Explore the challenges and innovative solutions in data management for the Linac Coherent Light Source upgrade (LCLS-II) at SLAC National Accelerator Laboratory. Delve into the LCLS-II Data System architecture, designed to handle extreme data throughput of hundreds of GB/s to multi-TB/s. Learn about the feature extraction layer that aims to reduce data volumes while preserving scientific content, and discover the real-time analysis framework providing rapid visualization and configurable analysis. Examine the fast feedback layer offering dedicated processing resources for quick experimental data quality assessment. Gain insights into the Data Reduction Pipeline (DRP) and online monitoring framework, addressing the increasing velocity, volume, and complexity of data generated by cutting-edge free electron laser experiments.
Overview
Syllabus
Stanford Seminar - Data Analytics at the Exascale for Free Electron Lasers Project
Taught by
Stanford Online
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4.3 rating, based on 3 Class Central reviews
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Mabedi Vienna NnyepiThis lecture is about the data analytics challenges at the Stanford Linear Accelerator Center (SLAC) free-electron laser (LCL) project.
Here are some key points from the lecture:
* The LCL is a powerful tool for imaging samples at the atomic level.
* The LCL generates a very high rate of data.
* Traditional data analysis methods are not sufficient for handling LCL data.
* A two-stage data reduction approach is proposed to address the data challenges.
* The amount of computing power needed for LCL data analysis is significant and is expected to increase in the future.
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I recently completed the Data Analytics course, and I’m genuinely impressed with the experience. The course content was comprehensive, covering key areas such as data cleaning, visualization, statistical analysis, and the use of tools like Excel, SQL, and Python. The instructors were knowledgeable and provided clear, actionable insights, making complex concepts accessible
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I recently completed the Data Analytics course, and I’m genuinely impressed with the experience. The course content was comprehensive, covering key areas such as data cleaning, visualization, statistical analysis, and the use of tools like Excel, SQL, and Python. The instructors were knowledgeable and provided clear, actionable insights, making complex concepts accessible
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This course is very useful, and I learnt a lot from it.I really highly recommendate you can listen to this courses.
