of redundant internal coordinates. Overall, our method updates the molecular geometry by following the geodesic generated by a displacement vector on the internal coordinate manifold, which dramatically reduces the number of steps required to converge to a minimum. Our method can be implemented in any existing optimization code, requiring only implementation of derivatives of the Wilson B-matrix and the ability to numerically solve an ordinary differential equation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗