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At least 991 records · Page 55

Hunting for Majoranas

Over the past decade, there have been considerable efforts to observe non-abelian quasiparticles in novel quantum materials and devices. These efforts are motivated by the goals of demonstrating quantum statistics of quasiparticles beyond those of fermions and bosons and of establishing the underlying science for the creation of topologically protected quantum bits. In this Review, we focus on efforts to create topological superconducting phases that host Majorana zero modes. We consider the lessons learned from existing experimental efforts, which are motivating both improvements to present platforms and the exploration of new approaches. Although the experimental detection of non-abelian quasiparticles remains challenging, the knowledge gained thus far and the opportunities ahead offer high potential for discovery and advances in this exciting area of quantum physics.

Science & Technology - Other Topics↗

Cryogenic control system operational experience at SNS

Abstract The helium cryogenic system at Spallation Neutron Source (SNS) provides cooling to 81 superconducting radio frequency cavities. To support the operation of the cryogenic facility, a highly reliable control system consisting of software, hardware, and Human Machine Interface (HMI) has been developed and improved during the first fifteen years of operation. Integrating the cryogenic control system with other subsystems of the SNS complex is an important aspect to the success of the operation. The operating experience, lessons learned and recommendations to consider for future facilities will be detailed in this paper.

Howell, M. (ORCID:0000000310360707)↗

Large-Aperture High-Field Nb 3 Sn Quadrupole Magnets for HiLumi

The HL-LHC Inner Triplet quadrupole magnets use Nb 3 Sn superconductor for the first time in a particle accelerator. Coil peak field, forces, and stored energy density are significantly higher than in previous accelerator magnets. The original design addressed all these challenges. Lessons learned in the early phases made the final design and specifications for series magnets more robust.

43 PARTICLE ACCELERATORS↗

Navigating the maze: the impact of configurability in bioinformatics software

The bioinformatics software domain contains thousands of applications for automating tasks such as the pairwise alignment of DNA sequences, building and reasoning about metabolic models or simulating growth of an organism. Its end users range from sophisticated developers to those with little computational experience. In response to their needs, developers provide many options to customize the way their algorithms are tuned. Yet there is little or no automated help for the user in determining the consequences or impact of the options they choose. In this paper we describe our experience working with configurable bioinformatics tools. We find limited documentation and help for combining and selecting options along with variation in both functionality and performance. We also find previously undetected faults. We summarize our findings with a set of lessons learned, and present a roadmap for creating automated techniques to interact with bioinformatics software. We believe these will generalize to other types of scientific software.

McDevitt, Mikaela Cashman↗

One SQL to Rule Them All - an Efficient and Syntactically Idiomatic Approach to Management of Streams and Tables

Real-time data analysis and management are increasingly critical for today's businesses. SQL is the de facto lingua franca for these endeavors, yet support for robust streaming analysis and management with SQL remains limited. Many approaches restrict semantics to a reduced subset of features and/or require a suite of non-standard constructs. Additionally, use of event timestamps to provide native support for analyzing events according to when they actually occurred is not pervasive, and often comes with important limitations. We present a three-part proposal for integrating robust streaming into SQL, namely: (1) time-varying relations as a foundation for classical tables as well as streaming data, (2) event time semantics, (3) a limited set of optional keyword extensions to control the materialization of time-varying query results. We show how with these minimal additions it is possible to utilize the complete suite of standard SQL semantics to perform robust stream processing. We motivate and illustrate these concepts using examples and describe lessons learned from implementations in Apache Calcite, Apache Flink, and Apache Beam. We conclude with syntax and semantics of a concrete proposal for extensions of the SQL standard and note further areas of exploration.

Begoli, Edmon↗

C3F: Collaborative Container-based Model Coupling Framework

Solving complex real-world grand challenge problems requires in-depth collaboration of researchers from multiple disciplines. Such collaboration often involves harnessing multiscale and multi-dimensional data and combining models from different fields to simulate systems. However, the progress on this front has been limited mainly due to significant gaps in domain knowledge and tools that are typically employed in silos of the domains. Researchers from different fields face considerable barriers to understanding and reusing each other’s data/models in order to collaborate effectively. For example, in solving the global sustainability problems, researchers from hydrology, climate science, agriculture, and economics need to run their respective models to study different components of the global and local food, energy and water systems while, at the same time, need to interact with other researchers and integrate the results of one model with another. Developing this kind of model coupling workflow calls for (1) a large amount of data being processed and exchanged across domains and organizations, (2) identifying and processing the output of one model to make it ready for integration into another model, (3) controlling the workflow dynamically so that it runs until a certain convergence condition or other criteria is met, and (4) close collaboration among the modelers to explore, tune, and test the configuration and data transformation needed to link the models. We have developed C3F, a flexible collaborative model coupling framework to help researchers accelerate their model integration and linking efforts by leveraging advanced cyberinfrastructure such as high-performance computing and virtual containers. In this paper, we describe our experience and lessons learned in developing this cyberinfrastructure solution to support the linking of Water Balance Model (WBM) and SIMPLE-G agricultural economic model in an NSF funded INFEWS project and a DOE-funded Program on Coupled Human and Earth Systems (PCHES) to study the implications of groundwater scarcity for food-energy-water systems. The C3F model coupling framework can be extended to facilitate other model linkages as well.

containerization↗

FacultyHack Events: Faculty-Focused Hackathons for High-Performance Computing Curriculum Development

Broadening participation initiatives are important for engaging underrepresented groups in science, technology, engineering, and math (STEM). Such initiatives help foster supportive and inclusive work environments that promote creativity and productivity. While there are initiatives that aim to engage students and faculty, opportunities remain to improve faculty support. Hackathons have proved to be a useful approach for student engagement. There are, however, limited insights into whether and how such events would also work for faculty aiming to develop curricula. This paper discusses the design of a faculty-focused hackathon event, FacultyHack, for curriculum development. We outline the logistics and structure for two past FacultyHack events, detail changes between events, and describe potential improvements and lessons learned.

Holmen, John [ORNL] (ORCID:0000000259342641)↗

Adversarial Binaries: AI-guided Instrumentation Methods for Malware Detection Evasion

Adversarial binaries are executable files that have been altered without loss of function by an AI agent in order to deceive malware detection systems. Progress in this emergent vein of research has been constrained by the complex and rigid structure of executable files. Although prior work has demonstrated that these binaries deceive a variety of malware classification models which rely on disparate feature sets, a consensus as to the best approach has not been reached, either in terms of the optimization algorithms or the instrumentation methods. Furthermore, although inconsistencies in the data sets, target classifiers, and functionality verification methods make head-to-head comparisons difficult, here we extract lessons learned and make recommendations for future research.

malware obfuscation↗

Scaling Uintah on the Aurora Exascale System up to 122,880 Intel Ponte Vecchio Xe Stacks

The challenge of being able to scale application codes based on the Asynchronous Many-Task (AMT) Uintah framework on the Department of Energy (DOE) Aurora exascale system is addressed in this work by considering a challenging Reverse Monte Carlo Ray Tracing radiation benchmark calculation. This benchmark involves potentially global all-to-all communication and uses adaptive mesh refinement and ray tracing to achieve scalability. This benchmark has been used as part of previous scalability studies on a number of pre-exascale systems and on the DOE Frontier exascale system. This paper describes steps taken to enable this benchmark to run successfully on up to 10,240 nodes and 122,880 Intel® Ponte Vecchio Xe stacks on the DOE Aurora exascale system. This scalability was achieved through a limited number of experiments on Aurora, given machine loads and its uniqueness. These experiments constitute valuable lessons learned to achieve scalability at this level. The resulting scalability runs, while few in number, demonstrate relatively good strong-scaling characteristics. A detailed analysis of these results provides important indications about the path to scalability on Aurora for future work. Overall, these results continue the remarkable ability of this AMT approach to produce scalable solutions for challenging problems at extreme scale on heterogeneous architectures.

Garcia, Marta [Argonne National Laboratory (ANL)]↗

Insights from Optimizing HPL Performance on Exascale Systems: A Comparative Analysis of Panel Factorization

High performance LINPACK (HPL) remains the primary benchmark for evaluating supercomputing performance. It includes many parts with substantial internal complexity, and its performance is affected by a large number of parameters that interact in ways that are difficult to predict on large-scale heterogeneous supercomputer systems. We present a comprehensive performance analysis of HPL on Frontier, the world’s first exascale supercomputer, which achieved HPL performance of 1.35 exaflops. Through empirical parameter tuning, detailed modeling, and comparative evaluation, we uncover critical performance insights, share lessons learned, and outline best practices for effective parameter tuning on exascale systems. We introduce and evaluate two novel PDFACT strategies: a dedicated-thread (DT) variant and a GPU-based variant (GPUPDFACT) implementation using HIP cooperative groups, demonstrating that GPU-based factorization outperforms conventional CPU-based PDFACT on Frontier’s architecture. Our findings establish key performance factors for HPL on exascale systems and offer valuable guidance for future high-performance computing and benchmarking efforts.

Lu, Hao [ORNL] (ORCID:000000018941870X)↗

Reinvented: An Attosecond Chemist

Attosecond science requires a substantial rethinking of how to make measurements on very short timescales; how to acquire the necessary equipment, technology, and personnel; and how to build a set of laboratories for such experiments. This entails a rejuvenation of the author in many respects, in the laboratory itself, with regard to students and postdocs, and in generating funding for research. It also brings up questions of what it means to do attosecond science, and the discovery of the power of X-ray spectroscopy itself, which complements the short timescales addressed. The lessons learned, expressed in the meanderings of this autobiographical article, may be of benefit to others who try to reinvent themselves.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pre-exascale accelerated application development: The ORNL Summit experience

High-performance computing (HPC) increasingly relies on heterogeneous architectures to achieve higher performance. In the Oak Ridge Leadership Facility (OLCF), Oak Ridge, TN, USA, this trend continues as its latest supercomputer, Summit, entered production in early 2019. The combination of IBM POWER9 CPU and NVIDIA V100 GPU, along with a fast NVLink2 interconnect and other latest technologies, pushes system performance to a new height and breaks the exascale barrier by certain measures. Due to Summit's powerful GPUs and much higher GPU–CPU ratio, offloading to accelerators becomes a requirement for any application, which intends to effectively use the system. To facilitate navigating a complex landscape of competing heterogeneous architectures, a collection of applications from a wide spectrum of scientific domains is selected for early adoption on Summit. In this article, the experience and lessons learned are summarized, in the hope of providing useful guidance to address new programming challenges, such as scalability, performance portability, and software maintainability, for future application development efforts on heterogeneous HPC systems.

97 MATHEMATICS AND COMPUTING↗

Nalu

Nalu is a Sierra ToolKit (STK) based application module, and it has provided a set of "lessons learned" for the STK transition effort through its early adoption of STK. It makes use of the open-sourced Trilinos/ Tpetra library. Through the investment of LORD and ASCR projects, the Nalu code module has been extended beyond prototype status. Physics capability includes low Mach, variable density turbulent flow. The ongoing objective for Nalu is to facilitate partnerships with external organizations in order to extend code capability and knowledge; however, it is not intended to support routine CFD analysis. The targeted usage of this module is for non-NW applications that support work-for-others in the multiphysics energy sector.

Source record↗

Global-Address Space Networking for Exascale

GASNet-EX is a portable, open-source, high-performance communication library designed to efficiently support the networking requirements of Partitioned Global Address Space (PGAS) runtime systems and other alternative models in future exascale machines. The library is an evolution of the popular GASNet communication system, building upon over 15 years of lessons learned. GASNet is a language-independent, networking middleware layer that provides network-independent, high-performance communication primitives including Remote Memory Access (RMA) and Active Messages (AM). It has been used to implement parallel programming models and libraries such as UPC, Co-Array Fortran, Titanium, Legion, Chapel, and many others. The interface is primarily intended as a compilation target and for use by runtime library writers (as opposed to end users), and the primary goals are high performance, interface portability, and expressiveness. GASNet stands for "Global-Address Space Networking".

ECP↗

pnnl/NWGraph

NWGraph aims to fill the role of a reusable library of generic graph algorithms for C++, similar to the algorithms available in the standard template library (STL) in C++. The library draws lessons learned from Boost Graph Library (BGL) and other libraries (PBGL, Galois, Gunrock, GraphX etc.), the evolution of the C++ language, and the evolution of C++ practice over the last 20 years.

Lumsdaine, Andrew↗

Electronic Visualization Laboratory's 50th Anniversary Retrospective: Look to the Future, Build on the Past

September 2023 marks the 50th anniversary of the Electronic Visualization Laboratory (EVL) at University of Illinois Chicago (UIC). EVL's introduction of the CAVE Automatic Virtual Environment in 1992, the first widely replicated, projection-based, walk-in, virtual-reality (VR) system in the world, put EVL at the forefront of collaborative, immersive data exploration and analytics. However, the journey did not begin then. Since its founding in 1973, EVL has been developing tools and techniques for real-time, interactive visualizations—pillars of VR. But EVL's culture is also relevant to its successes, as it has always been an interdisciplinary lab that fosters teamwork, where each person's expertise contributes to the development of the necessary tools, hardware, system software, applications, and human interface models to solve problems. Over the years, as multidisciplinary collaborations evolved and advanced scientific instruments and data resources were distributed globally, the need to access and share data and visualizations while working with colleagues, local and remote, synchronous and asynchronous, also became important fields of study. This paper is a retrospective of EVL's past 50 years that surveys the many networked, immersive, collaborative visualization and VR systems and applications it developed and deployed, as well as lessons learned and future plans.

Johnson, Andrew E.↗

A 15-Year Retrospective on Immersive Visualization Lessons from the Applied Visualization Laboratory

This article shares the experiences of operating an immersive visualization laboratory over a 15-year period. The paper discusses valuable insights into the lessons learned from various projects, including the challenges they faced, such as technical difficulties, user adoption, and opportunities, and practical solutions for overcoming them. One crucial element for successful immersive visualization projects is interdisciplinary collaboration. The paper presents the advantages of immersive visualization technology, such as improved data comprehension, enhanced communication, and increased engagement in complex scenarios. We present the dynamic realm of virtual and augmented truth (VR/AR) technology in the context of a immersive laboratory system. We spotlight rising trends inside the integration of VR/AR tools for visualization. We also present our experience in dealing with the hardware and software additives in an immersive VR/AR labs, dropping light on the demanding situations and successes encountered throughout everyday operations. Furthermore, it offers practical knowledge and guidance based on years of experience in the field, which can help you overcome challenges and achieve success in your project.

99 GENERAL AND MISCELLANEOUS↗

A Bird’s Eye View: Development of an Operational ARM Unmanned Aerial Capability for Atmospheric Research in Arctic Alaska

Here, we present that unmanned aerial capabilities offer exciting new perspectives on the Arctic atmosphere and the US Department of Energy is working with partners to offer such perspectives to the research community. Thorough understanding of aerosols, clouds, boundary layer structure and radiation is required to improve representation of the Arctic atmosphere in weather forecasting and climate models. To develop such understanding, new perspectives are needed to provide details on the vertical structure and spatial variability of key atmospheric properties, along with information over difficult-to-reach surfaces such as newly-forming sea ice. Over the last three years, the US Department of Energy (DOE) has supported various flight campaigns using unmanned aircraft systems (UAS, also known as UAVs and drones) and tethered balloon systems (TBS) at Oliktok Point, Alaska. These activities have featured in-situ measurements of thermodynamic state, turbulence, radiation, aerosol properties, cloud microphysics and turbulent fluxes to provide a detailed characterization of the lower atmosphere. Alongside a suite of active and passive ground-based sensors and radiosondes deployed by the DOE Atmospheric Radiation Measurement (ARM) program through the third ARM Mobile Facility (AMF-3), these flight activities demonstrate the ability of such platforms to provide critically-needed information. In addition to providing new and unique datasets, lessons learned during initial campaigns have assisted toward the development of an exciting new community resource.

54 ENVIRONMENTAL SCIENCES↗