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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.

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At least 145 records · Page 8

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Asynchronous distributed-memory task-parallel algorithm for compressible flows on unstructured 3D Eulerian grids

Here, we discuss the implementation of a finite element method, used to numerically solve the Euler equations of compressible flows, using an asynchronous runtime system (RTS). The algorithm is implemented for distributed-memory machines, using stationary unstructured 3D meshes, combining data-, and task-parallelism on top of the Charm++ RTS. Charm++’s execution model is asynchronous by default, allowing arbitrary overlap of computation and communication. Task-parallelism allows scheduling parts of an algorithm independently of, or dependent on, each other. Built-in automatic load balancing enables continuous redistribution of computational load by migration of work units based on real-time CPU load measurement. The RTS also features automatic checkpointing, fault tolerance, resilience against hardware failure, and supports power-, and energy-aware computation. We demonstrate scalability up to 25 x 10 9 cells at $\mathscr{O}$10 4 compute cores and the benefits of automatic load balancing for irregular workloads. The full source code with documentation is available at https://quinoacomputing.org.

42 ENGINEERING↗

DOE OSTI2014

Region templates: Data representation and management for high-throughput image analysis

Compartment fires exhibit unique features associated with smoke accumulation and restricted air ventilation. The objective of the present study is to evaluate the ability of CFD-based fire models to simulate these features and in particular the effects of flame extinction that results from under-ventilated fire conditions. The study is performed using FireFOAM; FireFOAM is an advanced fire modeling software developed by FM Global and is based on a general-purpose open-source software called OpenFOAM. A new flame extinction model based on the concept of a critical value of the flame Damköhler number is incorporated into FireFOAM. The performance of the extinction model is evaluated via comparisons with a previously developed experimental database corresponding to a reduced-scale, heptane-fueled, compartment fire configuration. The numerical simulations also include a description of fuel evaporation driven by the computed gas-to-liquid heat feedback. Comparisons between experimental data and numerical results provide a suitable test bed to evaluate the ability of CFD-based fire models to describe the transition from over- to under-ventilated fire conditions, as well as the transition from extinction-free conditions to conditions in which the flame experiences partial or total quenching.

Energy & Fuels↗

DOE OSTI2019

An Evaluation of An Asynchronous Task Based Dataflow Approach For Uintah

The challenge of running complex physics code on the largest computers available has led to dataflow paradigms being explored. While such approaches are often applied at smaller scales, the challenge of extreme-scale data flow computing remains. The Uintah dataflow framework has consistently used dataflow computing at the largest scales on complex physics applications. At present Uintah contains two main dataflow models. Both are based upon asynchronous communication. One uses a static graph-based approach with asynchronous communication and the other uses a more dynamic approach that was introduced almost a decade ago. Subsequent changes within the Uintah runtime system combined with many more large scale experiments, has necessitated a reevaluation of these two approaches, comparing them in the context of large scale problems. While the static approach has worked well for some large-scale simulations, the dynamic approach is seen to offer performance improvements over the static case for a challenging fluid-structure interaction problem at large scale that involves fluid flow and a moving solid represented using particle method on an adaptive mesh.

Humphrey, Alan↗

DOE OSTI2017

Aces4: A Platform for Computational Chemistry Calculations with Extremely Large Block-Sparse Arrays

Aces4 is a parallel programming platform comprising a DSL for Computational Chemistry and its runtime system. It offers a convenient way to express parallelism together with extensive support for extremely large, possibly sparse, distributed arrays. It aids scientists in the creation of performant, scalable, massively parallel programs that can effectively take advantage of leadership class computing systems to address important scientific questions. Aces4 has enabled the development and implementation of new methods in electronic structure theory which are breaking new ground in their ability to perform highly accurate calculations on ever larger molecular systems. In this paper the design of Aces4, which is based on the the Super Instruction Architecture approach, is described. Experimental scaling results for Molecular Cluster Perturbation Theory, a new method enabled by Aces4, and CCSD, a widely used computational chemistry method are given.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Analysis of Threading Libraries for High Performance Computing

With the appearance of multi-/many core machines, applications and runtime systems have evolved in order to exploit the new on-node concurrency brought by new software paradigms. POSIX threads (Pthreads) was widely-adopted for that purpose and it remains as the most used threading solution in current hardware. Lightweight thread (LWT) libraries emerged as an alternative offering lighter mechanisms to tackle the massive concurrency of current hardware. In this article, we analyze in detail the most representative threading libraries including Pthread- and LWT-based solutions. In addition, to examine the suitability of LWTs for different use cases, we develop a set of microbenchmarks consisting of OpenMP patterns commonly found in current parallel codes, and we compare the results using threading libraries and OpenMP implementations. Moreover, we study the semantics offered by threading libraries in order to expose the similarities among different LWT application programming interfaces and their advantages over Pthreads. This article exposes that LWT libraries outperform solutions based on operating system threads when tasks and nested parallelism are required.

GLT↗

DOE OSTI2013

CONRAD—A software framework for cone-beam imaging in radiology

Purpose: In the community of x-ray imaging, there is a multitude of tools and applications that are used in scientific practice. Many of these tools are proprietary and can only be used within a certain lab. Often the same algorithm is implemented multiple times by different groups in order to enable comparison. In an effort to tackle this problem, the authors created CONRAD, a software framework that provides many of the tools that are required to simulate basic processes in x-ray imaging and perform image reconstruction with consideration of nonlinear physical effects.Methods: CONRAD is a Java-based state-of-the-art software platform with extensive documentation. It is based on platform-independent technologies. Special libraries offer access to hardware acceleration such as OpenCL. There is an easy-to-use interface for parallel processing. The software package includes different simulation tools that are able to generate up to 4D projection and volume data and respective vector motion fields. Well known reconstruction algorithms such as FBP, DBP, and ART are included. All algorithms in the package are referenced to a scientific source.Results: A total of 13 different phantoms and 30 processing steps have already been integrated into the platform at the time of writing. The platform comprises 74.000 nonblank lines of code out of which 19% are used for documentation. The software package is available for download at http://conrad.stanford.edu. To demonstrate the use of the package, the authors reconstructed images from two different scanners, a table top system and a clinical C-arm system. Runtimes were evaluated using the RabbitCT platform and demonstrate state-of-the-art runtimes with 2.5 s for the 256 problem size and 12.4 s for the 512 problem size.Conclusions: As a common software framework, CONRAD enables the medical physics community to share algorithms and develop new ideas. In particular this offers new opportunities for scientific collaboration and quantitative performance comparison between the methods of different groups.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2016

Quinoa, Version 0.1

Quinoa is a set of computational tools that enables research and numerical analysis in fluid dynamics. At this time it is a test-bed to experiment with various algorithms using fully asynchronous runtime systems.

Bakosi, Jozsef↗

DOE OSTI2021

High Performance Approximate Computing

This code repository contains the implementation of the "High-Performance Approximate Computing" (HPAC) toolkit. The toolkit allows you to approximate your own C/C++. The developer uses "pragma's" to annotate code regions as approximate. The compiler extensions lower these pragmas to either compiletime approximate techniques or runtime approximation techniques. At execution time, the implemented runtime system decides which annotated regions it should approximate. HPAC also provides a set of script utilities. The utilities perform a grid search within approximation parameters and performance. The user can analyze the raw data to identify optimal approximation techniques for the application.

Parasyris, Konstantinos↗

DOE OSTI2018

pnnl/gmt

Global Memory and Threading runtime system

Minutoli, Marco↗

DOE OSTI2019

pnnl/ARTS

Abstract RunTime System (ARTS) aims to provide different levels of abstraction that trade-off performance and programmability and helps to connect upper layers of the software stack with the different computational substrates.

Manzano Franco, Joseph↗

DOE OSTI2013

Exascale Co-Design Center for Materials in Extreme Environments (ExMatEx) Annual Report — Year 2

All activities of the Exascale Co-design Center for Materials in Extreme Environments (ExMatEx) are focused on the two ultimate goals of the project: (1) demonstrating and delivering a prototype scale-bridging materials science application based upon adaptive physics refinement, and (2) identifying the requirements for the exascale ecosystem that are necessary to perform computational materials science simulations (both single- and multi-scale). During the first year of ExMatEx, our focus was on establishing how we do computational materials science, by developing an initial suite of flexible proxy applications. These “proxy apps” are the primary vehicle for the co-design process, involving assessments and tradeoff evaluations both within the ExMatEx team, and with the entire exascale ecosystem. These interactions have formed the basis of our second year activities. The set of artifacts from these co-design interactions are the lessons learned, that are used to re-express the applications and algorithms within the context of emerging architectures, programming models, and runtime systems.

36 MATERIALS SCIENCE↗

DOE OSTI2013

Exascale Co-Design Center for Materials in Extreme Environments (ExMatEx) Annual Report - Year 2

All activities of the Exascale Co-design Center for Materials in Extreme Environments (Ex- MatEx) are focused on the two ultimate goals of the project: (1) demonstrating and delivering a prototype scale-bridging materials science application based upon adaptive physics refinement, and (2) identifying the requirements for the exascale ecosystem that are necessary to perform computational materials science simulations (both single- and multi-scale). During the first year of ExMatEx, our focus was on establishing how we do computational materials science, by developing an initial suite of flexible proxy applications. These “proxy apps” are the primary vehicle for the co-design process, involving assessments and tradeoff evaluations both within the ExMatEx team, and with the entire exascale ecosystem. These interactions have formed the basis of our second year activities. The set of artifacts from these co-design interactions are the lessons learned, that are used to re-express the applications and algorithms within the context of emerging architectures, programming models, and runtime systems.

36 MATERIALS SCIENCE↗

DOE OSTI2016

Functional Programming in Computer Science

We explore functional programming through a 16-week internship at Los Alamos National Laboratory. Functional programming is a branch of computer science that has exploded in popularity over the past decade due to its high-level syntax, ease of parallelization, and abundant applications. First, we summarize functional programming by listing the advantages of functional programming languages over the usual imperative languages, and we introduce the concept of parsing. Second, we discuss the importance of lambda calculus in the theory of functional programming. Lambda calculus was invented by Alonzo Church in the 1930s to formalize the concept of effective computability, and every functional language is essentially some implementation of lambda calculus. Finally, we display the lasting products of the internship: additions to a compiler and runtime system for the pure functional language STG, including both a set of tests that indicate the validity of updates to the compiler and a compiler pass that checks for illegal instances of duplicate names.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Comfort in High-Performance Homes in a Hot-Humid Climate

IBACOS monitored 37 homes during the late summer and early fall of 2014 in a hot and humid climate to better understand indoor comfort conditions. These homes were constructed in the last several years by four home builders that offered a comfort and performance guarantee for the homes. The homes were located in one of four cities: Tampa, Florida; Orlando, Florida; Houston, Texas; and San Antonio, Texas. Temperature and humidity data were collected from the thermostat and each room of the house using small, battery-powered data loggers. To understand system runtime and its impact on comfort, supply air temperature also was measured on a 1-minute interval. Overall, the group of homes only exceeded a room-to-room temperature difference of 6 degrees Fahrenheit for 5% of the time.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2016

Programming Models in HPC

These are the slides for a presentation on programming models in HPC, at the Los Alamos National Laboratory's Parallel Computing Summer School. The following topics are covered: Flynn's Taxonomy of computer architectures; single instruction single data; single instruction multiple data; multiple instruction multiple data; address space organization; definition of Trinity (Intel Xeon-Phi is a MIMD architecture); single program multiple data; multiple program multiple data; ExMatEx workflow overview; definition of a programming model, programming languages, runtime systems; programming model and environments; MPI (Message Passing Interface); OpenMP; Kokkos (Performance Portable Thread-Parallel Programming Model); Kokkos abstractions, patterns, policies, and spaces; RAJA, a systematic approach to node-level portability and tuning; overview of the Legion Programming Model; mapping tasks and data to hardware resources; interoperability: supporting task-level models; Legion S3D execution and performance details; workflow, integration of external resources into the programming model.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Scalability of Several Asynchronous Many-Task Models for In Situ Statistical Analysis.

This report is a sequel to [PB16], in which we provided a first progress report on research and development towards a scalable, asynchronous many-task, in situ statistical analysis engine using the Legion runtime system. This earlier work included a prototype implementation of a proposed solution, using a proxy mini-application as a surrogate for a full-scale scientific simulation code. The first scalability studies were conducted with the above on modestly-sized experimental clusters. In contrast, in the current work we have integrated our in situ analysis engines with a full-size scientific application (S3D, using the Legion-SPMD model), and have conducted nu- merical tests on the largest computational platform currently available for DOE science ap- plications. We also provide details regarding the design and development of a light-weight asynchronous collectives library. We describe how this library is utilized within our SPMD- Legion S3D workflow, and compare the data aggregation technique deployed herein to the approach taken within our previous work.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Enabling Diverse Software Stacks on Supercomputers using High Performance Virtual Clusters.

While large-scale simulations have been the hallmark of the High Performance Computing (HPC) community for decades, Large Scale Data Analytics (LSDA) workloads are gaining attention within the scientific community not only as a processing component to large HPC simulations, but also as standalone scientific tools for knowledge discovery. With the path towards Exascale, new HPC runtime systems are also emerging in a way that differs from classical distributed com- puting models. However, system software for such capabilities on the latest extreme-scale DOE supercomputing needs to be enhanced to more appropriately support these types of emerging soft- ware ecosystems. In this paper, we propose the use of Virtual Clusters on advanced supercomputing resources to enable systems to support not only HPC workloads, but also emerging big data stacks. Specifi- cally, we have deployed the KVM hypervisor within Cray's Compute Node Linux on a XC-series supercomputer testbed. We also use libvirt and QEMU to manage and provision VMs directly on compute nodes, leveraging Ethernet-over-Aries network emulation. To our knowledge, this is the first known use of KVM on a true MPP supercomputer. We investigate the overhead our solution using HPC benchmarks, both evaluating single-node performance as well as weak scaling of a 32-node virtual cluster. Overall, we find single node performance of our solution using KVM on a Cray is very efficient with near-native performance. However overhead increases by up to 20% as virtual cluster size increases, due to limitations of the Ethernet-over-Aries bridged network. Furthermore, we deploy Apache Spark with large data analysis workloads in a Virtual Cluster, ef- fectively demonstrating how diverse software ecosystems can be supported by High Performance Virtual Clusters.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

LLVM Infrastructure and Tools Project Summary

This project works with the open source LLVM Compiler Infrastructure (http://llvm.org) to provide tools and capabilities that address needs and challenges faced by ECP community (applications, libraries, and other components of the software stack). Our focus is on providing a more productive development environment that enables (i) improved compilation times and code generation for parallelism, (ii) additional features/capabilities within the design and implementations of LLVM components for improved platform/performance portability and (iii) improved aspects related to composition of the underlying implementation details of the programming environment, capturing resource utilization, overheads, etc. -- including runtime systems that are often not easily addressed by application and library developers.

97 MATHEMATICS AND COMPUTING↗