You’ve checked for understanding—now you can use this framework to understand what students’ confusion is telling you, and how you can adjust course.

Abstract: Compute-In-Memory (CiM) is emerging as a promising paradigm to design energy-efficient hardware accelerators for AI, addressing the processor-memory data transfer bottleneck. The popularity ...

This project implements an 8x8 systolic array for high-performance matrix multiplication, leveraging a parallel processing architecture optimized for efficiency and scalability. The workflow spans RTL ...

Abstract: Sparse matrix multiplication (SpMM) is a critical kernel used in a wide range of applications, but irregular memory access patterns and memory bandwidth bottleneck as well as load imbalance ...

This report explores the limitations of data upload size using Google Apps Script and introduces a script to overcome these limitations. In the current stage, Gemini API can generate content using the ...