scholarly journals Elastic scheduling for flexible workload management

2002 ◽  
Vol 51 (3) ◽  
pp. 289-302 ◽  
Author(s):  
G.C. Buttazzo ◽  
G. Lipari ◽  
M. Caccamo ◽  
L. Abeni
Keyword(s):  
Workload Management ◽  
Elastic Scheduling

Elastic scheduling in real-time systems

2013 ◽  
Vol 32 (2) ◽  
pp. 573-577
Author(s):  
Zhi-bang YANG ◽  
Cheng XU ◽  
Xu ZHOU ◽  
Xue-qing ZHU
Keyword(s):  
Real Time ◽  
Real Time Systems ◽  
Time Systems ◽  
Elastic Scheduling

The Workload Management System for Nursing

1990 ◽  
Author(s):  
DEPARTMENT OF THE ARMY WASHINGTON DC
Keyword(s):  
Management System ◽  
Workload Management

scholarly journals HPC Cloud Architecture to Reduce HPC Workflow Complexity in Containerized Environments

2021 ◽  
Vol 11 (3) ◽  
pp. 923
Author(s):  
Guohua Li ◽  
Joon Woo ◽  
Sang Boem Lim
Keyword(s):  
High Performance ◽  
Cloud Services ◽  
Workload Management ◽  
Job Management ◽  
Security Issues ◽  
Cloud Architecture ◽  
Management Efficiency ◽  
Complexity Problem ◽  
And Performance ◽  
Hpc Cloud

The complexity of high-performance computing (HPC) workflows is an important issue in the provision of HPC cloud services in most national supercomputing centers. This complexity problem is especially critical because it affects HPC resource scalability, management efficiency, and convenience of use. To solve this problem, while exploiting the advantage of bare-metal-level high performance, container-based cloud solutions have been developed. However, various problems still exist, such as an isolated environment between HPC and the cloud, security issues, and workload management issues. We propose an architecture that reduces this complexity by using Docker and Singularity, which are the container platforms most often used in the HPC cloud field. This HPC cloud architecture integrates both image management and job management, which are the two main elements of HPC cloud workflows. To evaluate the serviceability and performance of the proposed architecture, we developed and implemented a platform in an HPC cluster experiment. Experimental results indicated that the proposed HPC cloud architecture can reduce complexity to provide supercomputing resource scalability, high performance, user convenience, various HPC applications, and management efficiency.

scholarly journals The CMS monitoring infrastructure and applications

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Christian Ariza-Porras ◽  
Valentin Kuznetsov ◽  
Federica Legger
Keyword(s):  
Distributed Computing ◽  
Compact Muon Solenoid ◽  
Hadron Collider ◽  
Efficient Operation ◽  
Workload Management ◽  
Future Developments ◽  
Cms Experiment ◽  
Data Transfers ◽  
Monitoring Architecture ◽  
Globally Distributed

AbstractThe globally distributed computing infrastructure required to cope with the multi-petabyte datasets produced by the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) at CERN comprises several subsystems, such as workload management, data management, data transfers, and submission of users’ and centrally managed production requests. To guarantee the efficient operation of the whole infrastructure, CMS monitors all subsystems according to their performance and status. Moreover, we track key metrics to evaluate and study the system performance over time. The CMS monitoring architecture allows both real-time and historical monitoring of a variety of data sources. It relies on scalable and open source solutions tailored to satisfy the experiment’s monitoring needs. We present the monitoring data flow and software architecture for the CMS distributed computing applications. We discuss the challenges, components, current achievements, and future developments of the CMS monitoring infrastructure.

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