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Statistical Characterization of HPC Monitoring DataBachelor ThesisUniversity of Basel Faculty of Science Department of Mathematics and Computer Science HPC Research GroupExaminer: Prof. Dr. Florina M. Ciorba Supervisor: Thomas JakobscheMonika Multani monika.multani@stud.unibas.chDecember 21, 2021AbstractScientific applications use high computing power offered by High Performance Computing (HPC) systems to solve research questions. The use of system resources is recorded by monitoring...

How to fill out statistical characterization of hpc

How to fill out statistical characterization of hpc

1. Identify the purpose of the statistical characterization for the HPC system.
2. Collect relevant data including performance metrics, workload characteristics, and resource utilization.
3. Define the key performance indicators (KPIs) that will be used in the characterization.
4. Organize the data collected into a structured format for analysis.
5. Perform statistical analysis on the data to identify patterns and trends.
6. Document the findings clearly and concisely, ensuring all KPIs are covered.
7. Review the document to ensure accuracy and completeness before final submission.

Who needs statistical characterization of hpc?

1. HPC system administrators
2. Performance analysts
3. Researchers utilizing HPC resources
4. IT managers overseeing HPC operations
5. Funding agencies requiring performance documentation
6. Industry professionals looking to optimize HPC usage

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What is statistical characterization of hpc?

Statistical characterization of high-performance computing (HPC) refers to the systematic collection and analysis of data related to the performance, usage, and efficiency of HPC systems, enabling better resource management and optimization.

Who is required to file statistical characterization of hpc?

Organizations and institutions that operate high-performance computing systems, particularly those receiving public funding or those that are mandated to report on their computing resources, are typically required to file a statistical characterization of HPC.

How to fill out statistical characterization of hpc?

To fill out the statistical characterization of HPC, one should collect relevant performance metrics, resource usage statistics, and user access data, and then input this information into the designated reporting format or tool as specified by the relevant authority overseeing HPC activities.

What is the purpose of statistical characterization of hpc?

The purpose of the statistical characterization of HPC is to assess the performance and efficiency of computing resources, facilitate resource allocation decisions, enhance budgeting, and guide strategic planning for future investments in computing infrastructure.

What information must be reported on statistical characterization of hpc?

Information that must be reported includes system specifications (hardware and software), performance benchmarks, resource utilization statistics, user demographics, service usage patterns, and any relevant performance metrics related to computational tasks executed.