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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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All sources NASA NTRS DOE OSTI

NASA NTRS1995

Job Scheduling Under the Portable Batch System

The typical batch queuing system schedules jobs for execution by a set of queue controls. The controls determine from which queues jobs may be selected. Within the queue, jobs are ordered first-in, first-run. This limits the set of scheduling policies available to a site. The Portable Batch System removes this limitation by providing an external scheduling module. This separate program has full knowledge of the available queued jobs, running jobs, and system resource usage. Sites are able to implement any policy expressible in one of several procedural language. Policies may range from "bet fit" to "fair share" to purely political. Scheduling decisions can be made over the full set of jobs regardless of queue or order. The scheduling policy can be changed to fit a wide variety of computing environments and scheduling goals. This is demonstrated by the use of PBS on an IBM SP-2 system at NASA Ames.

Henderson, Robert L.↗

DOE OSTI2025

Predicting runtime and resource utilization of jobs on integrated cloud and HPC systems

Recent advances in virtualization technologies used in cloud computing offer performance that closely approaches bare-metal levels. Combined with specialized instance types and high-speed networking services for cluster computing, cloud platforms have become a compelling option for high-performance computing (HPC). However, most current batch job schedulers in HPC systems are designed for homogeneous clusters and make decisions based on limited information about jobs and system status. Scientists typically submit computational jobs to these schedulers with a requested runtime that is often over- or under-estimated. More accurate runtime predictions can help schedulers make better decisions and reduce job turnaround times. Here, they can also support decisions about migrating jobs to the cloud to avoid long queue wait times in HPC systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Quantum Computing in the Cloud: Analyzing job and machine characteristics

As the popularity of quantum computing continues to grow, quantum machine access over the cloud is critical to both academic and industry researchers across the globe. And as cloud quantum computing demands increase exponentially, the analysis of resource consumption and execution characteristics are key to efficient management of jobs and resources at both the vendor-end as well as the client-end. While the analysis of resource consumption and management are popular in the classical HPC domain, it is severely lacking for more nascent technology like quantum computing. This paper is a first-of-its-kind academic study, analyzing various trends in job execution and resources consumption / utilization on quantum cloud systems. We focus on IBM Furthermore, quantum systems and analyze characteristics over a two year period, encompassing over 6000 jobs which contain over 600,000 quantum circuit executions and correspond to almost 10 billion “shots” or trials over 20+ quantum machines. Specifically, we analyze trends focused on, but not limited to, execution times on quantum machines, queuing/waiting times in the cloud, circuit compilation times, machine utilization, as well as the impact of job and machine characteristics on all of these trends. Furthermore, our analysis identifies several similarities and differences with classical HPC cloud systems. Based on our insights, we make recommendations and contributions to improve the management of resources and jobs on future quantum cloud systems.

42 ENGINEERING↗

DOE OSTI2021

Mitigating Inter-Job Interference via Process-Level Quality-of-Service

Jobs on most high-performance computing (HPC) systems share the network with other concurrently executing jobs. Network sharing leads to contention that can severely degrade performance. Here we investigate the use of Quality of Service (QoS) mechanisms to reduce the negative impacts of network contention. QoS allows users to manage resource sharing between network flows and to provide bandwidth guarantees to specific flows. Our results show that careful use of QoS reduces the impact of network contention for specific jobs, resulting in up to a 40% performance improvement. In some cases, it completely eliminates the impact of contention. It achieves these improvements with limited negative impact to other jobs; any job that experiences performance loss typically degrades less than 5%, and often much less. Our approach can help ensure that HPC machines maintain high levels of throughput as per-node compute power continues to increase faster than network bandwidth.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Is Knowledge about Running Applications Helping Improve Runtime Prediction of HPC Jobs?

High-performance computing systems rely upon scheduling algorithms to achieve high utilization. These schedulers rely upon user estimates of job resource requirements, such as runtime, to determine optimal scheduling of incoming jobs. These user estimates, however, are prone to error. To mitigate this error, significant research has been directed at providing better estimates of job runtime, usually employing machine learning techniques. These techniques are dependent upon the input features selected. Among the possible features is the primary application used by the job. In a survey of more than 20 papers directed at improving runtime prediction, only four included primary application as an input feature. We focus this investigation specifically on the value of adding primary application as an input feature, and find that it does improve model performance, especially for jobs with longer runtimes, though this improvement varies based on the application used. We recommend further research to determine the cause of this variability as well as an optimal strategy for employing a mixture of models both including and not including primary application as a feature.

MATHEMATICS AND COMPUTING↗

NASA NTRS1973

A program to reduce coronary heart disease risk by altering job stresses

This study reports the design, implementation, and evaluation of a program attempting to reduce job stress by improving person-environment fit with respect to job aspects such as work load, responsibility, and interpersonal relationships. In order to assess the effects of the program, measures of both stress and strain were collected at three points in time--just prior to the program, immediately after the program, and three months after completion of the program. Measures of strain included systolic and diastolic blood pressure, determinations of glucose, cholesterol, and uric acid in the plasma, job satisfaction, and job related self-esteem. The findings were interpreted in light of both program incidents within specific experimental groups and general aspects of the program common to the experimental groups. Additional analyses indicated that both good person-environment fit with respect to participation predicts to good fit with respect to other job aspects over a three month interval and that stress causes strain, rather than the reverse.

Campbell, D. B.↗

NASA NTRS1995

Job Management Requirements for NAS Parallel Systems and Clusters

A job management system is a critical component of a production supercomputing environment, permitting oversubscribed resources to be shared fairly and efficiently. Job management systems that were originally designed for traditional vector supercomputers are not appropriate for the distributed-memory parallel supercomputers that are becoming increasingly important in the high performance computing industry. Newer job management systems offer new functionality but do not solve fundamental problems. We address some of the main issues in resource allocation and job scheduling we have encountered on two parallel computers - a 160-node IBM SP2 and a cluster of 20 high performance workstations located at the Numerical Aerodynamic Simulation facility. We describe the requirements for resource allocation and job management that are necessary to provide a production supercomputing environment on these machines, prioritizing according to difficulty and importance, and advocating a return to fundamental issues.

Saphir, William↗

DOE OSTI2023

According to the U.S. Census Bureau, Florida had 13,466,496 people in its working population (15 to 64 years of age) in 2019. The graphs below show solar photovoltaic (PV), land-based wind, battery energy storage (BES), and energy efficiency job estimates in 2020, 2025, and 2030. These job estimates do not represent net job creation. Rather, they represent the size of the workforce required to achieve projected national deployment levels of each technology for 2025 and 2030 if the state captures the same proportion of jobs in the sector as it did in 2020.

clean energy↗