Office hours: Tuesday 1-2pm at POB 4.126
TA: Roshan Dathathri (firstname.lastname@example.org)
TA office hours: Friday 11am-noon at POB 4.116
Canvas: https://utexas.instructure.com/courses/1128191 for assignment submissions and grades.
Piazza: https://piazza.com/utexas/spring2015/cse392cs378/ for announcements and discussions.
To obtain the high level of end-to-end performance needed in
problem domains like graphics, computer games, and scientific
computing, it is necessary for programs to exploit many of the
features of modern computer architectures. In this course,
we will study the performance-critical features of modern
computer architectures, and discuss how applications can take
advantage of them to obtain high performance. This is not
a course on software tricks; rather, the emphasis is on
abstractions of computer architecture, understanding
performance, and obtaining performance when you need it.
Topics include the following:
- Analysis of applications that need high end-to-end
- Understanding performance: performance models, Amdahl's law
- Measurement and design of computer experiments
- Microbenchmarks for abstracting performance-critical aspects
of computer systems
- Memory hierarchy: caches, virtual memory, exploiting spatial
and temporal locality
- Vectors and vectorization
- GPUs and GPU programming
- Multi-core processors and shared-memory programming, OpenMP
- Distributed-memory machines and message-passing programming,
- Optimistic parallelization
- Self-optimizing software
There will be 4 or 5 substantial programming assignments
and a final project.
programming maturity, knowledge of C/C++, basic course on modern
For basic material on computer architecture, read "Computer
Architecture: A Quantitative Approach"
by Hennessy & Patterson, Morgan Kaufmann Publishers.
- Assignments (4-5): 55%
- Mid-term exams (one or two): 20%
- Final project: 25%