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DOE OSTI2014

UPC++

UPC++ is a Partitioned Global Address Space (PGAS) extension for C++, with three main objectives: 1) to provide an object-oriented PGAS programming model in the context of the popular C++ language; 2) to add useful parallel programming idioms unavailable in UPC, such as asynchronous remote function invocation and multidimensional arrays, to support complex scientific applications; 3) to offer an easy on-ramp to PGAS programming through interoperability with other existing parallel programming systems (e.g., MPI, OpenMP, CUDA). UPC++ includes two main features beyond UPC: 1) One of the major limitations of UPC in the context of DOE application is the relatively weak notion of multidimensional arrays, which it inherited from C. To remedy this problem in UPC++, we included a multidimensional domain and array library based on that of Titanium. Titanium's library is similar to Chapel's dense and strided domains, as both were inspired by the dense and strided regions and arrays in ZPL. 2) Another feature provided by UPC++ but not by UPC is remote function invocation, which is inspired by Phalanx, X10, Habanero-C, and C++11. The user may start an asynchronous remote function invocation with the following syntax: "async(place)(function, args...);". UPC++ provides two programming constructs for specifying dynamic dependencies among tasks: 1) event-driven execution as in Phalanx and Habanero-C; 2) finish-async as in X10. We implemented UPC++ with a "compiler-free" approach using C++ templates and runtime libraries. The UPC++ front-end consists of a set of C++ header files that enables the C++ compiler to "translate" UPC++ features in a user program to runtime library calls. In particular, we use templates and operator overloading to customize the behavior of UPC++ types. This software package has been replaced with UPCC++ V 1.0

Amir Kamil, YiliZheng↗

DOE OSTI2017

Evaluation of the OpenCL AES Kernel using the Intel FPGA SDK for OpenCL

The OpenCL standard is an open programming model for accelerating algorithms on heterogeneous computing system. OpenCL extends the C-based programming language for developing portable codes on different platforms such as CPU, Graphics processing units (GPUs), Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs). The Intel FPGA SDK for OpenCL is a suite of tools that allows developers to abstract away the complex FPGA-based development flow for a high-level software development flow. Users can focus on the design of hardware-accelerated kernel functions in OpenCL and then direct the tools to generate the low-level FPGA implementations. The approach makes the FPGA-based development more accessible to software users as the needs for hybrid computing using CPUs and FPGAs are increasing. It can also significantly reduce the hardware development time as users can evaluate different ideas with high-level language without deep FPGA domain knowledge. In this report, we evaluate the performance of the kernel using the Intel FPGA SDK for OpenCL and Nallatech 385A FPGA board. Compared to the M506 module, the board provides more hardware resources for a larger design exploration space. The kernel performance is measured with the compute kernel throughput, an upper bound to the FPGA throughput. The report presents the experimental results in details. The Appendix lists the kernel source code.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Evaluation of CHO Benchmarks on the Arria 10 FPGA using Intel FPGA SDK for OpenCL

The OpenCL standard is an open programming model for accelerating algorithms on heterogeneous computing system. OpenCL extends the C-based programming language for developing portable codes on different platforms such as CPU, Graphics processing units (GPUs), Digital Signal Processors (DSPs) and Field Programmable Gate Arrays (FPGAs). The Intel FPGA SDK for OpenCL is a suite of tools that allows developers to abstract away the complex FPGA-based development flow for a high-level software development flow. Users can focus on the design of hardware-accelerated kernel functions in OpenCL and then direct the tools to generate the low-level FPGA implementations. The approach makes the FPGA-based development more accessible to software users as the needs for hybrid computing using CPUs and FPGAs are increasing. It can also significantly reduce the hardware development time as users can evaluate different ideas with high-level language without deep FPGA domain knowledge. Benchmarking of OpenCL-based framework is an effective way for analyzing the performance of system by studying the execution of the benchmark applications. CHO is a suite of benchmark applications that provides support for OpenCL [1]. The authors presented CHO as an OpenCL port of the CHStone benchmark. Using Altera OpenCL (AOCL) compiler to synthesize the benchmark applications, they listed the resource usage and performance of each kernel that can be successfully synthesized by the compiler. In this report, we evaluate the resource usage and performance of the CHO benchmark applications using the Intel FPGA SDK for OpenCL and Nallatech 385A FPGA board that features an Arria 10 FPGA device. The focus of the report is to have a better understanding of the resource usage and performance of the kernel implementations using Arria-10 FPGA devices compared to Stratix-5 FPGA devices. In addition, we also gain knowledge about the limitations of the current compiler when it fails to synthesize a benchmark application.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Experimental Design and Laboratory Characterization of a Medium- and High-Efficiency Rooftop Unit for use in Building Energy Simulations

Commercial rooftop units that incorporate variable speed components are quickly entering into the market place; however, the design and modeling tools that calculate the energy benefits of these units cannot properly estimate performance. This is due to two factors: 1) There are insufficient measured performance data of real systems that can be entered into these simulations, and 2) building energy simulators are unable to properly interpret performance data. Therefore, publicly available datasets designed to encompass the entire performance map coupled with control sequence information are needed as inputs for these modelling programs to accurately estimate energy savings and promote variable speed RTUs. As part of the Verification and Uncertainty Characterization for Energy Simulation milestone funded by the Department of Energy, the National Renewable Energy Laboratory recorded and published data across the entire performance range for two commercially available RTUs; one with a two-stage compressor and variable speed supply fan, and another with a fully variable speed compressor, supply fan and condenser fan. This paper details 1) how the design of experiments was created as well as how the units were controlled, and 2) the operational limitations of the two units. The paper will also discuss methods for building energy simulation programs to properly interpret these data sets and integrate them into building energy simulation models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

RMACXX: An Efficient High-Level C++ Interface over MPI-3 RMA

Parallel scientific applications can benefit from de- coupling communication and synchronization. One-sided pro- gramming abstractions, which separate communication from syn- chronization, have in fact served as a motivation for partitioned global address space (PGAS) models. However, the use of PGAS models in application codes in a manner that fully exploits the benefit of these programming models requires significant development effort. Meanwhile, a vast majority of scientific codes already use the Message Passing Interface (MPI) and need convenient features to support application-specific one-sided communication scenarios. MPI Remote Memory Access (RMA) can be employed for this purpose. MPI is a low-level API, however, and developing applications with MPI RMA requires programmers to be well versed in its nuances. We present RMACXX, a compact set of C++ bindings to MPI-3 RMA, to ease the use of MPI RMA. Unlike other PGAS models, which may have interoperability issues with MPI, RMACXX is written on top of MPI and uses the same runtime as MPI. The basic functionality of RMACXX adds only a relatively small number of extra instructions (about 20) to the critical communication path. Moreover, RMACXX provides an intuitive API for building a wide variety of scientific applications while enjoying performance matching handwritten MPI-3 RMA codes.

MPI-3 RMA, one-sided communication, PGAS, C++, exp↗

DOE OSTI2014

New Software Architecture Options for the TCL Data Acquisition System

The Turbulent Combustion Laboratory (TCL) conducts research on combustion in turbulent flow environments. To conduct this research, the TCL utilizes several pulse lasers, a traversable wind tunnel, flow controllers, scientific grade CCD cameras, and numerous other components. Responsible for managing these different data-acquiring instruments and data processing components is the Data Acquisition (DAQ) software. However, the current system is constrained to running through VXI hardware—an instrument-computer interface—that is several years old, requiring the use of an outdated version of the visual programming language, LabVIEW. A new Acquisition System is being programmed which will borrow heavily from either a programming model known as the Current Value Table (CVT) System or another model known as the Server-Client System. The CVT System model is in essence, a giant spread sheet from which data or commands may be retrieved or written to, and the Server-Client System is based on network connections between a server and a client, very much like the Server-Client model of the Internet. Currently, the bare elements of a CVT DAQ Software have been implemented, consisting of client programs in addition to a server program that the CVT will run on. This system is being rigorously tested to evaluate the merits of pursuing the CVT System model and to uncover any potential flaws which may result in further implementation. If the CVT System is chosen, which is likely, then future work will consist of build up the system until enough client programs have been created to run the individual components of the lab. The advantages of such a System will be flexibility, portability, and polymorphism. Additionally, the new DAQ software will allow the Lab to replace the VXI with a newer instrument interface—the PXI—and take advantage of the capabilities of current and future versions of LabVIEW.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

DARMA 0.3.0-alpha Specification

In this document, we provide the specifications for DARMA (Distributed Asynchronous Resilient Models and Applications), a co-design research vehicle for asynchronous many-task (AMT) programming models that serves to: 1) insulate applications from runtime system and hardware idiosyncrasies, 2) improve AMT runtime programmability by co-designing an application programmer interface (API) directly with application developers, 3) synthesize application co-design activities into meaningful requirements for runtime systems, and 4) facilitate AMT design space characterization and definition, accelerating the development of AMT best practices.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

Flexible Computer Science Infrastructure (FleCSI)

FleCSI is a compile-time configurable framework designed to support multi-physics application development. As such, FleCSI attempts to provide a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. Current support includes multi-dimensional mesh topology, mesh geometry, and mesh adjacency information, n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures. FleCSI also introduces a functional programming model with control, execution, and data abstractions that are consistent with both MPI and state-of-the-art task-based runtimes such as Legion and Charm++. The FleCSI abstraction layer provides the developer with insulation from the underlying runtime, while allowing support for multiple runtime systems, including conventional models like asynchronous MPI. The intent is to give developers a concrete set of user-friendly programming tools that can be used now, while allowing flexibility in choosing runtime implementations and optimizations that can be applied to architectures and runtimes that arise in the future. The control and execution models in FleCSI also provide formal nomenclature for describing poorly understood concepts like kernels and tasks.

Moss, Nicholas↗

DOE OSTI2016

Flexible Computer Science Infrastructure (FleCSI)

Bergen, Ben↗

DOE OSTI2014

Scaling Irregular Applications through Data Aggregation and Software Multithreading

Bioinformatics, data analytics, semantic databases, knowledge discovery are emerging high performance application areas that exploit dynamic, linked data structures such as graphs, unbalanced trees or unstructured grids. These data structures usually are very large, requiring significantly more memory than available on single shared memory systems. Additionally, these data structures are difficult to partition on distributed memory systems. They also present poor spatial and temporal locality, thus generating unpredictable memory and network accesses. The Partitioned Global Address Space (PGAS) programming model seems suitable for these applications, because it allows using a shared memory abstraction across distributed-memory clusters. However, current PGAS languages and libraries are built to target regular remote data accesses and block transfers. Furthermore, they usually rely on the Single Program Multiple Data (SPMD) parallel control model, which is not well suited to the fine grained, dynamic and unbalanced parallelism of irregular applications. In this paper we present {\bf GMT} (Global Memory and Threading library), a custom runtime library that enables efficient execution of irregular applications on commodity clusters. GMT integrates a PGAS data substrate with simple fork/join parallelism and provides automatic load balancing on a per node basis. It implements multi-level aggregation and lightweight multithreading to maximize memory and network bandwidth with fine-grained data accesses and tolerate long data access latencies. A key innovation in the GMT runtime is its thread specialization (workers, helpers and communication threads) that realize the overall functionality. We compare our approach with other PGAS models, such as UPC running using GASNet, and hand-optimized MPI code on a set of typical large-scale irregular applications, demonstrating speedups of an order of magnitude.

Aggregation↗

DOE OSTI2017

FleCSPH notes

FleCSI is a compile-time con gurable framework designed to support multi-physics application development. As such, FleCSI provides a very general set of infrastructure design patterns that can be specialized and extended to suit the needs of a broad variety of solver and data requirements. FleCSI currently supports multi-dimensional mesh topology, geometry, and adjacency information, as well as n-dimensional hashed-tree data structures, graph partitioning interfaces, and dependency closures. FleCSI introduces a functional programming model with control, execution, and data abstractions that are consistent both with MPI and with state-of-the-art, task-based runtimes such as Legion and Charm++. The abstraction layer insulates developers from the underlying runtime, while allowing support for multiple runtime systems including conventional models like asynchronous MPI. The intent is to provide developers with a concrete set of user-friendly programming tools that can be used now, while allowing exibility in choosing runtime implementations and optimization that can be applied to future architectures and runtimes. FleCSI's control and execution models provide formal nomenclature for describing poorly understood concepts such as kernels and tasks. FleCSI's data model provides a low-buy-in approach that makes it an attractive option for many application projects, as developers are not locked into particular layouts or data structure representations. FleCSI currently provides a parallel but not distributed implementation of Binary, Quad and Oct-tree topology. This implementation is base on space lling curves domain decomposition, the Morton order. The current FleCSI version requires the implementation of a driver and a specialization driver. The role of the specialization driver is to provide the data distribution. This feature is not complete in FleCSI code and we provide it. The next step will be to incorporate it directly from FleCSPH to FleCSI as we reach a good level of performance. Then the driver represent the general execution of the resolution without worrying of the data locality and communications. As FleCSI is an On-Development code the structure may change in the future and we keep track of these changes in FleCSPH.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Performance portability study for massively parallel computational fluid dynamics application on scalable heterogeneous architectures

Patient-specific hemodynamic simulations have the possibility to greatly improve both the diagnosis and treatment of a variety of vascular diseases. Portability will enable wider adoption of computational fluid dynamics (CFD) applications in the biomedical research community and targeting to platforms ideally suited to different vascular regions. Here, we introduce a case study in performance portability that assesses (1) the ease of porting an MPI application optimized for one specific architecture to new platforms using variants of hybrid MPI+X programming models; (2) performance portability seen when simulating blood flow in three different vascular regions on diverse heterogeneous architectures; (3) model-based performance prediction for future architectures; and (4) performance scaling of the hybrid MPI+X programming on parallel heterogeneous systems. We report on the lessons learned in porting HARVEY, a massively parallel CFD application, from traditional multicore CPUs to diverse heterogeneous architectures ranging from NVIDIA/AMD GPUs to Intel MICs and Altera FPGAs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Methane Exhaust Measurements at Gathering Compressor Stations in the United States

Unburned methane entrained in exhaust from natural gas-fired compressor engines (“combustion slip”) can account for a substantial portion of station-level methane emissions. A novel in-stack, tracer gas method was coupled with Fourier transform infrared (FTIR) species measurements to quantify combustion slip from natural gas compressor engines at 67 gathering and boosting stations owned or managed by nine “study partner” operators in 11 U.S. states. The mean methane emission rate from 63 four-stroke, lean-burn (4SLB) compressor engines was 5.62 kg/h (95% CI = 5.15–6.17 kg/h) and ranged from 0.3 to 12.6 kg/h. The mean methane emission rate from 39 fourstroke, rich-burn (4SRB) compressor engines was 0.40 kg/h (95% CI = 0.37– 0.42 kg/h) and ranged from 0.01 to 4.5 kg/h. Study results for 4SLB engines were lower than both the U.S. EPA compilation of air pollutant emission factors (AP-42) and Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI) by 8 and 9%, respectively. Study results for 4SRB engines were 43% of the AP-42 emission factor and 8% of the GHGI emission factor, the latter of which does not distinguish between engine types. Total annual combustion slip from the U.S. natural gas gathering and boosting sector was modeled using measured emission rates and compressor unit counts from the U.S. EPA Greenhouse Gas Reporting Program. Modeled results [328 Gg/y (95% CI = 235–436 Gg/y) of unburned methane] would account for 24% (95% CI = 17–31%) of the 1391 Gg of methane emissions for “Gathering and Boosting Stations”, or 6% of the net emissions for “Natural Gas Systems” (5598 Gg) as reported in the 2020 U.S. EPA GHGI. In conclusion, gathering and boosting combustion slip emissions reported in the 2020 GHGI (374 Gg) fall within the uncertainty of this model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Systematic Validation of Ensemble Cloud-Process Simulations using Polarimetric Radar Observations and Simulator over the NASA Wallops Flight Facility

The BiLateral Operational Storm-Scale Observation and Modeling (BLOSSOM) project was initiated to establish a long-term supersite to improve understanding of cloud physical states and processes as well as to support satellite and climate model programs over the WFF site via a bilateral approach of storm-scale observations and process modeling. This study highlights a noble systematic validation framework of the BLOSSOM ensemble cloud-process simulations through mixed-phase, light-rain, and deep-convective precipitation cases. The framework consists of creating a domain-shifted ensemble of large-scale forcing datasets, and configuring and performing cloud-process simulations with three different bulk microphysics schemes. Validation uses NASA S-band dual-POLarimetric radar (NPOL) observations in the form of statistical composites and skill scores via a polarimetric radar simulator and newly developed CfRad Data tool (CfRAD). While the simulations capture the overall structures of the reflectivity composites, polarimetric signals are still poorly simulated, mainly due to a lack of representation of ice microphysics diversity in shapes, orientation distributions, and their complex mixtures. Despite the limitation, this new ensemble-based validation framework demonstrates that 1) no particular forcing or microphysics scheme outperforms the rest and 2) the skill scores of coarse- and fine-resolution ensemble simulations with different domain-shifted forcing and microphysics schemes are highly correlated with each other with no clear improvement. On the other hand, this suggests that coarse-resolution ensemble simulations are relevant for selecting the best meteorological forcing and microphysics scheme before conducting computationally demanding large eddy simulations (LESs) in support of aircraft and satellite instrument development as well as cloud-precipitation-convection parameterizations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Synergism of the method of characteristics and CAD technology for neutron transport calculation

The method of characteristics (MOC) is a very popular methodology in neutron transport calculation and numerical simulation in recent decades for its unique advantages. One of the key problems determining whether the MOC can be applied in complicated and highly heterogeneous geometry is how to combine an effective geometry processing method with MOC. Most of the existing MOC codes describe the geometry by lines and arcs with extensive input data, such as circles, ellipses, regular polygons and combination of them. Thus they have difficulty in geometry modeling, background meshing and ray tracing for complicated geometry domains. In this study, a new idea making use of a CAD solid modeler MCAM which is a CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport developed by FDS Team in China was introduced for geometry modeling and ray tracing of particle transport to remove these geometrical limitations mentioned above. The diamond-difference scheme was applied to MOC to reduce the spatial discretization error of the flat flux approximation in theory. Based on MCAM and MOC, a new MOC code was developed and integrated into SuperMC system, which is a Super Multi-function Computational system for neutronics and radiation simulation. The numerical testing results demonstrated the feasibility and effectiveness of the new idea for geometry treatment in SuperMC. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Jacobian-based model diagnostics and application to equation oriented modeling of a carbon capture system

It can be difficult to identify the specific variables or equations responsible for convergence issues in large mathematical programming models. The Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES-IP) contains a tool to identify poorly scaled constraints and variables by searching for rows and columns of the Jacobian matrix with small L2-norms. A singular value decomposition is then performed to identify degenerate sets of equations and remaining scaling issues. Here, this work presents a flowsheet developed for post-combustion carbon capture using a monoethanolamine (MEA) solvent system as a case study. This work takes the reader through the entire process of model diagnostics and reformulation, from a basic introduction to the mathematics behind these model diagnostics to the reformulations necessary to make the model numerically robust, including a significantly modified enhancement factor model.

IDAES↗

DOE OSTI2015

First experience of vectorizing electromagnetic physics models for detector simulation

The recent emergence of hardware architectures characterized by many-core or accelerated processors has opened new opportunities for concurrent programming models taking advantage of both SIMD and SIMT architectures. The GeantV vector prototype for detector simulations has been designed to exploit both the vector capability of mainstream CPUs and multi-threading capabilities of coprocessors including NVidia GPUs and Intel Xeon Phi. The characteristics of these architectures are very different in terms of the vectorization depth, parallelization needed to achieve optimal performance or memory access latency and speed. An additional challenge is to avoid the code duplication often inherent to supporting heterogeneous platforms. In this paper we present the first experience of vectorizing electromagnetic physics models developed for the GeantV project.

Amadio, G.↗

DOE OSTI2024

IRIS Reimagined: Advancements in Intelligent Runtime System for Task-Based Programming

Task-based programming models are gaining traction in scientific computing. IRIS is a portable runtime system that exploits multiple heterogeneous programming systems and can discover available resources and manage multiple diverse programming systems (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, and OpenMP) simultaneously. It accounts for the constraints of task dependencies and provides customizable scheduling policies to map those tasks to heterogeneous devices. In this paper, we present new capabilities added to IRIS to improve its portability for heterogeneous programming, build-friendliness, and performance efficiency. The new additions include vendor-specific kernel support, a runtime system with a foreign function interface to eliminate writing wrapper or boilerplate code for heterogeneous kernels, an easy-to-use and configurable CMake-based build environment, automatic and efficient data transfers and orchestration, and the Hunter and DAGGER toolchains to evaluate IRIS’s task scheduling algorithms.

Miniskar, Narasinga Rao↗