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How to Analyze Your Time-Dependent Data 6 Times Faster
TECPLOT WEBINAR - Parts of the post-processing pipeline are inherently single-threaded - data loading and rendering come to mind. The challenge is how to reduce these bottlenecks to speed up the process.
Date: April 3, 2019
Location: United States
Web Page:
Contact Email:
Organizer: Tecplot, Inc
Application Areas: Aerospace
Special Fields: High Performance Computing
Softwares: Tecplot
Type of Event: Seminar, International

Let’s face it, analyzing large amounts of transient data 
can take forever. Animating images to a movie can take an 
entire weekend to complete. Why can’t Tecplot just do it 
for me, and do it faster? 

This Webinar will show you how the power of Python can 
take advantage of multi-process parallelism.  Using 
Tecplot 360’s Python API, PyTecplot, you can get your 
results up to six times faster.

Webinar Agenda:

1. The Problem - Post-processing time-dependent data can 
take a long time and consume large amounts of RAM.

2. The Solution - Reduce memory usage and take advantage 
of multi-processing – both will drastically speed up 
transient post-processing.

3. The Results - Get your results up to six times faster! 

4. Caveats - Of course there are caveats! We will explain 
each of these: hardware constraints, licensing, dataset 

5. Future Work - We plan to test this on a distributed 
HPC system.

6. Q&A  
Event record first posted on March 21, 2019, last modified on March 23, 2019

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