[Faculty] Fwd: [CSRC.COLLOQUIUM] "Building Repeatable and Automatable Scientific Computing Platforms with Modern Tools: Machine Learning as a Use Case"

[Jose Castillo]

[image: SDSU_CSRC Logo.jpg]




DATE:  *Friday, May 8, 2020*



TITLE:

*Building Repeatable and Automatable Scientific Computing Platforms with
Modern Tools: Machine Learning as a Use Case*


TIME:  *3:00-4:00PM*




LOCATION:
Join Zoom Meeting -  https://SDSU.zoom.us/j/99859040967
<https://sdsu.zoom.us/j/99859040967>

Note: Recent videos from previous colloquium talks for

Spring 2020 can be seen on the CSRC website in the colloquium archive
section or on the CSRC YouTube page here
<https://www.youtube.com/channel/UCN0ZEztlmyDqG2pm-Rle_Eg/feed>.




SPEAKER/BIO:


*Dr. **John Aven, Director of Engineering, Hashmap, Inc.,*





ABSTRACT:

Repeatability (Reproducibility, Sharability, Auditabilty, and Immutability)
in research, in academia and in industry, is not optional - it is a
fundamental requirement for any modern solution, analysis or result set.
Furthermore, running analysis on your personal devices is passe -
monitoring such processes and the temporary loss of device functionality
are not attractive. Fortunately, in scientific computing, as can be
evidenced by the data science phenomenon, matures and adopts best practices
from modern software engineering, the tools we use and how we operate will
be and are changing. Also, as the software engineering field evolves,
additional tools become available - and at our disposal. By combining these
approaches and the demand for repeatability in our scientific work it is
possible to design and implement frameworks that enable us to completely
track all stages and versions of our investigations with cloud-native
cross-platform (platform agnostic) deployability. We will present design
concepts around such needs and provide an exemplar implementation.



Host: Jose Castillo

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