410250: High Performance Computing

This repository compiles essential resources for the SPPU Computer Engineering Parallel Computing course (2019 pattern). It features PYQs with detailed solutions, code implementations, assignment handouts, write-ups, and notes on parallel paradigms, algorithm design, data communication, CUDA architecture, performance analysis, and HPC applications. Perfect for mastering course outcomes, exam preparation, projects, and hands-on learning.


Index

Notes

Codes

Practical

  1. Practical-1
  2. Practical-2
  3. Practical-3
  4. Practical-4
  5. Mini Project

Assignments

  1. Assignment-1
  1. Assignment-2

Question Papers

IN-SEM PYQ Answers


Miscellaneous

-> Disclaimer: Please read the DISCLAIMER file for important information regarding the contents of this repository.

-> Note: Content such as codes, softcopies, write-ups and question papers is provided by us, i.e. our contributors. You are free to use this content however you wish, without any restrictions. Some of the notes and handouts have been provided by our professors, thus to use them for anything other than educational purposes, please contact them.

-> Maintained by:

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-> Motto:

Making information freely accessible to everyone.

-> Keywords:

SPPU, Savitribai Phule Pune University, Pune University, Computer Engineering, COMP, Fourth Year, Final Year, BE, Semester 8, SEM-8, Notes, Codes, Practical work, Handouts, Assignments, PYQs, parallel computing, CUDA, parallel programming, parallel algorithms, HPC, performance analysis, data communication, PYQ solutions, write-ups,


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Description
This repository compiles essential resources for the SPPU Computer Engineering Parallel Computing course (2019 pattern). It features PYQs with detailed solutions, code implementations, assignment handouts, write-ups, and notes on parallel paradigms, algorithm design, data communication, CUDA architecture, performance analysis, and HPC applications. Perfect for mastering course outcomes, exam preparation, projects, and hands-on learning.
Readme 10 MiB
Languages
C++ 50%
Jupyter Notebook 34.8%
Cuda 15.2%