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At least 235 records · Page 13

Requirements, Status, and Plans for Track Reconstruction at the sPHENIX Experiment

sPHENIX is a new experiment that is being constructed at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The primary physics goals of sPHENIX are to measure jets, their substructure, and the upsilon resonances in p+p, p+Au and Au+Au collisions. To realize these goals, a tracking system composed of a time projection chamber and several silicon detectors will be used to identify tracks that correspond to jets and upsilon decays. However, the sPHENIX experiment will collect approximately 200 PB of data utilizing a finite-sized computing center; thus, performing track reconstruction in a timely manner is a challenge due to the large occupancy of heavy-ion collisions. The sPHENIX experiment, its track reconstruction, and the need for implementing faster track-fitting algorithms, such as that provided by the A Common Tracking Software package, into the sPHENIX software stack are discussed.

Osborn, Joe↗

Comparison of Simulated and Experimentally Measured Detector Impulse Responses to Pulsed X-rays

The Gamma Array Simulation Toolkit (GAST) is a multi-physics software stack comprised of Geant4, MATLAB, and experimentally measured photomultiplier tube (PMT) impulse response waveforms that is used to model and inform the end-to-end performance of radiation detector systems. In order to validate the ability of GAST to predict the impulse response of a modeled detector configuration operated in current mode, experimental measurements using the Nevada National Security Site Transformational Diagnostics and Imaging 2 MeV endpoint energy electron linear accelerator (linac) with a tungsten target were performed. Seven different detector configurations consisting of unique combinations of scintillator material, size, reflectivity conditions, presence or absence of light guide, and PMT were evaluated. The resultant impulse response of each detector configuration was recorded and compared to a GAST simulation that emulated the respective linac experiment conditions. The comparison of the experimental and simulated detector impulse responses indicated that GAST can reliably predict detector impulse responses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

On the Marriage of Asynchronous Many Task Runtimes and Big Data: A Glance

The rise of the accelerator-based architectures and reconfigurable computing have showcased the weakness of software stack toolchains that still maintain a static view of the hardware instead of relying on a symbiotic relationship between static (e.g., compilers) and dynamic tools (e.g., runtimes). In the past decades, this need has given rise to adaptive runtimes with increasingly finer computational tasks. These finer tasks help to take advantage of the hardware by switching out when a long latency operation is encountered (because of the deeper memory hierarchies and new memory technologies that might target streaming instead of random access), thus trading off idle time for unrelated work. Examples of these finer task runtimes are Asynchronous Many Task (AMT) runtimes, in which highly efficient computational graphs run on a variety of hardware. Due to its inherent latency tolerant characteristics, Latency-sensitive applications, such as Graph Analytics and Big Data can effectively use these runtimes. This paper aims to present an example of how the careful design of an AMT can exploit the hardware substrate when faced with high latency applications such as the ones given in the Big Data domain. Moreover, with its introspection and adaptive capabilities, we aim to show the power of these runtimes when facing the changing requirements of the application workloads. We use the Performance Open Community Runtime (P-OCR) as our vehicle to demonstrate the concepts presented here.

adaptive runtime, big data analysis↗

Bringing OpenCL to Commodity RISC-V CPUs

The importance of open-source hardware has been increasing in recent years with the introduction of the RISC-V Open ISA. This has also accelerated the push for support of the open-source software stack from compiler tools to full-blown operating systems. Parallel computing with today’s Application Programming Interfaces such as OpenCL has proven to be effective at leveraging the parallelism in commodity multi-core processors and programmable parallel accelerators. However, to the best of our knowledge, there is currently no publicly available implementation of OpenCL targeting commodity RISC-V processors that is accessible to the open-source community. Besides opening RISC-V to the existing rich variety of scientific parallel applications, OpenCL also provides access to a unique genre of benchmarks useful in computer architecture research. In this work, we extended an Open-source implementation of OpenCL to target RISC-V CPUs. Our work not only cover commodity multi-core RISC-V processors, but also plethora of low- profile embedded RISC-V CPUs that often do not support atomic instructions or multi-threading.

Tine, Blaise↗

Science Federation Emulation Testbed: Demonstration of VFSIE Functionalities

The Virtual Federated Science Instrument Environment (VFSIE) is a digital twin of a federated infrastructure of multiple sites with science instruments and computing systems that are geographically dispersed. It emulates the federation using containers and virtual hosts (vhosts) connected over local and wide-area networks for the main purpose of supporting the development and testing of science workflows and software stacks, which will subsequently transition to the physical infrastructure. In this demo, we present VFSIE of a four sites scenario and illustrate the following use cases: (i) execution of federation stack components that expose resources to enable a science user to execute workflows, (ii) execution of remote control commands of beam-line instruments to collect measurements and position the sensor, and (iii) remote execution and access of Jupyter Notebook for tomographic image computations

Al Najjar, Anees↗

GradientGraph

Under this SBIR Phase II, Reservoir Labs has developed G2 Analytics, a new technology that allows network operators to analyze bottleneck and flow performance with high precision. G2 delivers a new analytical approach and framework to resolve a variety of key problems found in modern communication networks, including: traffic engineering, routing, flow scheduling, network design, capacity planning, resiliency analysis, network slicing, or service level agreement (SLA) management, among others. G2 leverages the bottleneck structure of congestion-controlled communication networks, a recent mathematical discovery by the Reservoir team [RL19b, RL20a, RL20b, RL21a]. Bottleneck structures reveal how perturbations on flows and links propagate through the network, providing an analytical framework to measure (qualitatively and quantitatively) the ripple effects induced as they traverse the network. Leveraging the mathematics of bottleneck structures, Reservoir Labs is developing the G2 technology to provide network operators with a framework to design, optimize and troubleshoot network performance. This delivery includes the G2 software stack.

Yellamraju, Sruthi↗

ExaWind: Opportunity for Discovery

The predictive simulation of the dynamics of modern wind turbines and wind farms is a high-performance-computing (HPC) grand challenge. Modern wind turbines are the largest rotating machines in the world, with rotor diameters exceeding 200 meters, and with heights well into the atmospheric boundary layer. To address this grand challenge, the U.S. Department of Energy (DOE) Wind Energy Technologies Office and the Exascale Computing Project have been supporting the creation of the ExaWind modeling and simulation environment since 2016. ExaWind is composed of the incompressible-flow computational-fluid-dynamics (CFD) solvers AMR-Wind and Nalu-Wind and the wind-turbine-dynamics solver OpenFAST. In our hybrid CFD approach, Nalu-Wind unstructured-grid models resolve the near-body flow around the turbine; those models are embedded in, and two-way coupled to, an AMR-Wind structured-grid mesh through overset meshes. In this talk I give an overview of ExaWind software stack and describe how it is being used to address important problems in wind energy.

computational fluid dynamics↗

ExaWind: Then and Now

The scientific goal of the ExaWind project is to advance our fundamental understanding of the flow physics governing whole wind plant performance, including wake formation, complex terrain impacts, and turbine-turbine-interaction effects. The primary application codes in the ExaWind environment are Nalu-Wind, an unstructured-grid computational fluid dynamics (CFD) code, AMR-Wind, a structured-grid CFD code, and OpenFAST, a whole-turbine simulation code. In this poster we present the current status of the ExaWind software stack in the context of the modeling and simulation capabilities when the project started in 2016.

computational fluid dynamics↗

Quantum Software Engineering (Dagstuhl Seminar 24512)

The Dagstuhl Seminar 24512 on "Quantum Software Engineering" was held from December 15 to 20, 2024. It brought together 26 participants from industry and academia from 13 different countries, including senior and junior researchers as well as practitioners in the field of Quantum Software Engineering. The aim of the seminar was to advance software engineering methods and tools for the engineering of hybrid quantum systems by promoting personal interaction and open discussion among researchers who are already working in this emerging area of knowledge. The first day of the seminar was devoted to the topic "When software engineering meets quantum mechanics", while the second day focused on "Quantum software engineering and its challenges." During both days, 16 invited presentations were given. The rest of the seminar was organized into three working groups to address the topics "Quantum Software Design, Modelling and Architecturing", "Adaptive Hybrid Quantum Systems", and "Quantum Software Quality Assurance". The seminar was a very fruitful experience for all participants both in terms of scientific outcomes and in terms of the personal relationships that were generated to jointly address future experiences.

97 MATHEMATICS AND COMPUTING↗

eXascale PRogramming Environment and System Software (XPRESS)

Exascale systems, with a thousand times the compute capacity of today’s leading edge petascale computers, are expected to emerge during the next decade. Their software systems will need to facilitate the exploitation of exceptional amounts of concurrency in applications, and ensure that jobs continue to run despite the occurrence of system failures and other kinds of hard and soft errors. Adapting computations at runtime to cope with changes in the execution environment, as well as to improve power and performance characteristics, is likely to become the norm. As a result, considerable innovation is required to develop system support to meet the needs of future computing platforms. The XPRESS project aims to develop and prototype a revolutionary software system for extreme-­scale computing for both exascale and strong­scaled problems. The XPRESS collaborative research project will advance the state-­of-­the-­art in high performance computing and enable exascale computing for current and future DOE mission-­critical applications and supporting systems. The goals of the XPRESS research project are to: A. enable exascale performance capability for DOE applications, both current and future, B. develop and deliver a practical computing system software X-­stack, OpenX, for future practical DOE exascale computing systems, and C. provide programming methods and environments for effective means of expressing application and system software for portable exascale system execution.

97 MATHEMATICS AND COMPUTING↗

Virtual machine-based simulation platform for mobile ad-hoc network-based cyber infrastructure

In modeling and simulating complex systems such as mobile ad-hoc networks (MANETs) in de-fense communications, it is a major challenge to reconcile multiple important considerations: the rapidity of unavoidable changes to the software (network layers and applications), the difficulty of modeling the critical, implementation-dependent behavioral effects, the need to sustain larger scale scenarios, and the desire for faster simulations. Here we present our approach in success-fully reconciling them using a virtual time-synchronized virtual machine(VM)-based parallel ex-ecution framework that accurately lifts both the devices as well as the network communications to a virtual time plane while retaining full fidelity. At the core of our framework is a scheduling engine that operates at the level of a hypervisor scheduler, offering a unique ability to execute multi-core guest nodes over multi-core host nodes in an accurate, virtual time-synchronized manner. In contrast to other related approaches that suffer from either speed or accuracy issues, our framework provides MANET node-wise scalability, high fidelity of software behaviors, and time-ordering accuracy. The design and development of this framework is presented, and an ac-tual implementation based on the widely used Xen hypervisor system is described. Benchmarks with synthetic and actual applications are used to identify the benefits of our approach. The time inaccuracy of traditional emulation methods is demonstrated, in comparison with the accurate execution of our framework verified by theoretically correct results expected from analytical models of the same scenarios. In the largest high fidelity tests, we are able to perform virtual time-synchronized simulation of 64-node VM-based full-stack, actual software behaviors of MANETs containing a mix of static and mobile (unmanned airborne vehicle) nodes, hosted on a 32-core host, with full fidelity of unmodified ad-hoc routing protocols, unmodified application executables, and user-controllable physical layer effects including inter-device wireless signal strength, reachability, and connectivity.

97 MATHEMATICS AND COMPUTING↗

A cross-platform execution engine for the quantum intermediate representation

Hybrid languages like the quantum intermediate representation (QIR) are essential for programming systems that mix quantum and conventional computing models, while execution of these programs is often deferred to a system-specific implementation. Here, we develop the QIR Execution Engine (QIR-EE) for parsing, interpreting, and executing QIR across multiple hardware platforms. QIR-EE uses LLVM to execute hybrid instructions specifying quantum programs and, by design, presents extension points that support customized runtime and hardware environments. We demonstrate an implementation that uses the XACC quantum hardware-accelerator library to dispatch prototypical quantum programs on different commercial quantum platforms and numerical simulators, and we validate execution of QIR-EE on IonQ, Quantinuum, and IBM hardware. Our results highlight the efficiency of hybrid executable architectures for handling mixed instructions, managing mixed data, and integrating with quantum computing frameworks to realize cross-platform execution.

LLVM↗

RTN-056: Study of the Photon Transfer Curve in the CCD detectors of the Vera C. Rubin Observatory

The RECA internship program provides Colombian students with an opportunity to enhance their research skills in Astronomy, Astrophysics, and Cosmology. During this three-month program, our main objective was to study the Photon Transfer Curves (PTC) of the Vera C. Rubin Observatory, specifically the gain, and to compare it with the gain obtained through pairs of flats. Overall, the study of PTCs is crucial in understanding the performance of detectors and instruments used in Astronomy. The Vera C. Rubin Observatory is an important facility that will enable researchers to carry out a wide range of studies in this field, making it essential to investigate its gain performance. We used run 13144 to construct the PTCs and 13186 to analyze the crosstalk. We employed the LSST Science Pipelines (also known as the DM stack), a software under development for this observatory, which performs all the necessary reductions for the construction of the PTCs. We also used simulations to replicate the observed effects. Initially, we found a 5% difference between the gain calculated by PTC and pairs of flats for a flow range between 5000 and 10000 ADU. Simulations showed that this difference was due to the handling of statistics and the assumption that the distribution following the Lupton equation is Gaussian. We found an error interval for this flow region based on the vendor, with (1.8 ± 0.7, 4.1 ± 0.9) % for E2V and (0.85 ± 0.7, 2.2 ± 0.9) % for ITL. From the PTC, we also obtained the average Full Well Capacity of LSSTCam as 130000 ± 10000$ electrons. We identified a list of segments where we found differences with the results obtained by SLAC National Acceleration Laboratory in PTC parameters, low saturation level, or other defects. We detected and corrected the effect of statistics in the gain calculation using pairs of flats and proposed a code change, which was implemented in the pipeline software. We do not recommend correcting for crosstalk as it does not significantly affect the parameters and does not change the shape of the PTC. However, the opposite is true for the nonlinearity correction.

79 ASTRONOMY AND ASTROPHYSICS↗

URBAN-NET-TOOLKIT

Strengthening and maintaining secure, functioning, and resilient Critical Infrastructure Systems (CISs) is one of our nation's primary goals, and it requires proactive and coo0rdinated efforts among federal, state, local, public and private owners and operators of CISs. Recent worldwide extreme events have shown how interdependencies across CISs (electric grid, telecommunications, transportation, water networks, etc.) can drastically increase system vulnerability. To understand these complex interdependencies, ORNL has instantiated Urban-NET, a novel decision support system for CIS operators who need to identify vulnerabilities for minimizing the cascading impacts - saving utilities, the federal and state government, and private sector companies potentially billions by avoiding a complete CI failure and/or shutdown. The developed system includes a stack of software tools for preprocessing, modeling, interconnecting multiple CIS datasets as an integrated heterogeneous graph (i.e. network), identifying vulnerabilities through topological analysis, and predicting consequences based on simulations along with visualization.

Chinthavali, Supriya↗

A scalable matrix-free spectral element approach for unsteady PDE constrained optimization using PETSc/TAO

In this work, we provide a new approach for the efficient matrix-free application of the transpose of the Jacobian for the spectral element method for the adjoint-based solution of partial differential equation (PDE) constrained optimization. This results in optimizations of nonlinear PDEs using explicit integrators where the integration of the adjoint problem is not more expensive than the forward simulation. Solving PDE constrained optimization problems entails combining expertise from multiple areas, including simulation, computation of derivatives, and optimization. The Portable, Extensible Toolkit for Scientific computation (PETSc) together with its companion package, the Toolkit for Advanced Optimization (TAO), is an integrated numerical software library that contains an algorithmic/software stack for solving linear systems, nonlinear systems, ordinary differential equations, differential algebraic equations, and large-scale optimization problems and, as such, is an ideal tool for performing PDE-constrained optimization. This paper describes an efficient approach in which the software stack provided by PETSc/TAO can be used for large-scale nonlinear time-dependent problems. Time integration can involve a range of high-order methods, both implicit and explicit. The PDE-constrained optimization algorithm used is gradient-based and seamlessly integrated with the simulation of the physical problem.

97 MATHEMATICS AND COMPUTING↗

XPRESS: eXascale PRogramming Environment and System Software

The XPRESS Project is one of four major projects of the DOE Office of Science Advanced Scientific Computing Research X-stack Program initiated in September, 2012. The purpose of XPRESS is to devise an innovative system software stack to enable practical and useful exascale computing around the end of the decade with near-term contributions to efficient and scalable operation of trans-Petaflops performance systems in the next two to three years; both for DOE mission-critical applications. To this end, XPRESS directly addresses critical challenges in computing of efficiency, scalability, and programmability through introspective methods of dynamic adaptive resource management and task scheduling.

97 MATHEMATICS AND COMPUTING↗

Supply Chain Binary Program Assessment Annual Report

Secure environments face a steadily increasing threat from the introduction of scientific equipment that includes extensive software components. Devices such as powerful microscopes, 3d printers, programmable logic controllers, and many others, increase our capability and scientific output. Unfortunately, they now frequently include an entire computing stack with custom software bundled along with entire operating systems. Our ability to introspect and understand binary software is extremely limited, opening up the possibility of malicious third-parties including software that compromises our critical missions.

42 ENGINEERING↗