Organizers: Dr. Cengiz Gunay and Dr. Anca Doloc-Mihu
School of Science and Technology, Georgia Gwinnett College, USA
Tutorial time:
| Time zone: | Los Angeles | New York | Berlin | Sydney |
|---|---|---|---|---|
| July 18, 2020 | 10am - 1pm | 1 - 4pm | 7 - 10pm | 3 - 6am (July 19) |
Description of the tutorial
Computational neuroscience projects often involve large number of simulations for parameter search of computer models, which generates large amount of data. With the advances in computer hardware, software methods, and cloud computing opportunities making this task easier, the amount of collected data has exploded, similar to what has been happening in many fields. High performance computing (HPC) methods have been used in the computational neuroscience field for a while. However, use of novel data science and big data methods are less frequent. In this tutorial, we will review established HPC methods and introduce novel data science tools to be used in computational neuroscience workflows, starting from the industry standard of Apache Hadoop to newer tools, such as Apache Spark. These tools can be used for either model simulation or post-processing and analysis of the generated data. To visualize the data, we will review novel web-based interactive dashboard technologies mostly based on Javascript and Python.
Software tools
Expected knowledge/materials
- Some familiarity with Python, Javascript, HTML
- For the visualization session: Google Account suggested to use the online Jupyter notebook service at Colab
Draft schedule
| Time from start | Speaker | Schedule item |
|---|---|---|
| 00:00 | Cengiz Gunay | From High Performance Computing to Hadoop and Spark (slides) |
| 00:50 | Break | |
| 01:00 | Anca Doloc-Mihu | High-dimensional data visualizations (slides and materials) |
| 01:50 | Break | |
| 02:00 | Hieu Dinh, Joshua Walton, Anthony Morariu | Analysim.tech: A data sharing site for crowdsourcing analysis of parameter-search datasets (slides and demo site) |
| 02:50 | Break before next session |