Basic Information
Computer Architectures in a Multi-processor Environment With Emphasis On Machine Learning (ml) Accelerators and Qualitative And Quantitative Methods in Power and Energy Constrained Environment. Identify Future Technology Trends and Techniques in System S Structures. Asymmetric Computing Systems, Advanced Machine Learning Accelerators Architectures With Emphasis On Deep Neural Networks. Comprehend The Basic Requirements of Learning Systems and Leverage Them For Energy-efficient Architectural Design. The Goal of The Course Is to Provide The Student With Architectural Knowledge, Tools and a Passion Approach to Enable Implementations Of Future Computational Systems.
Faculty: Electrical and Computer Engineering
|Undergraduate Studies
|Graduate Studies
Pre-required courses
Course with no extra credit
48853
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