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Scaling Conway’s Game of Life. Why do parallelism?. Speedup – solve a problem faster . Accuracy – solve a problem better . Scaling – solve a bigger problem. Problem 1: communication overhead.
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Why do parallelism? • Speedup– solve a problem faster. • Accuracy – solve a problem better. • Scaling– solve a bigger problem.
Problem 1: communication overhead • Parallel algorithms that employ distributed memory have a certain amount of communication and a certain amount of computation. • As more processes are added, the communication overheadincreases. • At some number of processes, communication overhead will cause the algorithm to take longer in parallel than serially.
Problem 2: Amdahl’s law • Speedup is limited by the algorithm’s serial regions– the parts of the algorithm that cannot be parallelized. • An algorithm will never be faster than its parallel regions. Speedup= where P = the proportion of the program that can be made parallel 1 – P = the proportion of the program that cannot be made parallel N = the number of processors
Strong scaling • Strong scaling– increasing the number of processes but keeping the problem size constant.
The solution • Don’t solve a problem faster, instead solve a bigger problem.
Gustafson’s law • A bigger problem solved with more processors can be solved in the same amount of time it takes to solve a smaller problem with fewer processors.
Weak scaling • Weak scaling– increasing the problem size as the number of processes increases.