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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6

AIIO: Using Artificial Intelligence for Job-Level and Automatic I/O Performance Bottleneck Diagnosis

Manually diagnosing the I/O performance bottleneck for a single application (hereinafter referred to as the "job level'') is a tedious and error-prone procedure requiring domain scientists to have deep knowledge of complex storage systems. However, existing automatic methods for I/O performance bottleneck diagnosis have one major issue: the granularity of the analysis is at the platform or group level and the diagnosis results cannot be applied to the individual application. To address this issue, we designed and developed a method named "Artificial Intelligence for I/O"(AIIO), which uses AI and its interpretation technology to diagnose I/O performance bottlenecks at the job level automatically. By considering the sparsity of I/O log files, employing multiple AI models for performance prediction, merging diagnosis results across multiple models, and generalizing its performance prediction and diagnosis functions, AIIO can accurately and robustly identify the bottleneck of an even unseen application. Experimental results show that real and unseen applications can use the diagnosis results from AIIO to improve their I/O performance by at most 146 times.

Dong, Bin↗

JobQueue-PG: A Task Queue for Coordinating Varied Tasks Across Multiple HPC Resources and HPC Jobs

The software allows for queueing and dispatch of tasks of small, varied, or uncertain runtimes across multiple HPC jobs, resources, and other computing systems. The software was designed to allow scientists to enqueue, run, and accumulate results from computational experiments in an efficient, manageable manner. For example, the software can be used to enqueue many small computational experiments and run them using several long-running multi-node HPC jobs that may or may not run simultaneously.

Tripp, Charles↗

Scheduling real-time, periodic jobs using imprecise results

A process is called a monotone process if the accuracy of its intermediate results is non-decreasing as more time is spent to obtain the result. The result produced by a monotone process upon its normal termination is the desired result; the error in this result is zero. External events such as timeouts or crashes may cause the process to terminate prematurely. If the intermediate result produced by the process upon its premature termination is saved and made available, the application may still find the result unusable and, hence, acceptable; such a result is said to be an imprecise one. The error in an imprecise result is nonzero. The problem of scheduling periodic jobs to meet deadlines on a system that provides the necessary programming language primitives and run-time support for processes to return imprecise results is discussed. This problem differs from the traditional scheduling problems since the scheduler may choose to terminate a task before it is completed, causing it to produce an acceptable but imprecise result. Consequently, the amounts of processor time assigned to tasks in a valid schedule can be less than the amounts of time required to complete the tasks. A meaningful formulation of this problem taking into account the quality of the overall result is discussed. Three algorithms for scheduling jobs for which the effects of errors in results produced in different periods are not cumulative are described, and their relative merits are evaluated.

Liu, Jane W. S.↗

A hybrid job-shop scheduling system

The intention of the scheduling system developed at the Fraunhofer-Institute for Material Flow and Logistics is the support of a scheduler working in a job-shop. Due to the existing requirements for a job-shop scheduling system the usage of flexible knowledge representation and processing techniques is necessary. Within this system the attempt was made to combine the advantages of symbolic AI-techniques with those of neural networks.

Hellingrath, Bernd↗

Integrated Intelligent training and job aiding for combustion turbine engines

This paper describes an ongoing program to augment such an expert system gas turbine startup advisor, known as the EPRI SA VANT System, by including an intelligent training package. It will give a brief background on the SA VANT development and an overview of its evolution into a full-blown Gas Turbine Information System (GTIS) for rapid access of on-line documentation, diagnostics, and training. In particular, the paper will address: (1) the conversion of the knowledge base used by the SA VANT startup advisor so that it can be used for both training and job aiding; and (2) the hypertext-oriented user manuals being incorporated into the system for rapidly accessing on-line documentation at the job site.

Mckeithan, Clifford M., Jr.↗

NAS Requirements Checklist for Job Queuing/Scheduling Software

The increasing reliability of parallel systems and clusters of computers has resulted in these systems becoming more attractive for true production workloads. Today, the primary obstacle to production use of clusters of computers is the lack of a functional and robust Job Management System for parallel applications. This document provides a checklist of NAS requirements for job queuing and scheduling in order to make most efficient use of parallel systems and clusters for parallel applications. Future requirements are also identified to assist software vendors with design planning.

Jones, James Patton↗

A Comparison of Parameter Study Creation and Job Submission Tools

We consider the differences between the available general purpose parameter study and job submission tools. These tools necessarily share many features, but frequently with differences in the way they are designed and implemented For this class of features, we will only briefly outline the essential differences. However we will focus on the unique features which distinguish the ILab parameter study and job submission tool from other packages, and which make the ILab tool easier and more suitable for use in our research and engineering environment.

DeVivo, Adrian↗

Job Superscheduler Architecture and Performance in Computational Grid Environments

Computational grids hold great promise in utilizing geographically separated heterogeneous resources to solve large-scale complex scientific problems. However, a number of major technical hurdles, including distributed resource management and effective job scheduling, stand in the way of realizing these gains. In this paper, we propose a novel grid superscheduler architecture and three distributed job migration algorithms. We also model the critical interaction between the superscheduler and autonomous local schedulers. Extensive performance comparisons with ideal, central, and local schemes using real workloads from leading computational centers are conducted in a simulation environment. Additionally, synthetic workloads are used to perform a detailed sensitivity analysis of our superscheduler. Several key metrics demonstrate that substantial performance gains can be achieved via smart superscheduling in distributed computational grids.

Shan, Hongzhang↗

PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs

It is generally desirable for high-performance computing (HPC) applications to be portable between HPC systems, for example to make use of more performant hardware, make effective use of allocations, and to co-locate compute jobs with large datasets. Unfortunately, moving scientific applications between HPC systems is challenging for various reasons, most notably that HPC systems have different HPC schedulers. We introduce PSI/J, a job management abstraction API intended to simplify the construction of software components and applications that are portable over various HPC scheduler implementations. We argue that such a system is both necessary and that no viable alternative currently exists. We analyze similar notable APIs and attempt to determine the factors that influenced their evolution and adoption by the HPC community. We base the design of PSI/J on that analysis. We describe how PSI/J has been integrated in three workflow systems and one application, and also show via experiments that PSI/J imposes minimal overhead.

Hategan, Mihael↗

Alternative mixed integer linear programming optimization for joint job scheduling and data allocation in grid computing

This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer quadratically constrained program. To tackle the nonlinearity in the constraint, we alternatively fix a subset of decision variables and optimize the remaining ones via Mixed Integer Linear Programming (MILP). We solve the MILP problem at each iteration via an off-the-shelf MILP solver. Our experimental results show that our method significantly outperforms existing heuristic methods, employing either independent optimization or joint optimization strategies. We have also verified the generalization ability of our method over grid environments with various sizes and its high robustness to the algorithm setting.

97 MATHEMATICS AND COMPUTING↗

International Jobs and Economic Development Impacts Model: Stories of Use and Impact

The International Jobs and Economic Development Impacts (I-JEDI) model is a freely available economic model that estimates gross economic impacts from wind, solar, biopower, and geothermal energy projects around the world. This short publication outlines how the tool has been used by organizations around the world.

economic development↗

Exploiting Kubernetes to Simplify the Deployment and Management of the Multi-purpose CMS Pilot Job Factory

GlideinWMS, a widely utilized workload management system in high-energy physics (HEP) research, serves as the backbone for efficient job provisioning across distributed computing resources. It is utilized by various experiments and organizations, including CMS, OSG, Dune, and FIFE, to create HTCondor pools as large as 600k cores. In particular, a shared factory service historically deployed at UCSD has been configured to interface with more than 500 routes to compute clusters. As part of our team’s initiative to modernize infrastructure and enhance scalability, we undertook the migration of the GlideinWMS factory service into the Kubernetes environment. Leveraging the flexibility and orchestration capabilities of Kubernetes, we successfully deployed the factory service within the OSG Tiger Kubernetes cluster. The major benefits Kubernetes gives us is it streamlines the management and monitoring of the factory infrastructure, and improves fault tolerance through its resilient deployment strategies. Through this case study, we aim to share insights, challenges, and best practices encountered during the migration process. Our experience underscores the benefits of embracing containerization and Kubernetes orchestration for HEP computing infrastructure, paving the way for scalability and resilience in distributed computing environments.

Dost, Jeffrey Michael [UC, San Diego (main)]↗

RCT Continuing Training: RCT Job Coverage and CONOPS

RCT Continuing Training covering all of the necessary steps associated with RCT, and how conduct of operations ties in with this process. The terminal objective of this training is: Given the need to perform radiological job coverage, recognize the requirements to maintain radiological work control in accordance with P121, Radiation Protection, RP-PROG-TP-200, Radiation Protection Manual, and P315, Conduct of Operations.

61 RADIATION PROTECTION AND DOSIMETRY↗

LABCON - Laboratory Job Control program

Computer program LABCON controls the budget system in a component test laboratory whose workload is made up from many individual budget allocations. A common denominator is applied to an incoming job, to which all effort is charged and accounted for.

Reams, L. T.↗