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Characteristics of Workload on ASCI Blue-Pacific at Lawrence Livermore National Laboratory.


DE200415006159

Publication Date 2000
Personal Author Yoo, A. B.; Jette, M. A.
Page Count 26
Abstract Symmetric multiprocessor (SMP) clusters have become the prevalent computing platforms for large-scale scientific computation in recent years mainly due to their good scalability. In fact, many parallel machines being used at supercomputing centers and national laboratories are of this type. It is critical and often very difficult on such large-scale parallel computers to efficiently manage a stream of jobs, whose requirement for resources and computing time greatly varies. Understanding the characteristics of workload imposed on a target environment plays a crucial role in managing system resources and developing an efficient resource management scheme. A parallel workload is analyzed typically by studying the traces from actual production parallel machines. The study of the workload traces not only provides the system designers with insight on how to design good processor allocation and job scheduling policies for efficient resource management, but also helps system administrators monitor and fine-tune the resource management strategies and algorithms.
Keywords
  • Array processors
  • Lawrence Livermore National Laboratory
  • Resource management
  • Computers
  • Design
  • Monitors
  • Performance
  • Production
  • Targets
  • Algorithms
Source Agency
  • Technical Information Center Oak Ridge Tennessee
Corporate Authors Lawrence Livermore National Lab., CA.; Department of Energy, Washington, DC.
Supplemental Notes Sponsored by Department of Energy, Washington, DC.
Document Type Technical Report
NTIS Issue Number 200413
Characteristics of Workload on ASCI Blue-Pacific at Lawrence Livermore National Laboratory.
Characteristics of Workload on ASCI Blue-Pacific at Lawrence Livermore National Laboratory.
DE200415006159

  • Array processors
  • Lawrence Livermore National Laboratory
  • Resource management
  • Computers
  • Design
  • Monitors
  • Performance
  • Production
  • Targets
  • Algorithms
  • Technical Information Center Oak Ridge Tennessee
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