SCS Faculty Candidate

Livestream ET - from Newell-Simon Hall 4305 (Teaching Demo)

ELBA GARZA , Ph.D. Candidate
Department of Computer Science and Computer Engineering
Texas A&M University

Principles of Caching within the Context of Computer Hardware and Organization

Teaching Demo:  Principles of Caching within the Context of Computer Hardware and Organization

In this mock lecture, I present the principles of caching within the context of a computer hardware and organization course. This mock lecture presents the first 45 minutes of a typical 75-minute lecture for a semester-long course in computer organization, or the equivalent of 15-213. This lecture assumes students’ previous exposure to the lecture’s topics via a pre-course Computer Organization and Design (6th edition, MIPS) ZyBook interactive activity; however, it is not necessary to complete or purchase for the mock lecture. Concepts are presented using in-classroom activities, and abstraction via real-life metaphors for fundamental understanding.

  • Teaching Demo: 19  January 2022 - 10:00 am  ET
  • Faculty Candidate Research Talk: 20 January 2021 - 10:00 am ET


Research Talk:  Developing Robust Microarchitectural Predictive Structures for the Front End

Modern processors rely on predictive structures and policies for making important control and data flow execution decisions. To maintain forward progress while awaiting resolving instructions, early computer architects looked to speculation–effectively acting on predicted directions of control flow. Without quick yet accurate prediction, processor architectures may still be relegated to the age of stall-heavy and heavily sequential execution. In this talk, I outline my research contributions toward making microarchitectural predictive structures and policies more accurate and resilient to changing computing demands. Structures and policies outlined include those for the branch target buffer, instruction cache, and translation lookaside buffer. 

Elba Garza is a final-year Computer Science PhD student at Texas A&M University working under Daniel A. Jiménez. Her work focuses on making hardware predictive structures & policies (e.g., branch prediction, prefetching, cache replacement) more resilient to evolving computing demands. She holds a BSc in Computer Science from Columbia University, and an MSc in the same from Princeton University. Her work has been featured in top-tier computer architecture conferences including ISCA and MICRO. Her research has earned accolades, including the 2020 IEEE CS Lance Stafford Larson Student Award. She was named a 2020 Rising Star in EECS and also recently named a 2021 Google Scholar. After returning to graduate school for her PhD and seeing fellow graduate students struggle with mental health issues arising from the general toll of academic life, she helped co-found the Computer Architecture Student Association, or CASA. CASA is an independent student-run organization with the express purpose of developing and fostering a positive and inviting student community within computer architecture.

Faculty Host: Brian Railing

Computer Science Department

→  Presentation in Newell-Simon 4305.
→  Due to modified campus posture, the talk will be livestreamed. See announcement.

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