Lectures: | Tuesdays, 12:00-1:20 p.m., PH 125B |
Wednesdays, 10:30-11:20 a.m., SH 324 | |
Thursdays, 12:00-1:20 p.m., PH 125B | |
Instructor: | Todd C. Mowry, WeH 8123, 268-3725, tcm@cs.cmu.edu |
Office Hours: Thursdays, 3:00-4:00pm, WeH 8123 | |
TA: | Tiankai Tu, tutk@cs.cmu.edu |
Class Admin: | Jennifer Landefeld, WeH 8124, 268-4740, jennsbl@cs.cmu.edu |
Web Page: | www.cs.cmu.edu/afs/cs/academic/class/15418-s04/www/ |
Newsgroup: | cyrus.academic.cs.15-418 |
Handouts: | Electronic: /afs/cs.cmu.edu/academic/class/15418-s04/public |
Hardcopies: In bins outside WeH 8124. |
We will be using the following textbooks in class:
The goal of this course is to provide a deep understanding of the fundamental principles and engineering tradeoffs involved in designing modern parallel computers (aka ``multiprocessors''), as well as the programming techniques to effectively utilize these machines. Parallel machines are already ubiquitous from desktops to supercomputers, and the expectation is that they will become even more commonplace in the future. However, very few people exploit the potential processing power of these machines because they do not understand how to write efficient parallel programs. Because one cannot design a good parallel program without understanding how parallel machines are built and vice-versa, this course will cover both parallel hardware and software design, as well as the impact that they have on each other.
Course topics include naming shared data, synchronizing threads, and the latency and bandwidth associated with communication. Case studies on shared-memory, message-passing, data-parallel and dataflow machines will be used to illustrate these techniques and tradeoffs. Programming assignments will be performed on one or more commercial multiprocessors, and there will be a significant course project.
This is a relatively unique course since this material is rarely offered to undergraduates. Because parallel processing has become such an important and mainstream technology, the time has come to integrate this material into the undergraduate systems curriculum.
15-213 (Intro to Computer Systems) is a strict prerequisite for this course. We will build directly upon the material presented in 15-213, including memory hierarchies, memory management, basic networking, etc.
While 18-347 (Intro to Computer Architecture) would be helpful for understanding the material in this course, it is not a prerequisite.
To complete your programming assignments and course projects, you will be receiving accounts on machines at the National Center for Supercomputing Applications (NCSA) and the Pittsburgh Supercomputing Center (PSC). Details will be provided later.
Important: please note that the class will be allocated a finite (and not particularly large) amount of time on these machines, so please be careful not to waste time unnecessarily.
Grades will be based on homeworks, a project, two exams, and class participation.
Your overall grade is determined as follows:
Homework: | 25% |
Project: | 25% |
Exams: | 40% (20% each) |
Class Participation: | 10% |
Late assignments will not be accepted without prior arrangement.
Table 1 shows the tentative schedule. The idea is to cover the lecture material in roughly the first 2/3 of the semester (by meeting three rather than two days a week), so that you will have more time to devote to the class project in the last 1/3 of the semester, and so that you can take advantage of all of the course lecture material in your projects.
Class | Date | Day | Topic | Reading | Assignments |
1 | 1/13 | Tue | Why Study Parallel Architecture? | 1.1 | |
2 | 1/14 | Wed | Evolution of Parallel Architecture | 1.2 | |
3 | 1/15 | Thu | Fundamental Design Issues | 1.3-4 | |
4 | 1/20 | Tue | Parallel Programming: Overview I | 2.1-2 | L1 Out |
5 | 1/21 | Wed | Parallel Programming: Overview II | 2.3-4 | |
6 | 1/22 | Thu | Parallel Programming: Performance I | 3.1 | |
7 | 1/27 | Tue | Parallel Programming: Performance II | 3.2 | |
8 | 1/28 | Wed | Parallel Programming: Performance III | 3.3-4 | |
9 | 1/29 | Thu | Par. Prog: Case Studies & Implications | 3.5-6 | L2 Out |
10 | 2/3 | Tue | Workload-Driven Arch Evaluation I | 4.1 | L1 Due |
11 | 2/4 | Wed | Workload-Driven Arch Evaluation II | 4.2-3 | |
12 | 2/5 | Thu | Shared Memory Multiprocessors I | 5.1 | |
13 | 2/10 | Tue | Shared Memory Multiprocessors II | 5.3 | |
14 | 2/11 | Wed | Shared Memory Multiprocessors III | 5.4 | |
15 | 2/12 | Thu | Directory-Based Cache Coherence I | 8.1-5 | L3 Out |
16 | 2/17 | Tue | Directory-Based Cache Coherence II | 8.6-7, 8.9-11 | L2 Due |
17 | 2/18 | Wed | Relaxed Memory Consistency Models | 9.1 | |
18 | 2/19 | Thu | Snoop-Based Multiprocessor Design I | 6.1 | |
19 | 2/24 | Tue | Snoop-Based Multiprocessor Design II | 6.2 | |
20 | 2/25 | Wed | Earthquake Simulation Case Study | ||
2/26 | Thu | Exam I | |||
21 | 3/2 | Tue | Snoop-Based Multiprocessor Design III | 6.3-4 | L3 Due |
22 | 3/3 | Wed | Snoop-Based Multiprocessor Design IV | 6.5, 6.7 | |
23 | 3/4 | Thu | Synchronization | 5.5., 7.9, 8.8 | Project Proposal |
Spring Break | |||||
24 | 3/16 | Tue | Scalable Distributed Memory MPs I | 7.1-3 | |
25 | 3/17 | Wed | Scalable Distributed Memory MPs II | 7.4-8 | |
26 | 3/18 | Thu | Interconnection Network Design | 10.1-10 | |
27 | 3/23 | Tue | Latency Tolerance: Prefetching | 11.1, 11.6 | |
28 | 3/24 | Wed | Latency Tolerance: Multithreading | 11.7-9 | |
3/25 | Thu | Project Milestone 1 | |||
3/30 | Tue | Exam II | |||
29 | 4/8 | Thu | Terascale Computing System at PSC | Project Milestone 2 | |
4/22 | Thu | Project Poster Session | Project Report Due |
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