Heterogeneous Computing 

for Signal and Data Processing 

Heterogeneous Computing for Signal and Data Processing

** Parallel computing  with GPUs and other devices**

Course number: EECS E4750     

(Original name: Signal Processing and Communications on Mobile Multicore Processors)

Prof. Zoran Kostic, Electrical Engineering Department, Data Sciences Institute,  Columbia University in the City of New York

Target Audience: 

 Students interested in acquiring software and systems design skills in parallel computing for graphics processing units (GPUs) and heterogeneous computing infrastructure, relevant to applications in data processing, deep learning, signal and communications industries.

Bulletin Description:

Dates:

Content

Applications of Parallel Computing

Graphics Processing Unit (GPU) architecture and programming.

Heterogeneous Parallel Computing (HPC)

Parallel SW development in OpenCL and CUDA, Apple Metal, Vulkan, other standards.

Syllabus Details

Theory, CUDA, OpenCL:

Project Suggestions for implementation in CUDA or OpenCL


Books, Tools and Resources

2014 Fall Projects

2015 Fall Projects

2016 Fall Projects

2017 Fall Projects

2018 Fall Projects

2019 Fall Projects

2020 Fall Projects

2021 Fall Projects