Parallelism

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Talks about splitting python across multiple cores and servers. Multithreading, Multiprocessing, and distributed Systems.

10 Best Parallelism Videos
Votes
 Date
292 👍
5 👎
96.1%
292 👍
5 👎
2018-05-10
82 👍
1 👎
93.5%
82 👍
1 👎
2018-07-12
42 👍
91.6%
42 👍
2018-05-11
113 👍
4 👎
91.5%
113 👍
4 👎
2018-05-13
41 👍
91.4%
41 👍
2018-07-15
141 👍
7 👎
90.6%
141 👍
7 👎
2018-05-13
32 👍
89.3%
32 👍
2018-04-17
30 👍
88.6%
30 👍
2018-05-11
67 👍
3 👎
88.1%
67 👍
3 👎
2018-05-10
50 👍
2 👎
Democratizing Distributed Computing with Dask and JupyterHub
We used JupyterHub, XArray, Dask, and Kubernetes to build a cloud-based system to enable scientists to analyze and manage large datasets.
87.0%
50 👍
2 👎
2018-05-13
 


Sub Categories

1. Distributed Systems Software that runs across the network. Message Brokers, Workflows, that type of thing.
2. Scaling Applications Scaling PostgreSQL, data pipelines, Spark and the like.
3. Reliability Enginnering How to make these systems reliable.
4. Addressing Multithreading & Multiprocessing in Transparent & Pythonic Methods
5. An Introduction to Julia (Beginner Level) Julia allows concurrent, parallel and distributed computing, and direct calling of C and Fortran libraries without glue code. It may be of interest to Python developers.