How can we Teach Workload Modeling in CS Systems Classes?

In Computer Science curriculum guidelines, topics related to Performance Engineering have typically been listed as small, elective components, if at all. Even less has been said about how and when to teach workload modeling. In this paper, I discuss how Systems courses are a good place to include this topic, including suggestions on how to do so that are rooted in personal experience, existing literature and examples from course programs found online. The ideas presented in this paper were first presented as an invited talk at the TeaPACS 2024 workshop, and the paper was written post-workshop, so the feedback and discussions of the TeaPACS speakers and attendees have been incorporated into it.

Authors

Institutions

Publication Details

Journal
ACM SIGMETRICS Performance Evaluation Review
Published
2024-09-05
DOI
https://doi.org/10.1145/3695411.3695432
Citations
2
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.70
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

How can we Teach Workload Modeling in CS Systems Classes?

Cristina L. Abad
2 citations
ACM SIGMETRICS Performance Evaluation Review
Distributed and Parallel Computing Systems
0.70
article

How can we Teach Workload Modeling in CS Systems Classes?

Cristina L. Abad
article en
2 citations

Abstract

In Computer Science curriculum guidelines, topics related to Performance Engineering have typically been listed as small, elective components, if at all. Even less has been said about how and when to teach workload modeling. In this paper, I discuss how Systems courses are a good place to include this topic, including suggestions on how to do so that are rooted in personal experience, existing literature and examples from course programs found online. The ideas presented in this paper were first presented as an invited talk at the TeaPACS 2024 workshop, and the paper was written post-workshop, so the feedback and discussions of the TeaPACS speakers and attendees have been incorporated into it.

ACM SIGMETRICS Performance Evaluation ReviewVol. 52(2)
Escuela Superior Politecnica del Litoral (EC)
Openalex Percentile: Top 28%
Distributed and Parallel Computing Systems
0.70
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.