introduction what class is this? cs 484 – parallel processing who am i? mark clement 2214 tmcb ...
TRANSCRIPT
Introduction
What class is this? CS 484 – Parallel Processing
Who am I? Mark Clement 2214 TMCB [email protected] 422-7608
When are office hours? MW 10-12 and appointment
Course and Text
Homepage (Everything is here)BYU Learning Suite
Text:Online tutorials & papers
Course Objectives
Students will understand and demonstrate the ability to develop Shared memory parallel programs (OpenMP & Pthreads), Distributed memory parallel programs (MPI), and Data parallel programs (CUDA)
Students will understand and be able to implement several basic parallel algorithms and load balancing techniques.
Lectures
Follow schedule on the homepage We will move quickly.
READ BEFORE CLASS!!!!!There will be in-class quizzes - no makeup
I will post lecture notes on the web.
What is expected of you? READ!!! Assignments
C/C++ on the Supercomputer & CS Open Labs All assignments include a report. The report IS
the assignment. The program is what you did to accomplish the assignment. - I will grade your writing.
Submit through Learningsuite Exams
In the testing center 8 1/2 x 11 sheet of notes allowed
What is expected of you?
Get an account on the university supercomputers Go to fsl.byu.edu Register Do it today!!!
Read through the batch jobs tutorial for marylou Schedule a simple hello world using a PBS script.
copy ~mjc22/hello/hello.c and ~mjc22/hello/hello.pbs edit hello.pbs mpicc hello.c sbatch hello.pbs
Grading
Grade Distribution Homework & labs 60 % Midterm 15 % Final 15 % Project 10%
Grade Scale 94 % - Above A 90 % - 93.9 % A- 80 % - 89.9 % B-, B, B+ 65 % - 79.9 % C-, C, C+
I expect everyone to get a good grade!
Policies
Late Work I don’t like late work. However….. 10% off per school day – limited to 70% off
Programming Assignments To get better than a C-, you must complete ALL labs If you don’t complete all the labs, your grade ceiling is
a C-
Other Policies
Honor Code: I expect you to follow the honor code including the
dress and grooming standards. You can work together in groups on the homework
and laboratories from a conceptual perspective, but the answers that you give and the programs that you write should be your own, not copies of other students work.
Your reports should focus on your own ideas and things you have learned from your experimentation.
Other Policies
Cheating Cheating in any form will NOT be tolerated. This
includes copying any part of a homework assignment or programming lab.
Any assignment turned in that is not your work will be given a negative full value score. Any cases of multiple offense or cheating on a test will result in failure of the class.
Systems Abuse Policy Abuse in any form will result in immediate suspension
of your accounts(s).
Other Policies
Preventing Sexual Harassment Title IX of the Education Amendments of 1972 prohibits sex
discrimination against any participant in an educational program or activity receiving federal funds. Title IX covers discrimination in programs, admissions, activities, and student-to-student sexual harassment.
BYU's policy against sexual harassment extends not only to employees but to students as well.
If you encounter unlawful sexual harassment or gender based discrimination, please talk to your professor; contact the Equal Employment Office at 377-5895 or 367-5629 (24 hours); or contact the Honor Code Office at 378-2847.
Other Policies
Students With Disabilities Brigham Young University is committed to providing a
working and learning atmosphere that reasonably accommodates qualified persons with disabilites. If you have any disability, which may impair your ability to complete this course successfully, please contact the Services for Students with Disabilities Office (378-2767). Reasonable academic accommodations are reviewed for all students who have qualified documented disabilites.
Other Policies
Children in the Classroom The study of Computer Science requires a degree of
concentration and focus that is exceptional. Having small children in class is often a distraction that degrades the educational experience for the whole class. Please make other arrangements for child care rather than bringing children to class with you. If there are extenuating circumstances, please talk with your instructor in advance.
What will we do in this class? Focus on shared memory and message passing
programming PThreads OpenMP MPI Data parallel programming with CUDA
Write code for the supercomputers
Study parallel algorithms and parallelization
What is Parallelism? Multiple tasks working at the same time on
the same problem.
Parallel Computing
What is a parallel computer? A set of processors that are able to work
cooperatively to solve a computational problem Examples
Parallel supercomputers Clusters of workstations Symmetric multiprocessors Multiple core processors
Won't serial computers be fast enough? Moore's Law
Double in speed every 18 months
Predictions of need British government in 1940s predicted they would only
need about 2-3 computers Market for Cray was predicted to be about 10
Problem Doesn't take into account new applications.
Applications Drive Supercomputing Traditional
Weather simulation and prediction Climate modeling Chemical and physical computing
New apps. Collaborative environments DNA Virtual reality Parallel databases Games Photoshop
Application Needs
Graphics 109 volume elements 200 operations per element Real-time display
Weather & Climate 10 year simulation involves 1016 operations Accuracy can be improved by higher resolution grids
which involves more operations.
Cost-Performance Trend
1960s
1970s1980s
1990s
Cost
Performance
Serial computers
What does this suggest?
More performance is easy to a point. Significant performance increases of current
serial computers beyond the saturation point is extremely expensive.
Connecting large numbers of microprocessors into a parallel computer overcomes the saturation point. Cost stays low and performance increases.
Computer Design
Single processor performance has been increased lately by increasing the level of internal parallelism. Multiple functional units Pipelining
Higher performance gains by incorporating multiple "computers on a chip.”
Gigahertz race is over (Intel won) Multiple cores is where performance will come from
Computer Performance
1e2
1e7
1e12
Eniac
IBM 704
IBM 7090
CDC 7600
Cray 1Cray X-MP
Cray C90
IBM SP-2
1950 20001975
TFLOPS
Communication Performance
Early 1990s Ethernet 10 Mbps Mid 1990s FDDI 100 Mbps Mid 1990s ATM 100s Mbps Late 1990s Fast Ethernet 100 Mbps Late 1990s Gig Ethernet 100s Mps Gbps is now commonplace
Performance Summary
Applications are demanding more speed. Performance trends
Processors are increasing in speed. Communication performance is increasing.
Future Performance trends suggest a future where
parallelism pervades all computing. Concurrency is key to performance increases.
Parallel Processing Architectures Architectures
Single computer with lots of processors Multiple interconnected computers
Architecture governs programming Shared memory and locks Message passing
Shared Memory Computers
Uniform Memory Access All access the same
memory can lead to memory
bottleneck
Non-uniform Memory Access different speed access more scalable
Message Passing Computers
Distributed Shared Memory
Interconnection Network
Processors
Memory Modules
Message Passing Architectures
Requires some form of interconnection
The network is the bottleneckLatency and bandwidthDiameterBisection bandwidth
Message Passing Architectures
Line/Ring
Mesh/Torus
Message Passing Architectures
Tree/Fat Tree
Message Passing Architectures
Hypercube
Message Passing Architectures
Switched
Nice, but also has limitations
Parallel Programming Properties
Concurrency Performance should increase by employing
multiple processors. Scalability
Performance should continue to increase as we add more processors.
Locality of Reference Performance will be greater if we only access local
memory. Architecture affects each of the above!
Parallel Programming Models
Threads
Parallel Programming Models
Message Passing
Parallel Programming Models
Data Parallel
So What?
In this class you will learn to program using each of the parallel programming models.
We will talk about advantages/disadvantages of each model
We will also learn about common parallel algorithms and techniques