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Pipe Flowrate Measurement01:28

Pipe Flowrate Measurement

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In pipe flow measurement, orifice, nozzle, and Venturi meters are commonly used to determine fluid flowrates by constricting the flow area, which increases fluid velocity and reduces pressure. This pressure difference, governed by Bernoulli's principle and adjusted for real-world conditions, is essential for calculating flowrate. Each meter type is suited to specific applications based on accuracy, efficiency, and compatibility with various flow conditions.
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Updated: Jul 18, 2025

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
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Container Profiler: Profiling resource utilization of containerized big data pipelines.

Varik Hoang1, Ling-Hong Hung1, David Perez1

  • 1School of Engineering and Technology, University of Washington, Tacoma, WA 98402, USA.

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|August 25, 2023
PubMed
Summary
This summary is machine-generated.

The Container Profiler tool monitors CPU, memory, disk, and network usage for containerized tasks. This enables continuous resource monitoring and bottleneck identification in complex applications.

Keywords:
RNA sequencingcloud computingperformanceresource profilingtesting

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Area of Science:

  • Computer Science
  • Bioinformatics

Background:

  • Containerization is widely used for deploying applications.
  • Monitoring resource utilization is crucial for performance optimization.
  • Existing tools may not offer granular, continuous profiling for complex pipelines.

Purpose of the Study:

  • Introduce the Container Profiler, a novel software tool.
  • Evaluate the tool's effectiveness in profiling containerized tasks.
  • Assess the resource consumption of a bioinformatics pipeline.

Main Methods:

  • Developed Container Profiler to collect over 60 Linux OS metrics.
  • Profiled CPU, memory, disk, and network utilization.
  • Performed time-series profiling at configurable intervals.
  • Quantified profiling overhead across different granularity levels.

Main Results:

  • Container Profiler successfully measured resource usage for a multistage bioinformatics pipeline (RNA sequencing).
  • Identified patterns in CPU, disk, and network utilization across pipeline stages.
  • Profiling overhead was found to be negligible, even with high granularity.

Conclusions:

  • Container Profiler is a valuable tool for continuous monitoring of containerized applications.
  • Facilitates identification of resource bottlenecks in local or cloud-based deployments.
  • Aids in optimizing performance of complex, long-running containerized tasks.