#60: Scaling Python to 1000's of cores with Ufora

1

Introduction

00:00 • 1min

2

How I Got Into Python and Programming

01:28 • 3min

3

How to Speed Up Method Invocation in Python

04:02 • 2min

4

How to Make Python Programming Faster

06:15 • 2min

5

Euphora: A Platform for Executing Python Code at Massive Scale

08:28 • 2min

6

Distributed to a Grid Computing Type Framework

10:44 • 3min

7

How Spark and Hadoop Work

13:58 • 3min

8

The Evolution of Parallelism in MapReduce

16:53 • 3min

9

The Importance of Mutability in Python

19:58 • 4min

10

The Importance of Immutable Python

23:32 • 2min

11

The Immutable Nature of Python

25:40 • 3min

12

The Advantages of Spot Instances in Amazon's Infrastructure

28:44 • 2min

13

The Advantages of a Library Translation Approach to Distributed Computing

31:11 • 3min

14

How to Run a Python Model Out of Process

34:15 • 2min

15

How to Share Memory

36:36 • 2min

16

How to Solve a Query Where Chunks Are in the Wrong Place

38:54 • 2min

17

The Problem With Caching in a Distributed Environment

40:49 • 2min

18

Ufora: A Data Science and Engineering Consulting

43:00 • 2min

19

The Cost Advantage of Open Source Software

45:29 • 2min

20

Python Notebook Integration

47:04 • 4min

21

The Importance of Getting a Good Estimate

50:39 • 4min

22

The Cost of Computing on GPUs

54:50 • 3min

23

How to Estimate the Cost of a Neural Network

57:28 • 2min

24

How to Get Started With Distributed Computing

59:19 • 3min

25

PyFora's Context Manager

01:02:06 • 2min

26

How to Get Started With Python

01:03:48 • 2min

27

How to Learn Python

01:05:29 • 2min