SEARCH · Engineering Papers

Results for “code portability”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Developments in Performance and Portability for MadGraph5_aMC@NLO

Event generators simulate particle interactions using Monte Carlo techniques, providing the primary connection between experiment and theory in experimental high energy physics. These software packages, which are the first step in the simulation worflow of collider experiments, represent approximately 5 to 20% of the annual WLCG usage for the ATLAS and CMS experiments. With computing architectures becoming more heterogeneous, it is important to ensure that these key software frameworks can be run on future systems, large and small. In this contribution, recent progress on porting and speeding up the Madgraph5_aMC@NLO event generator on hybrid architectures, i.e. CPU with GPU accelerators, is discussed. The main focus of this work has been in the calculation of scattering amplitudes and "matrix elements", which is the computational bottleneck of an event generation application. For physics processes limited to QCD leading order, the code generation toolkit has been expanded to produce matrix element calculations using C++ vector instructions on CPUs and using CUDA for NVidia GPUs, as well as using Alpaka, Kokkos and SYCL for multiple CPU and GPU architectures. Performance is reported in terms of matrix element calculations per time on NVidia, Intel, and AMD devices. The status and outlook for the integration of this work into a production release usable by the LHC experiments, with the same functionalities and very similar user interfaces as the current Fortran version, is also described.

Valassi, Andrea↗

DOE OSTI2015

Towards intelligent diagnostic system employing integration of mathematical and engineering model

The development of medical diagnostic system has been one of the main research fields during years. The goal of the medical diagnostic system is to place a nosological system that could ease the diagnostic evaluation normally performed by scientists and doctors. Efficient diagnostic evaluation is essentials and requires broad knowledge in order to improve conventional diagnostic system. Several approaches on developing the medical diagnostic system have been designed and tested since the earliest 60s. Attempts on improving their performance have been made which utilizes the fields of artificial intelligence, statistical analyses, mathematical model and engineering theories. With the availability of the microcomputer and software development as well as the promising aforementioned fields, medical diagnostic prototypes could be developed. In general, the medical diagnostic system consists of several stages, namely the 1) data acquisition, 2) feature extraction, 3) feature selection, and 4) classifications stages. Data acquisition stage plays an important role in converting the inputs measured from the real world physical conditions to the digital numeric values that can be manipulated by the computer system. One of the common medical inputs could be medical microscopic images, radiographic images, magnetic resonance image (MRI) as well as medical signals such as electrocardiogram (ECG) and electroencephalogram (EEG). Normally, the scientist or doctors have to deal with myriad of data and redundant to be processed. In order to reduce the complexity of the diagnosis process, only the significant features of the raw data such as peak value of the ECG signal or size of lesion in the mammogram images will be extracted and considered in the subsequent stages. Mathematical models and statistical analyses will be performed to select the most significant features to be classified. The statistical analyses such as principal component analysis and discriminant analysis as well as mathematical model of clustering technique have been widely used in developing the medical diagnostic systems. The selected features will be classified using mathematical models that embedded engineering theory such as artificial intelligence, support vector machine, neural network and fuzzy-neuro system. These classifiers will provide the diagnostic results without human intervention. Among many publishable researches, several prototypes have been developed namely NeuralPap, Neural Mammo, and Cervix Kit. The former system (NeuralPap) is an automatic intelligent diagnostic system for classifying and distinguishing between the normal and cervical cancerous cells. Meanwhile, the Cervix Kit is a portable Field-programmable gate array (FPGA)-based cervical diagnostic kit that could automatically diagnose the cancerous cell based on the images obtained during sampling test. Besides the cervical diagnostic system, the Neural Mammo system is developed to specifically aid the diagnosis of breast cancer using a fine needle aspiration image.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Effects of Heat Pipe Failures in Microreactors

Microreactors provide new opportunities for nuclear reactor applications given their long-lived fuel source, compact size, portability, reliability as it relates to safety and their self-regulating nature. To take advantage of these opportunities there are technological challenges that need to be overcome. One advancing technology often used in conjunction with microreactor designs are heat pipes, which are used for heat removal from the reactor core to the power conversion system. Heat pipes are a substitute for the traditional system in which the same fluid used as coolant in the reactor is then used as the working fluid in the power conversion system. This document describes how heat pipes operate, what happens when a heat pipe fails, and what codes can be used to simulate the results. Our analyses show that a single/double heat pipe failure results in a temperature increase of 15-50°C respectively in surrounding heat pipes. Heat pipe microreactors could be easily designed such that this increase is within the maximum parameters allowable for safety and does not result in cascading heat pipe failure. Thus, such failures do not lead to severe degradation of the reactor.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2016

A scintillator-based approach to monitor secondary neutron production during proton therapy

Here, the primary objective of this work is to measure the secondary neutron field produced by an uncollimated proton pencil beam impinging on different tissue-equivalent phantom materials using organic scintillation detectors. Additionally, the Monte Carlo code mcnpx-PoliMi was used to simulate the detector response for comparison to the measured data. Comparison of the measured and simulated data will validate this approach for monitoring secondary neutron dose during proton therapy. Proton beams of 155- and 200-MeV were used to irradiate a variety of phantom materials and secondary particles were detected using organic liquid scintillators. These detectors are sensitive to fast neutrons and gamma rays: pulse shape discrimination was used to classify each detected pulse as either a neutron or a gamma ray. The mcnpx-PoliMi code was used to simulate the secondary neutron field produced during proton irradiation of the same tissue-equivalent phantom materials. As a result, an experiment was performed at the Loma Linda University Medical Center proton therapy research beam line and corresponding models were created using the mcnpx-PoliMi code. The authors’ analysis showed agreement between the simulations and the measurements. The simulated detector response can be used to validate the simulations of neutron and gamma doses on a particular beam line with or without a phantom. In conclusion, the authors have demonstrated a method of monitoring the neutron component of the secondary radiation field produced by therapeutic protons. The method relies on direct detection of secondary neutrons and gamma rays using organic scintillation detectors. These detectors are sensitive over the full range of biologically relevant neutron energies above 0.5 MeV and allow effective discrimination between neutron and photon dose. Because the detector system is portable, the described system could be used in the future to evaluate secondary neutron and gamma doses on various clinical beam lines for commissioning and prospective data collection in pediatric patients treated with proton therapy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Porting HEP Parameterized Calorimeter Simulation Code to GPUs

The High Energy Physics (HEP) experiments, such as those at the Large Hadron Collider (LHC), traditionally consume large amounts of CPU cycles for detector simulations and data analysis, but rarely use compute accelerators such as GPUs. As the LHC is upgraded to allow for higher luminosity, resulting in much higher data rates, purely relying on CPUs may not provide enough computing power to support the simulation and data analysis needs. As a proof of concept, we investigate the feasibility of porting a HEP parameterized calorimeter simulation code to GPUs. We have chosen to use FastCaloSim, the ATLAS fast parametrized calorimeter simulation. While FastCaloSim is sufficiently fast such that it does not impose a bottleneck in detector simulations overall, significant speed-ups in the processing of large samples can be achieved from GPU parallelization at both the particle (intra-event) and event levels; this is especially beneficial in conditions expected at the high-luminosity LHC, where extremely high per-event particle multiplicities will result from the many simultaneous proton-proton collisions. We report our experience with porting FastCaloSim to NVIDIA GPUs using CUDA. A preliminary Kokkos implementation of FastCaloSim for portability to other parallel architectures is also described.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2011

Automatic Parallelization of Numerical Python Applications using the Global Arrays Toolkit

Global Arrays is a software system from Pacific Northwest National Laboratory that enables an efficient, portable, and parallel shared-memory programming interface to manipulate distributed dense arrays. The NumPy module is the de facto standard for numerical calculation in the Python programming language, a language whose use is growing rapidly in the scientific and engineering communities. NumPy provides a powerful N-dimensional array class as well as other scientific computing capabilities. However, like the majority of the core Python modules, NumPy is inherently serial. Using a combination of Global Arrays and NumPy, we have reimplemented NumPy as a distributed drop-in replacement called Global Arrays in NumPy (GAiN). Serial NumPy applications can become parallel, scalable GAiN applications with only minor source code changes. Scalability studies of several different GAiN applications will be presented showing the utility of developing serial NumPy codes which can later run on more capable clusters or supercomputers.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

To Exascale and Beyond—The Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM), a Performance Portable Global Atmosphere Model for Cloud-Resolving Scales

The new generation of heterogeneous CPU/GPU computer systems offer much greater computational performance but are not yet widely used for climate modeling. One reason for this is that traditional climate models were written before GPUs were available and would require an extensive overhaul to run on these new machines. In addition, even conventional “high–resolution” simulations don't currently provide enough parallel work to keep GPUs busy, so the benefits of such overhaul would be limited for the types of simulations climate scientists are accustomed to. The vision of the Simple Cloud-Resolving Energy Exascale Earth System (E3SM) Atmosphere Model (SCREAM) project is to create a global atmospheric model with the architecture to efficiently use GPUs and horizontal resolution sufficient to fully take advantage of GPU parallelism. After 5 years of model development, SCREAM is finally ready for use. In this paper, we describe the design of this new code, its performance on both CPU and heterogeneous machines, and its ability to simulate real-world climate via a set of four 40 day simulations covering all 4 seasons of the year.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Stochastic Modeling of Radioactive Material Releases

Nonreactor nuclear facilities operated under the approval authority of the U.S. Department of Energy use unmitigated hazard evaluations to determine if potential radiological doses associated with design basis events challenge or exceed dose evaluation guidelines. Unmitigated design basis events that sufficiently challenge dose evaluation guidelines or exceed the guidelines for members of the public or workers, merit selection of safety structures, systems, or components or other controls to prevent or mitigate the hazard. Idaho State University, in collaboration with Idaho National Laboratory, has developed a portable and simple to use software application called SODA (Stochastic Objective Decision-Aide) that stochastically calculates the radiation dose associated with hypothetical radiological material release scenarios. Rather than producing a point estimate of the dose, SODA produces a dose distribution result to allow a deeper understanding of the dose potential. SODA allows users to select the distribution type and parameter values for all of the input variables used to perform the dose calculation. SODA then randomly samples each distribution input variable and calculates the overall resulting dose distribution. In cases where an input variable distribution is unknown, a traditional single point value can be used. SODA was developed using the MATLAB coding framework. The software application has a graphical user input. SODA can be installed on both Windows and Mac computers and does not require MATLAB to function. SODA provides improved risk understanding leading to better informed decision making associated with establishing nuclear facility material-at-risk limits and safety structure, system, or component selection. It is important to note that SODA does not replace or compete with codes such as MACCS or RSAC, rather it is viewed as an easy to use supplemental tool to help improve risk understanding and support better informed decisions. The work was funded through a grant from the DOE Nuclear Safety Research and Development Program.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2024

Performance Results on CPU/GPU Exascale Architectures for OMEGA: The Ocean Model for E3SM Global Applications

The US Department of Energy (DOE) conducts climate simulations on some of the world’s largest supercomputers. These exascale machines use heterogeneous architectures with both CPUs and GPUs, and scientific codes must adapt to make full use of this computing power. Los Alamos National Lab is developing Omega: The Ocean Model for E3SM Global Applications, which is specifically designed for modern exascale computers. It uses external libraries that have been optimized for a variety of architectures to run on different supercomputers. Omega is an unstructured-mesh ocean model based on TRiSK numerical methods. It will be the new ocean component of the DOE’s Energy Exascale Earth System Model (E3SM). The algorithms in Omega follow those of the current ocean component, MPAS-Ocean, but it will be written in C++ rather than Fortran to take advantage of the Kokkos performance portability library. Omega spatial operators are written as Kokkos kernels to run efficiently on both CPUs and GPUs. Work on Omega began in 2023 with a new C++ framework for unstructured mesh partitioning, halo exchanges, parallel IO, and Kokkos interfaces. The current version, Omega-0, is being developed to solve the shallow water equations and at present includes all of the tendency terms but not time stepping. Here we share the results of Omega-0 verification and performance testing. Verification includes unit tests implemented with CTest as well as convergence tests in Polaris, an in-house python package with a large suite of test problems. Performance tests compare simulations conducted on CPUs versus GPUs and across different architectures: tests are run on Frontier, which has AMD “Optimized 3rd Gen EPYC” CPUs and AMD MI250X GPUs, as well as Perlmutter, which is composed of AMD EPYC 7763 CPUs and NVIDIA A100 GPUs.

58 GEOSCIENCES↗

DOE OSTI2013

Compositional Dataflow Via Abstract Transition Systems

Despite decades of research and development of dataflow analyses within dozens of different compiler infrastructures, analysis of real programs is intractable in practice. The reason is that although a single research group is equipped to model a single well-defined aspect of application behavior, application developers use a very wide range of abstractions and coding techniques within a single application. Since to analyze even a single application all of its complexities must be modeled, researchers must combine analyses from multiple groups into comprehensive analysis frameworks such as OpenAnalysis or LLVM. Analysis composition is expensive in practice, requiring development effort that is quadratic in the number of analyses as well as tight inter-group coordination to maintain consistent APIs to each other’s symbolic abstractions. This paper proposes an approach to building compiler analysis frameworks that simplifies the composition of independently-developed analyses. It formalizes the operation of dataflow analyses in a way that simplifies reasoning about various types of analysis composition. Further, it defines a portable abstraction that can represent the results of many real analyses, making it possible for different analyses to leverage each other’s results with no knowledge of their APIs or internal abstractions and without any coordination between the groups that developed them. We have developed the Fuse compositional analysis framework based on this abstraction, and integrated it in the ROSE [15] compilation system. Our experience is that this approach greatly simplifies composition of program analyses, making it easy to tailor different combinations of program analyses to different input programs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Portable self-contained pressure testing manifold and associated methods

A portable, case-enclosed pressure test manifold, configured to support both pneumatic and hydrostatic pressure testing, and comprising a downstream fluid path (e.g., a system test gauge, a ball valve, a system test port, a system relief valve, and other components/piping) and an upstream fluid path (e.g., a low-pressure gauge, a high-pressure gauge, and other components/piping). A regulator and/or the ball valve selectively operate the downstream fluid path, defining a hydrostatic pressure testing path, to receive a liquid; and the upstream fluid path in combination with the downstream fluid path, defining a pneumatic pressure testing path, to receive a gas. Manifold components are pressure rated based on use and are ASME Code B31.3 compliant. A flexible hose connects with either of the pneumatic pressure testing path and the hydrostatic pressure testing path of the manifold. The case includes parking receptables and a carrying handle configured to stow the hose during transport.

Milholland, Roger A.↗

DOE OSTI2020

Three dimensions, two microscopes, one code: Automatic differentiation for x-ray nanotomography beyond the depth of focus limit

Conventional tomographic reconstruction algorithms assume that one has obtained pure projection images, involving no within-specimen diffraction effects nor multiple scattering. Advances in x-ray nanotomography are leading toward the violation of these assumptions, by combining the high penetration power of x-rays, which enables thick specimens to be imaged, with improved spatial resolution that decreases the depth of focus of the imaging system. We describe a reconstruction method where multiple scattering and diffraction effects in thick samples are modeled by multislice propagation and the 3D object function is retrieved through iterative optimization. We show that the same proposed method works for both full-field microscopy and for coherent scanning techniques like ptychography. Our implementation uses the optimization toolbox and the automatic differentiation capability of the open-source deep learning package TensorFlow, demonstrating a straightforward way to solve optimization problems in computational imaging with flexibility and portability.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Western States Building Energy & Controls Apprenticeship (BECA) Program

How does this project help to understand the challenges of workforce development in the commercial building energy management industry? The purpose of this project was to create a replicable, scalable, and portable apprenticeship program for building energy management and controls. This paper will demonstrate how local processes can be more adaptable and inclusive than federal processes in achieving workforce development goals. Our work provides insights into the technical effectiveness of the program, enabling others to achieve greater success in their workforce development initiatives. The project required more time and financial resources than initially anticipated and spent a year in a no-cost extension working to accomplish the Statement of Project Objectives. The original goal was to create an Industry Related Apprenticeship Program (IRAP). The development of this apprenticeship presented challenges due to the lack of existing programs for reference and the absence of relevant industry classification codes by the Department of Labor (DOL). Notably, the role of a commercial building energy analyst is not recognized by the DOL. The SIC (industry codes) do not have a good description of this job. There are many that may fall into related categories, but none are the actual duties of an energy analyst. Discussions with the DOL indicated that substantial groundwork was necessary before a national apprenticeship program could be implemented, causing delays in the program’s commencement. As a result, students experienced longer wait times before starting their apprenticeship component. The apprenticeship program officially launched on September 14, 2021. The success of the State of Oregon’s apprenticeship program, the first of its kind in the state, underscored the flexibility and effectiveness of local initiatives compared to federal efforts. The COVID-19 pandemic also significantly impacted the project’s success. Beginning in March 2020, the pandemic led to widespread closures of schools and colleges by fall 2020. By September 2021, when the apprenticeship option became available, enrollment in colleges and universities nationwide had decreased, affecting student participation in the program. Moreover, as employers transitioned their employees to remote work, there was limited interaction with external personnel, influencing the willingness of training agents (employers) to integrate additional workers into their teams. This paper addresses several challenges encountered during the project, with the hope that future workforce development efforts will benefit from these experiences. We Final Technical Report 4 | Page encourage others to engage with state and federal agencies to enhance and update pathways for workforce development and apprenticeship programs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2018

PyFly: A fast, portable aerodynamics simulator

Here, we present a fast, user-friendly implementation of a potential flow solver based on the unsteady vortex lattice method (UVLM), namely PyFly. UVLM computes the aerodynamic loads applied on lifting surfaces while capturing the unsteady effects such as the added mass forces, the growth of bound circulation, and the wake while assuming that the flow separation location is known a priori. This method is based on discretizing the body surface into a lattice of vortex rings and relies on the Biot–Savart law to construct the velocity field at every point in the simulated domain. We introduce the pointwise approximation approach to simulate the interactions of the far-field vortices to overcome the computational burden associated with the classical implementation of UVLM. The computational framework uses the Python programming language to provide an easy to handle user interface while the computational kernels are written in Fortran. The mixed language approach enables high performance regarding solution time and great flexibility concerning easiness of code adaptation to different system configurations and applications. The computational tool predicts the unsteady aerodynamic behavior of multiple moving bodies (e.g., flapping wings, rotating blades, suspension bridges) subject to incoming air. The aerodynamic simulator can also deal with enclosure effects, multi-body interactions, and B-spline representation of body shapes. Finally, we simulate different aerodynamic problems to illustrate the usefulness and effectiveness of PyFly.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Improving the Field Portability of Neutron and Gamma Counting Techniques

Savannah River National Laboratory (SRNL) puts science to work by developing techniques that better meet customers needs for in-situ measurements. There is high demand for laboratory quality measurements in field situations, improving the cost and speed for first responders and environmental monitoring. This work focused on two improvements (1) reading a signal from a neutron detector using a Raspberry Pi (2) testing the Peak-to-Valley method for determining the depth of a source in soil contamination measurements. A Raspberry Pi is a cheap, compact computer. This affordable, compact computer is able to do simple tasks that a desktop computer is able to do, like spreadsheets, browse the internet, play games and even program a simple robot. Additionally, a Raspberry Pi can run off of a battery, so it could be deployed for long term measurements in adverse conditions like neutron monitors deployed in a shipping port. Using the Raspberry Pi and libraries easily accessible on the internet, a code was written in Python that allows the Pi to keep track of how many times a button is pushed. This work will be used with the future goal of creating low power-budget neutron detectors. 1) Make sure Python was correctly installed on the Raspberry Pi. 2) Write a code that will keep track of how many times a button connected to the Pi is pressed. A code was written to use the Raspberry Pi to count the number of times the button was pushed. Moving forward the Raspberry Pi will be tested with a neutron counter. Ideally, each signal from the neutron pulse will be equivalent of 'push the button' and be counted. In the characterization of a soil contamination area both the location and the depth of the source is important. Attenuation of the source by the soil can make determining its depth challenging, particularly for monoenergetic radionuclides like Cs-137. To address this issue, a method of calculating the 'peak-to-valley' ratio of the gamma count spectra is implemented to help calculate the known depth of the source. 1) Determine the 'peak-to-valley' ratio of a Cs-137 source at different depths. 2) Find an appropriate function to serve as a model for the peak-to-valley ratio as a function of depth. Several Petri dishes, filled with sand, were stacked with one containing a Cs-137 source. The individual Petri dishes allowed for the source to be placed at different depths. A bucket was placed over the sand and source, to keep the detector at a consistent height. A Petri dish containing a Eu-155 source, which acted as an internal calibration standard, was placed on top of the bucket. A NaI detector was place on top of the Eu-155 source and the assembly was surrounded by a tungsten shield. Count times were 20 minutes and the data was analyzed using PeakEasy. Data was recorded for Cs-137 at a series of depths in sand. Both exponential and logarithmic functions provided a reasonable fit to the data. The experimental data showed a decreasing 'peak-to-valley' ratio as the depth was increased. The next steps for this project involves determining the optimum fit function and combining the results from sand to different soil types to get a better representation of the soil found at SRS. Eventually, the peak-to-valley ratio will be used to estimate the depth of contamination in field measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2012

Science Campaign-1 Pulsed Power Efforts [Slides]

The PHELIX portable pulsed-power driver is discussed. It is composed of two air-insulated, single Marx modules capable of storing 300 kJ of electrical energy. The Marx are cable coupled to a toroidal transformer with a 4:1 winding ratio. The experimental load is located at the center of the transformer. The components are mounted in a 8’x10’x18’ boxcar which can be moved in and out of the beam line at the LANL proton radiography facility and prevents EMI within the facility. PHELIX has successfully completed two liner implosion experiments with full diagnostic return from flash X-ray imaging, optical Faraday load current, and multi-channel PDV. Computational modeling with both the legacy 1D MHD code RAVEN and the LANL ASC-LAP FLAG code show good agreement with data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

autoGEMM: Pushing the Limits of Irregular Matrix Multiplication on Arm Architectures

This paper presents an open-source library that pushes the limits of performance portability for irregular General Matrix Multiplication (GEMM) on the widely-used Arm architectures. Our library, autoGEMM, is designed to support a wide range of Arm processors: from edge devices to HPC-grade CPUs. autoGEMM generates optimized kernels for various hardware configurations by auto-combining fragments of autogenerated micro-kernels that employ hand-written optimizations to maximize computational efficiency. We optimize the kernel pipeline by tuning the register reuse and the data load/store overlapping. In addition, we use a dynamic tiling scheme to generate balanced tile shapes. Finally, we position autoGEMM on top of the TVM framework where our dynamic tiling scheme prunes the search space for TVM to identify the optimal combination of parameters for code optimization. Evaluations on five different classes of Arm chips demonstrate the advantages of autoGEMM. For small matrices, autoGEMM achieves 98% of peak and up to 2.0x speedup over state-of-the-art libraries such as LIBXSMM and LibShalom. For irregular matrices (i.e. tall skinny and long rectangles), autoGEMM is 1.3-2.0x faster than widely-used libraries such as OpenBLAS and Eigen. autoGEMM is publicly available at: https://github.com/wudu98/autoGEMM.

Wu, Du↗

DOE OSTI2019

Parallel Computing for Module-Based Computational Experiment

Large-scale scientific code plays an important role in scientific researches. In order to facilitate module and element evaluation in scientific applications, we introduce a unit testing framework and describe the demand for module-based experiment customization. We then develop a parallel version of the unit testing framework to handle long-term simulations with a large amount of data. Specifically, we apply message passing based parallelization and I/O behavior optimization to improve the performance of the unit testing framework and use profiling result to guide the parallel process implementation. Finally, we present a case study on litter decomposition experiment using a standalone module from a large-scale Earth System Model. This case study is also a good demonstration on the scalability, portability, and high-efficiency of the framework.

Yao, Zhuo↗