COMPSCI 490PF / 690PF 3 credits

Performance Engineering

Instructor: Prof. Emery Berger
Email: emery@cs.umass.edu
Office: CS 378
Meeting times: MW 4:00–5:15pm (CS 140)
TA: Kyla Levin (khlevin@umass.edu)
TA Office Hours: Tuesdays & Fridays, 1–2pm (CS 207)
Delivery mode: In-person only; no hybrid, no recordings

Prerequisites

COMPSCI 490PF meets with COMPSCI 690PF. Instructor consent is required for COMPSCI 490PF. Junior and senior CS majors with grades of at least A- in both COMPSCI 230 and 377 are the level of background in systems that is expected. Past documented experience with GitHub projects is strongly preferred.

This course is project- and experiment-intensive. Students will analyze real software systems, perform quantitative performance measurements, and report results using professional standards. Familiarity with both C/C++ and Python is expected. Undergraduate and graduate sections meet together but have distinct project expectations and grading criteria. Enrollment is capped to support in-depth mentoring and evaluation.

Materials & Tools

Readings: Research papers and tool documentation, available online (see weekly schedule).

Assessments & Grade Weights

Oral Exam Format & Expectations (if applicable)

Grading Scale

490PF: A ≥ 93; A- 90–92; B+ 87–89; B 83–86; B- 80–82; C+ 77–79; C 73–76; C- 70–72; D+ 67–69; D 63–66; F ≤ 62.

690PF: A ≥ 93; A- 90–92; B+ 87–89; B 83–86; B- 80–82; C+ 77–79; C 73–76; F ≤ 72.

Attendance & Policies

Attendance Policy

Attendance is expected; many meetings include in-class activities. For religious observance, following UMass policy, notify the instructor in advance; reasonable accommodations will be provided.

Late & Make-Up Work

Communication

The primary method of communication for this course is Slack. Use Slack for general questions, discussions, and announcements. For private matters, use email. For deeper issues, use student hours / appointment hours.

Generative AI Policy

You may use generative AI tools only when explicitly allowed and with full disclosure (tool, prompt, how you validated outputs). Undisclosed or prohibited use may violate academic integrity. You are responsible for the technical correctness of any AI-assisted work and must reproduce all results independently.

Credit-Hour Expectation

This 3-credit course expects approximately 9 hours per week of out-of-class work (readings, problem-solving, projects, oral-exam preparation), in addition to 150 minutes of weekly contact time.