Example 195% of a program’s execution time occurs inside a loop that can be executed in parallel. What is the maximum speedup we should expect from a parallel version of the program executing on 8 CPUs?
Parallel Programming with MPI and OpenMP Michael J. Quinn
Chapter 7 Performance Analysis
Learning Objectives
Predict performance of parallel programs
Understand barriers to higher performance
Outline
General speedup formula
Amdahl’s Law
Gustafson-Barsis’ Law
Karp-Flatt metric
Isoefficiency metric
95% of a program’s execution time occurs inside a loop that can be executed in parallel. What is the maximum speedup we should expect from a parallel version of the program executing on 8 CPUs?
Example 2
20% of a program’s execution time is spent within inherently sequential code. What is the limit to the speedup achievable by a parallel version of the program?
Pop Quiz
An oceanographer gives you a serial program and asks you how much faster it might run on 8 processors. You can only find one function amenable to a parallel solution. Benchmarking on a single processor reveals 80% of the execution time is spent inside this function. What is the best speedup a parallel version is likely to achieve on 8 processors?
Pop Quiz
A computer animation program generates a feature movie frame-by-frame. Each frame can be generated independently and is output to its own file. If it takes 99 seconds to render a frame and 1 second to output it, how much speedup can be achieved by rendering the movie on 100 processors?
Limitations of Amdahl’s Law
Ignores (n,p)
Overestimates speedup achievable
Amdahl Effect
Typically (n,p) has lower complexity than (n)/p
As n increases, (n)/p dominates (n,p)
As n increases, speedup increases
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