Akademik Dersler - Tanıtım


Code - Course Title	EEM438 - Introduction to AI Processor Design
Course Type	Area Elective Courses
Language of Instruction	İngilizce
Laboratory + Practice	3+0
ECTS	5.0
Course Instructor(s)	DOKTOR ÖĞRETİM ÜYESİ MEHMET FİDAN
Mode of Delivery	Face-to-face
Prerequisites	There is no prerequisites.
Courses Recomended	EEM 232 -Digital Systems IEEM 336- Microprocessors I EEM 334- Digital Systems IIBİL200- Computer Programming
Required or Recommended Resources	Yunji Chen, et al.,”Intelligent Computing Systems”，China Machine Press，April, 2020Nan Zheng et al.，“Learning in Energy-Efficient Neuromorphic Computing: Algorithm and Architecture Co-Design”，Wiley-IEEE Press，Dec. 2019Chenxiong Zhang，”AI chips: Cutting-Edge Technologies and Innovative Future”， Posts and telicommunications Press，April, 2021Vivienne Sze et al.，” Efficient Processing of Deep Neural Networks”，Morgan &Claypool; publishers，April, 2020
Recommended Reading List	Chenxiong Zhang，”AI chips: Cutting-Edge Technologies and Innovative Future”， Posts and telicommunications Press，April, 2021Vivienne Sze et al.，” Efficient Processing of Deep Neural Networks”，Morgan &Claypool; publishers，April, 2020
Assessment methods and criteria	Two midterm exams, Implementation, Final Exam
Work Placement	Yok
Sustainability Development Goals

Weeks	Topics
Week - 1	Introduction to AI processors
Week - 2	Basics of Neural Network
Week - 3	Basic of Deep Learning
Week - 4	Operational Principle of Deep Learning Hardware Accelerator
Week - 5	Hardware Architecture of DNN processors
Week - 6	Principle of Spike Neural Network
Week - 7	Hardware Architecture of SNN processors
Week - 8	Mixed-Signal Computing Paradigms
Week - 9	Cutting-edge technologies of AI SoCs
Week - 10	Chip Implementation
Week - 11	Efficient Processing of Deep Neural Networks
Week - 12	Learning in Energy-Efficient Neuromorphic Computing
Week - 13	Smart Algorithm and Architecture Co-Design
Week - 14	Hardware Implementation and Verification of Design Smart Algorithm via FPGA

Assessment Method and Passing Requirements
	Quamtity	Percentage (%)
1.Midterm Exam	1	20
2.Midterm Exam	1	20
Homework	1	20
Final Exam	1	40
Toplam (%)		100