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At least 631 records · Page 35

Efficient Synthesis of Graph Methods: a Dynamically Scheduled Architecture

RDF databases naturally map to a graph representation and employ languages, such as SPARQL, that implements queries as graph pattern matching routines. Graph methods exhibit an irregular behavior: they present unpredictable, fine-grained data accesses, and are synchronization inten- sive. Graph data structures expose large amounts of dy- namic parallelism, but are difficult to partition without gen- erating load unbalance. In this paper, we present a novel ar- chitecture to improve the synthesis of graph methods. Our design addresses the issues of these algorithms with two com- ponents: a Dynamic Task Scheduler (DTS), which reduces load unbalance and maximize resource utilization, and a Hi- erarchical Memory Interface controller (HMI), which pro- vides support for concurrent memory operations on multi- ported/multi-banked shared memories. We evaluate our ap- proach by generating the accelerators for a set of SPARQL queries from the Lehigh University Benchmark (LUBM). We first analyze the load unbalance of these queries, showing that execution time among tasks can differ even of order of magnitudes. We then synthesize the queries and com- pare the performance of the resulting accelerators against the current state of the art. Experimental results show that our solution provides a speedup over the serial implementa- tion close to the theoretical maximum and a speedup up to 3.45 over a baseline parallel implementation. We conclude our study by exploring the design space to achieve maximum memory channels utilization. The best design used at least three of the four memory channels for more than 90% of the execution time.

architecture↗

Highlights of X-Stack ExM Deliverable: MosaStore

This brief report highlights the experience gained with MosaStore, an exploratory part of the X-Stack project “ExM: System support for extreme-scale, many-task applications”. The ExM project proposed to use concurrent workflows supported by the Swift language and runtime as an innovative programming model to exploit parallelism in exascale computers. MosaStore aims to support this endeavor by improving storage support for workflow-based applications, more precisely by exploring the gains that can be obtained from co-designing the storage system and the workflow runtime engine. MosaStore has been developed primarily at the University of British Columbia.

97 MATHEMATICS AND COMPUTING↗

Autoplan: A self-processing network model for an extended blocks world planning environment

Self-processing network models (neural/connectionist models, marker passing/message passing networks, etc.) are currently undergoing intense investigation for a variety of information processing applications. These models are potentially very powerful in that they support a large amount of explicit parallel processing, and they cleanly integrate high level and low level information processing. However they are currently limited by a lack of understanding of how to apply them effectively in many application areas. The formulation of self-processing network methods for dynamic, reactive planning is studied. The long-term goal is to formulate robust, computationally effective information processing methods for the distributed control of semiautonomous exploration systems, e.g., the Mars Rover. The current research effort is focusing on hierarchical plan generation, execution and revision through local operations in an extended blocks world environment. This scenario involves many challenging features that would be encountered in a real planning and control environment: multiple simultaneous goals, parallel as well as sequential action execution, action sequencing determined not only by goals and their interactions but also by limited resources (e.g., three tasks, two acting agents), need to interpret unanticipated events and react appropriately through replanning, etc.

Dautrechy, C. Lynne↗

Displacement Based Multilevel Structural Optimization

In the complex environment of true multidisciplinary design optimization (MDO), efficiency is one of the most desirable attributes of any approach. In the present research, a new and highly efficient methodology for the MDO subset of structural optimization is proposed and detailed, i.e., for the weight minimization of a given structure under size, strength, and displacement constraints. Specifically, finite element based multilevel optimization of structures is performed. In the system level optimization, the design variables are the coefficients of assumed polynomially based global displacement functions, and the load unbalance resulting from the solution of the global stiffness equations is minimized. In the subsystems level optimizations, the weight of each element is minimized under the action of stress constraints, with the cross sectional dimensions as design variables. The approach is expected to prove very efficient since the design task is broken down into a large number of small and efficient subtasks, each with a small number of variables, which are amenable to parallel computing.

Sobieszezanski-Sobieski, J.↗

Vestibular and Somatosensory Covergence in Postural Equilibrium Control: Insights from Spaceflight and Bed Rest Studies

The goal of the Functional Task Test study is to determine the effects of space flight on functional tests that are representative of high priority exploration mission tasks and to identify the key underlying physiological factors that contribute to decrements in performance. We are currently conducting studies on both International Space Station (ISS) astronauts experiencing up to 6 months of microgravity and subjects experiencing 70 days of 6head-down bed-rest as an analog for space flight. Bed-rest provides the opportunity for us to investigate the role of prolonged axial body unloading in isolation from the other physiological effects produced by exposure to the microgravity environment of space flight. This allows us to parse out the contribution of the body unloading somatosensory component on functional performance. Both ISS crewmembers and bed-rest subjects were tested using a protocol that evaluated functional performance along with tests of postural and locomotor control before and after space flight and bed-rest, respectively. Functional tests included ladder climbing, hatch opening, jump down, manual manipulation of objects and tool use, seat egress and obstacle avoidance, recovery from a fall, and object translation tasks. Astronauts were tested three times before flight, and on 1, 6, and 30 days after landing. Bed-rest subjects were tested three times before bed-rest and immediately after getting up from bed-rest as well as 1, 6, and 12 days after re-ambulation. A comparison of bed-rest and space flight data showed a significant concordance in performance changes across all functional tests. Tasks requiring a greater demand for dynamic control of postural equilibrium (i.e. fall recovery, seat egress/obstacle avoidance during walking, object translation, jump down) showed the greatest decrement in performance. Functional tests with reduced requirements for postural stability showed less reduction in performance. Results indicate that body unloading resulting from prolonged bed-rest impacts functional performance particularly for tests with a greater requirement for postural equilibrium control. These changes in functional performance were paralleled by similar decrement in tests designed to specifically assess postural equilibrium and dynamic gait control. These results indicate that body support unloading experienced during space flight plays a central role in postflight alteration of functional task performance. These data also support the concept that space flight may cause central adaptation of converging body-load somatosensory and vestibular input during gravitational transitions.

Mulavara, A. P.↗

X-HAB 2020: AR Field Treks Summary and Conclusions

As part of the FY20 X-Hab Challenge, BLiSS sought to create an Augmented Reality (AR) toolkit to help with analog field trek operations under the supervision of the Solar System Exploration Research Virtual Institute (SSERVI). These treks are operational and technical demonstrations at space-like destinations on Earth to test current extra-vehicular activity (EVA) techniques. While BLiSS as an organization has experience studying operational tasks such as this, it has never developed AR software at this scale. For that reason, another team at the University was brought on to work in parallel. The Collaborative Lab for Advancing Work in Space (CLAWS) is a veteran group of the NASA Spacesuit User Interface Technologies for Students (SUITS) challenge in which Hololens displays for astronauts are created within a year. The operational and technological pairing was ideally suited for tackling this problem. The team divided its responsibilities so that BLiSS would handle the research required to shape the project. As this deliverable had an end user, it was decided that interviewing these field geologists and operations specialists would provide the best insight. These interviews paired with literature review would reveal niche applications for AR that remained within feasible bounds. These science-driven EVAs in unknown terrain require more flexible tools than the current generation of EVA assistants. Rather than focus on sequential instructions, there instead needs to be a broad toolkit that's only called upon in specific instances. This AR Toolkit for Lunar Astronauts and Scientists (ATLAS) became the development goal of the project: create a non-intrusive assembly of tools that could be accessed in AR on the field. The current ATLAS design makes use of a geospatially and temporally annotated eld note system called GeoNotes. This allows for data to be collected and coordinated in a way that's synchronized across time, space, and different users. A Mission Control Center (MCC) and Mobile Support Equipment (MSE) were all needed to transport the AR headset into the field with the user. A network infrastructure was designed and set up within the University to enable this functionality. The software is based on a Protocol-Module structure that allows for modular development of each capability. A Protocol Manager coordinates different protocols that make use of modules. Each module tackles a different individual task while the protocol puts each one to use. The protocol manager coordinates when these are called to be used. This software is hosted on a head-mounted display (HMD) with the MCC acting as support from afar. While the software would be unit-tested at each level and each hardware component verified, a final demonstration would serve to prove the system's capabilities: an analog field trek. The team would prepare to support a user in a remote location from the MCC back at the University. A local area near campus would be tested before going out to do sample field geology further away. This unfortunately became impossible with the arrival of COVID-19. Access to all of the facilities to complete the project as planned were shut down. Our team was scattered across the globe and forced to complete the rest virtually. Adjustments were made to produce a small virtual concept in Adobe XD in the meantime. Even digital surveys were created based on the NASA task-load index (TLX) originally intended for testing actual users. The goal shifted towards completing software and getting feedback on the user interfaces (UI) and user experiences (UX). This team has reformed in response to COVID and its focus has shifted to what can be done remotely. There is still an intention to finish the original deliverable described in this report. The work has been expanded beyond the original X-Hab challenge and has instead become its own research e ort to be continued afterwards. This report collects the processes and knowledge gained from a year of studying and working at this problem with two teams. It should preserve it for the time until the world returns to normal and work can resume. CLAWS will be taking over full responsibility from that point forward, eventually surpassing the original needs of the project. While this document captures the work done towards an eventual end, the CLAWS team has written their own proposal alongside it. It outlines a new future for ATLAS beyond X-Hab, BLiSS, and hopefully beyond COVID-19. This project began as a vague goal hoping to place a new technology into the unique setting of exploration science. The project has since comfortably taken root and will hopefully bloom over the next year.

Alex Sena↗

Experiences with Cray multi-tasking

The issues involved in modifying an existing code for multitasking is explored. They include Cray extensions to FORTRAN, an examination of the application code under study, designing workable modifications, specific code modifications to the VAX and Cray versions, performance, and efficiency results. The finished product is a faster, fully synchronous, parallel version of the original program. A production program is partitioned by hand to run on two CPUs. Loop splitting multitasks three key subroutines. Simply dividing subroutine data and control structure down the middle of a subroutine is not safe. Simple division produces results that are inconsistent with uniprocessor runs. The safest way to partition the code is to transfer one block of loops at a time and check the results of each on a test case. Other issues include debugging and performance. Task startup and maintenance (e.g., synchronization) are potentially expensive.

Miya, E. N.↗

I/O in Machine Learning Applications on HPC Systems: A 360-degree Survey

Growing interest in Artificial Intelligence (AI) has resulted in a surge in demand for faster methods of Machine Learning (ML) model training and inference. This demand for speed has prompted the use of high performance computing (HPC) systems that excel in managing distributed workloads. Because data is the main fuel for AI applications, the performance of the storage and I/O subsystem of HPC systems is critical. In the past, HPC applications accessed large portions of data written by simulations or experiments or ingested data for visualizations or analysis tasks. ML workloads perform small reads spread across a large number of random files. This shift of I/O access patterns poses several challenges to modern parallel storage systems. In this paper, we survey I/O in ML applications on HPC systems, and target literature within a 6-year time window from 2019 to 2024. We define the scope of the survey, provide an overview of the common phases of ML, review available profilers and benchmarks, examine the I/O patterns encountered during offline data preparation, training, and inference, and explore I/O optimizations utilized in modern ML frameworks and proposed in recent literature. Lastly, we seek to expose research gaps that could spawn further R&D.

97 MATHEMATICS AND COMPUTING↗

Advanced Turbofan Duct Liner Concepts

The Advanced Subsonic Technology Noise Reduction Program goal is to reduce aircraft noise by 10 EPNdB by the year 2000 relative, to 1992 technology. The improvement goal for nacelle attenuation is 25% relative to 1992 technology by 1997 and 50% by 2000. The Advanced Turbofan Duct Liner Concepts Task work by Boeing presented in this document was in support of these goals. The basis for the technical approach was a Boeing study conducted in 1993-94 under NASA/FAA contract NAS1-19349, Task 6, investigating broadband acoustic liner concepts. As a result of this work, it was recommended that linear double layer, linear and perforate triple layer, parallel element, and bulk absorber liners be further investigated to improve nacelle attenuations. NASA LaRC also suggested that "adaptive" liner concepts that would allow "in-situ" acoustic impedance control also be considered. As a result, bias flow and high-temperature liner concepts were also added to the investigation. The major conclusion from the above studies is that improvements in nacelle liner average acoustic impedance characteristics alone will not result in 25% increased nacelle noise reduction relative to 1992 technology. Nacelle design advancements currently being developed by Boeing are expected to add 20-40% more acoustic lining to hardwall regions in current inlets, which is predicted to result in and additional 40-80% attenuation improvement. Similar advancements are expected to allow 10-30% more acoustic lining in current fan ducts with 10-30% more attenuation expected. In addition, Boeing is currently developing a scarf inlet concept which is expected to give an additional 40-80% attenuation improvement for equivalent lining areas.

Bielak, Gerald W.↗

Parallel Directionally Split Solver Based on Reformulation of Pipelined Thomas Algorithm

In this research an efficient parallel algorithm for 3-D directionally split problems is developed. The proposed algorithm is based on a reformulated version of the pipelined Thomas algorithm that starts the backward step computations immediately after the completion of the forward step computations for the first portion of lines This algorithm has data available for other computational tasks while processors are idle from the Thomas algorithm. The proposed 3-D directionally split solver is based on the static scheduling of processors where local and non-local, data-dependent and data-independent computations are scheduled while processors are idle. A theoretical model of parallelization efficiency is used to define optimal parameters of the algorithm, to show an asymptotic parallelization penalty and to obtain an optimal cover of a global domain with subdomains. It is shown by computational experiments and by the theoretical model that the proposed algorithm reduces the parallelization penalty about two times over the basic algorithm for the range of the number of processors (subdomains) considered and the number of grid nodes per subdomain.

Povitsky, A.↗

Characterization and identification of HPC applications at leadership computing facility

High Performance Computing (HPC) is an important method for scientific discovery via large-scale simulation, data analysis, or artificial intelligence. Leadership-class supercomputers are expensive, but essential to run large HPC applications. The Petascale era of supercomputers began in 2008, with the first machines achieving performance in excess of one petaflops, and with the advent of new supercomputers in 2021 (e.g., Aurora, Frontier), the Exascale era will soon begin. However, the high theoretical computing capability (i.e., peak FLOPS) of a machine is not the only meaningful target when designing a supercomputer, as the resources demand of applications varies. A deep understanding of the characterization of applications that run on a leadership supercomputer is one of the most important ways for planning its design, development and operation. In order to improve our understanding of HPC applications, user demands and resource usage characteristics, we perform correlative analysis of various logs for different subsystems of a leadership supercomputer. This analysis reveals surprising, sometimes counter-intuitive patterns, which, in some cases, conflicts with existing assumptions, and have important implications for future system designs as well as supercomputer operations. For example, our analysis shows that while the applications spend significant time on MPI, most applications spend very little time on file I/O. Combined analysis of hardware event logs and task failure logs show that the probability of a hardware FATAL event causing task failure is low. Combined analysis of control system logs and file I/O logs reveals that pure POSIX I/O is used more widely than higher level parallel I/O. Based on holistic insights of the application gained through combined and co-analysis of multiple logs from different perspectives and general intuition, we engineer features to "fingerprint" HPC applications. We use t-SNE (a machine learning technique for dimensionality reduction) to validate the explainability of our features and finally train machine learning models to identify HPC applications or group those with similar characteristic. To the best of our knowledge, this is the first work that combines logs on file I/O, computing, and inter-node communication for insightful analysis of HPC applications in production.

Liu, Zhengchun↗

ExaTN

A challenging scientific problem that will benefit from exascale computing is predictive simulation of two- and three-dimensional quantum many-body Hamiltonians in condensed matter physics, together with the related strong entanglement problems in quantum chemistry and quantum computing. Efficient numerical simulations will require new insights into wavefunction compression algorithms that scale on extremely heterogeneous HPC architectures. To address this need, we propose to develop a scalable math library of parallel multi-linear algebraic numerical primitives for hierarchical tensor compression. Our library will subsequently be used for building an efficient, performance-portable HPC framework for simulating strongly correlated quantum systems. In particular, our will will be the first to deliver a massively parallel implementation of the multiscale entanglement renormalization ansatz (MERA), a hierarchical tensor decomposition quantum scheme capable of expressing local expectation values of strongly entangled higher-dimensional quantum systems efficiently. To address the extreme complexity and high computational cost of such schemes, we will automate their parallel implementation by delivering an integrated software framework, ExaTN (Exascale Tensor Networks), that will process hierarchical tensor representations on exascale HPC systems via an asymchronous task-based programming model. As a specific application, our framework will provide scientists with a capability of simulating strongly entangled quantum systems, thus positioning ORNL as a strategic leader in modeling of strongly correlated materials.

McCaskey, AlexanderJ↗

DIVA/DeviceEditor v6.1.2

DIVA is an end-to-end DNA design and construction management platform that streamlines how researchers design, build, and receive sequence-verified DNA constructs. Through a web-based BioCAD interface (DeviceEditor), researchers independently design DNA constructs and submit them to a centralized queue with a single action. Designs progress transparently through standardized states which allow researchers to track status and access finished constructs via a central DNA repository. Submitted designs are reviewed by dedicated staff for feasibility and optimization, reducing costly failures and improving downstream execution. Automated DNA assembly software optimizes construction strategies by reusing existing parts where possible and sourcing synthetic DNA only when needed. Standardized, sequence-agnostic assembly methods enable many independent constructs to be built in parallel using lab automation, dramatically increasing throughput. High-throughput next-generation sequencing is used to verify construct accuracy, with flexible platforms selected based on task requirements. Throughout the process, detailed success and failure data are captured and analyzed, enabling continuous improvement of assembly protocols. Compared to traditional, manual DNA construction workflows, DIVA offers higher scalability, transparency, reproducibility, and data-driven optimization.

Plahar, Hector [Lawrence Berkeley National Laborat↗

Advances in Domain Mapping of Massively Parallel Scientific Computations

One of the most important concerns in parallel computing is the proper distribution of workload across processors. For most scientific applications on massively parallel machines, the best approach to this distribution is to employ data parallelism; that is, to break the datastructures supporting a computation into pieces and then to assign those pieces to different processors. Collectively, these partitioning and assignment tasks comprise the domain mapping problem.

97 MATHEMATICS AND COMPUTING↗

Addressing Thermal and Performance Variability Issues in Dynamic Processors

As CMOS scaling nears its end, parameter variations (process, temperature and voltage) are becoming a major concern. To overcome parameter variations and provide stability, modern processors are becoming dynamic, opportunistically adjusting voltage and frequency based on thermal and energy constraints, which negatively impacts traditional bulk-synchronous parallelism-minded hardware and software designs. As node-level architecture is growing in complexity, implementing variation control mechanisms only with hardware can be a challenging task. In this paper we investigate a software strategy to manage hardwareinduced variations, leveraging low-level monitoring/controlling mechanisms.

97 MATHEMATICS AND COMPUTING↗

P and W/GE propulsion systems studies introduction

The topics covered include the following: Pratt and Whitney (P&W)/ General Electric (GE) High Speed Civil Transport (HSCT) collaboration - joint propulsion studies and parallel technical organization; HSCT engine concepts; engine cycle/design ground rules - 2005 entry into service; engine evaluation criteria; 1991 HSCT system studies plan; P&W NASA study tasks; and GE NASA study tasks.

Gilkey, Samual C.↗

Issues in Airborne Systems for Closely-Spaced Parallel Runway Operations

Efforts to increase airport capacity include studies of aircraft systems that would enable simultaneous approaches to closely spaced parallel runways in Instrument Meteorological Conditions (IMC). The time-critical nature of a parallel approach results in key design issues for current and future collision avoidance systems. These issues are being studied in two ways. First, a part-task flight simulator study has examined the procedural and display issues inherent in such a time-critical task. Second, a prototype collision avoidance logic capable of generating this maneuver guidance has been designed using a recently developed methodology.

Pritchett, A.↗

Intern Poster Session 08/13: Autonomous Nuclear Robotics: Applications in nuclear waste inspection and hot cell experiments

The nuclear industry is experiencing renewed interest in autonomous robotics, yet most deployed systems remain teleoperated with limited autonomy. This work presents two contributions toward fully autonomous nuclear robotic systems: autonomous waste inspection at the Hanford Site and an autonomous hot cell laboratory framework. Inspections of Hanford's underground waste storage tanks are performed manually at significant cost and personnel exposure. We developed a reinforcement-learning (RL) training pipeline for a custom-built inspection arm. In parallel, we are designing an autonomous laboratory framework for post-irradiation examination in hot cells at the Specimen Preparation Laboratory (SPL) that integrates computer vision, task and motion planning, hardware execution, and operator-in-the-loop control. These systems demonstrate a path toward safer, more efficient nuclear operations by reducing human exposure while maintaining rigorous human oversight at critical decision points.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗