1. Thinking in Parallel - Introduction New Mexico Supercomputing Challenge in partnership with Intel Corp. and NM EPSCoR

2. Copyrights and Acknowledgments Intel and the Intel logo are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States or other countries. New Mexico EPSCoR Program is funded in part by the National Science Foundation award #0814449 and the State of New Mexico. Any opinions, findings, conclusions, or recommendations expressed in the material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. For questions about the Supercomputing Challenge, a 501(c)3 organization, contact us at: consult @ challenge.nm.org

3. Agenda Define parallel computing. Explain how to identify opportunities for parallelism. Introduce three main methodologies.

4. What Is Parallel Computing? Attempt to speed solution of a task by: Dividing task into sub-tasks Executing sub-tasks simultaneously on multiple processors Parallelization requires both: Understanding of where parallelism can be effective Knowledge of how to design and implement good solutions

5. Identifying parallelism opportunities Study problem – including existing code (if any). Look for opportunities to perform multiple tasks at the same time (parallelism), in order to: Try to keep all processors busy doing useful work. Solve the problem faster.

6. Three main methodologies Domain decomposition – Used when the same operation is performed on a large number of similar data items. Task decomposition – Used when some different operations can be performed at the same time. Pipelining – Used when there are sequential operations on a large amount of data.