MPI and C-Language Seminars 2010
Seminar Plan
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Week 1 – Introduction, Data Types, Control Flow, Pointers
Week 2 – Arrays, Structures, Enums, I/O, Memory
Week 3 – Compiler Options and Debugging
Week 4 – MPI in C and Using the HPSG Cluster
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Week 5 – “How to Build a Performance Model”
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Week 6-9 – Coursework Troubleshooting
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(Seminar tutors available in their office)
Performance Models
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Aim to predict the runtime of an application.
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Allow you to predict beyond grid size and unknown hardware.
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Gauge the scalability of the algorithm / code.
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Help analyse the parallel efficiency of code.
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See where bottle necks are. Both hardware and software.
Factors of a Model
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Computation – Active Processing:
 The time spent doing actual work.
 More processors => less work per processor.
 Overall computation time should fall with increase in processors.
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Communication – Message Passing:
 Communication between processors.
 Overall I/O time will increase with processor count.
 More network contention means slower communication.
Getting the Balance (1 / 2)
Communication Vs Computation
1200
1000
Time (S)
800
600
Comm Time
Comp Time
Total Time
400
200
0
1
5
9
13
17
21
25
29
33
37
41
Number Of Processors
45
49
53
57
61
Getting the Balance (2 / 2)
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Fixed Costs:
 The work done by all processors.
 More processors will not reduce this time.
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Variable Costs:
 Portion of work which varies with processor count.
 Generally based on problem size decomposition.
Timers
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Lots of different timers:
 CPU Time – Actual time spent of CPU.
 Wall Time – Total time since program start.
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Different timers have different overheads.
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Try and avoid timing timers.
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Recommend C timer – Need to call with 2 double pointers.
double cpuStart, wallStart;
Timers(&wallStart, &cpuStart);
Where is the Expense?

Need to establish what the expensive operations are:
 Functions which are called frequently.
 Functions which take a long time.
 Work out a percentage break down of total time.
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Is it communicational or computational expense?
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Is it a fixed cost or a variable cost?
Computational Model (1 / 2)
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How will the number of processors effect the amount of work
done by each processor.
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Will they all the same amount of work? Even decomposition.
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Are loops dependent on the problem size?
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Need to look at:
 How long operations take.
 How many times they are performed.
Computational Model (2 / 2)
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A basic model:
 Time how long each different operation takes.
 Calculate how many times those operations are used.
 Add them all up.
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Inaccuracy:
 When using timers consider their overhead.
 Always more accurate to time the repetition of operations and
divide through.
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Note: Communication will show in wall time.
Communication Model (1 / 2)
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Many different types of communication:
 Send and receives.
 Collective operations.
 Barriers.
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Need to build a model of the network:
 Can use existing programs: PingPong / SKaMPI
 Or write your own.
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How much data is being sent?
Communication Model (2 / 2)
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Communication times are based on packet size.
 There is an initial cost of a send – Handshake.
 Then a variable cost – Payload.
Time (uSec)
Send Time For Message Size
180
160
140
120
100
80
60
40
20
0
Ethernet
0
2048
4096
6144
8192
Message Size (Bytes)
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Where is the data being sent?
 Are the source and destination on the same node?
Bringing it all Together
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What you need:
 Computation benchmark application.
 Communication benchmark application.
 Spreadsheet model.
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Run benchmarks on cluster and plug data into model.
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Make predictions for different processor configurations.