High Performance Computing (Python)

What you'll be able to do

• High-Performance Computing Fundamentals
• Parallel and Distributed Processing
• GPU Acceleration and Optimization
• Scalability and Load Balancing
• HPC Tools and Frameworks
• Real-World Applications in AI and Data Science

1. 01ByteCode Programming7 lessons · 29 min

   1. Objectives and Setup9:57
   2. Download Resources1:00
   3. A Compelling Use case2:01
   4. Disassemble ByteCode with dis5:51
   5. Loop inside vs Loop outside4:41
   6. Exercises2:10
   7. Solutions3:08
2. 02Time Complexity5 lessons · 29 min

   1. Understanding Time Complexity11:23
   2. Common Time Complexities Big O Notation5:55
   3. Analyzing time complexities3:07
   4. Optimizing your code5:07
   5. Exercises3:29
3. 03Memory Hierarchy7 lessons · 27 min

   1. Understanding Memory Hierarchy5:45
   2. Demo Memory Performance in Python3:17
   3. Why exactly are numpy operations faster2:48
   4. Buffered IO3:44
   5. Exercise - Test Your Understanding0:44
   6. Row wise vs Column wise operations6:48
   7. Mini Exercises3:41
4. 04Profiling4 lessons · 17 min

   1. Profiling5:28
   2. Reading Profiler Outputs5:22
   3. Profiling code using PyInstrument3:20
   4. Exercises3:14
5. 05Threading13 lessons · 1 h 51 min

   1. Introduction to Threads12:35
   2. Problem and Solution Demo4:45
   3. What is Gill and it's purpose10:02
   4. Gill Part 2: Lock() to prevent Race Condition12:37
   5. Exercise 24:12
   6. Daemon Thread7:55
   7. ThreadPool for running concurrent tasks5:03
   8. Synchronisation: Locks, RLocks, Semaphores19:31
   9. Mini Project 1: Parking Lot Stimulation12:42
   10. Events - Signalling between Threads4:52
   11. Conditions in Thread communications9:54
   12. Queues2:30
   13. Mini Project: Fast Food Restaurant Order Management4:31
6. 06Multiprocessing10 lessons · 44 min

   1. Multiprocessing5:24
   2. Exercise 1: Image Parallel Processing3:21
   3. Queues4:02
   4. Exercise 2: Coffee Shop Ordering Queue4:21
   5. Pipes Connection4:22
   6. Exercise 3: Warehouse Packaging Simulation3:50
   7. Shared values and arrays2:44
   8. Sharing data example shopping4:28
   9. Final Mini Project9:39
   10. Review Exercises1:51
7. 07Async Programming7 lessons · 31 min

   1. Introduction to Async5:28
   2. Asynchronous webscraping5:29
   3. Mini Exercise2:33
   4. Exercise 3: Async Restaurant Operations7:14
   5. Coroutines and Eventloop6:17
   6. Task Cancellation1:57
   7. Final Exercises2:21
8. 08Cython10 lessons · 1 h 5 min

   1. Introduction to Cython14:19
   2. Practice Exercise 13:50
   3. Structs, Enums and Exercise6:09
   4. Numpy Arrays in Cython9:58
   5. Parallel Computing with Cython6:13
   6. Profiling and Debugging3:40
   7. Wrapping C Libraries in Python3:04
   8. Practice Problem Cython0:57
   9. Mini Project K Means Clustering9:45
   10. Solution6:40
9. 09CUDA Programming7 lessons · 55 min

   1. Introduction to CUDA Programming10:36
   2. Components of CUDA Programming6:58
   3. Thread Hierarchy: Threads, Blocks and Grid8:39
   4. Running CUDA code8:25
   5. 2D and 3D Arrangement6:47
   6. Sending data between host and device7:06
   7. Dynamic Allocations6:50

What you need

• Basics of Python
• Foundational knowledge of Data Science
• High school maths

Who this course is for

• Data Science Aspirants
• Data Science Professionals
• Software/Data engineers interested in quantitative analysis
• Professionals working with large datasets
• Data analysts, economists, researchers

Your instructor

Prabhakaran S

Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this course!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I've deployed 20+ global products. I'm also the Founder and Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I've put up the series of courses and projects with detailed explanations, just like on-the-job experience. Hope you love it!

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