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lecture03_machines_jwd12.pdf
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lecture03_machines_jwd12.pdf
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01/24/2012
CS267 Lecture 3
2
Outline
•
Overview of parallel machines (~hardware) and
programming models (~software)
•
Shared memory
•
Shared address space
•
Message passing
•
Data parallel
•
Clusters of SMPs or GPUs
•
Grid
•
Note: Parallel machine may or may not be tightly
coupled to programming model
•
Historically, tight coupling
•
Today, portability is important
01/24/2012
CS267 Lecture 3
3
A
ge
ne
ric
pa
ral
lel
ar
ch
ite
ct
ur
e
Proc
Interconnection Network
•
Where is the memory physically located?
•
Is it connect directly to processors?
•
What is the connectivity of the network?
Memory
Proc
Proc
Proc
Proc Proc
Memory
Memory
Memory Memory
01/24/2012
CS267 Lecture 3
4
Parallel Programming Models
•
Programming model is made up of the languages and
libraries that create an abstract view of the machine
•
Control
•
How is parallelism created?
•
What orderings exist between operations?
•
Data
•
What data is private vs. shared?
•
How is logically shared data accessed or communicated?
•
Synchronization
•
What operations can be used to coordinate parallelism?
•
What are the atomic (indivisible) operations?
•
Cost
•
How do we account for the cost of each of the above?
01/24/2012
CS267 Lecture 3
5
Simple Example
•
Consider applying a function f to the elements
of an array A and then computing its sum:
•
Questions:
•
Where does A live? All in single memory?
Partitioned?
•
What work will be done by each processors?
•
They need to coordinate to get a single result, how?
∑
−
=
1
0
])[(
n
i
iAf
A:
fA:
f
sum
A = array of all data
fA = f(A)
s = sum(fA)
s:
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