Spring '26
ECE 788 - Hardware Acceleration for Machine Learning (3 credits) New Jersey Institute of Technology
Course Objectives: This course provides an introduction to machine learning hardware systems, focusing on the interaction between modern learning algorithms and their underlying computing architectures. Students will study core machine learning models, including multilayer perceptrons (MLPs) and convolutional neural networks (CNNs), and examine how their computational characteristics influence hardware design. The course explores hardware/software co-design challenges, data mapping strategies, and implementation considerations for efficient machine learning acceleration. Topics include acceleration platforms such as GPUs, systolic arrays, and FPGAs, along with industry-standard benchmarking methodologies such as MLPerf. The course also introduces emerging computing paradigms, including analog crossbar architectures and in-memory computing, highlighting their potential to overcome energy and performance limitations of conventional architectures.
Spring '22 - '26
ECE 452 - High Performance Computer Architecture (3 credits) New Jersey Institute of Technology
Course Objectives: This course focuses on recent advances and topics of current active research in the field of computer architecture. It includes new computing paradigms such as brain-inspired non-von Neumann architectures, heterogeneous computing systems, and parallel machine learning accelerator architectures. It also covers topics related to hybrid memory systems, architectures of emerging memory technologies, rowhammer and secure and reliable memory systems, and memory consistency.
Fall '21- '25
ECE 451 - Advanced Computer Architecture (3 credits) New Jersey Institute of Technology
Course Objectives: This course focuses on advanced concepts in computer systems design, and the interaction between hardware and software components at various levels (i.e., hardware/software codesign). It introduces common performance measures and tradeoffs used by hardware and software designers to facilitate comparative analysis. The main topics are power wall and memory wall technology challenges, pipelining, multicore architecture, advanced memory technologies with an emphasis on non-volatile memories, introduction to parallel computing, domain-specific architectures (i.e., FPGA, ASIC), and an introduction to analog and digital in-memory computing.
Fall '19
EEL 4362: Post-CMOS Devices and Circuits (3 credits) University of Central Florida
Course Objectives: To introduce state-of-the-art complementary metal-oxide-semiconductor (CMOS) technology and post-CMOS technologies including spintronic, Quantum-dot Cellular Automata, memristor, tunneling FET devices, and their applications in emerging memory, logic, and neuromorphic computing.