Arizona State University & Intel Corporation Collaboration in Parallel Computing

Arizona State University, Ira A. Fulton Schools of Engineering, is working with the Intel Academic Community to integrate Parallel Computing into the Computer Science and Engineering, Mathematics and Statistical Sciences Programs, the High Performance Computing Initiative, at the Undergraduate and Master's degree levels.

Intel's Academic Program team members, Rowena Turner, Amit Jindal and Lauren Dankiewicz, together with ASU Professors Yann-Hang Lee, Yinong Chen, Partha Dasgupta, Eric Kostelich, Violet Syrotiuk, Gil Speyer, and Aviral Shrivastava have worked together to target nine courses at both the undergraduate and master-levels where parallelism will be taught.



Above are the Intel Academic Program team members with the professors from Ira A. Fulton Schools of Engineering.
First Row: Lauren Dankiewicz, Dean Johnson, Amy Barton, Rowena Turner, Amit Jindal Second Row: Dr. Shrinavasta, Dr. Chen, Dr. Speyer, Beth Redfield, Dr. Mahalov, Dr. Lee

 



Intel Academic Program Manager Amy Barton with Dean Johnson


As more multicore processors are created, the expected use in future computing has generated a demand in industry for technologists that can create advanced software that leverages parallelism to take advantage of the processing power available. This increased applicability of parallelism necessitates that undergraduate and master's degree curricula in computer science, computer engineering and electrical engineering be updated accordingly.

The following courses (ranging from undergraduate to master's degree levels) at ASU Ira A. Fulton Schools of Engineering will give students better understanding, experience and sophistication in writing and debugging multi-threaded code:

CSE 101: Introduction to Computer Science and Engineering

CSE 420: Computer Architecture I

CSE 430: Operating Systems

CSE 445/598: Distributed Software Development

MAT 420: Scientific Computing

CSE 494/598 and ME 494/598: Introduction to Parallel Computing

CSE 531: Distributed and Multiprocessor Operating Systems

CSE 591: Low-Power Computing



Read about TickerTape-- a free, downloadable "academic ready" game demo that ASU is integrating into their classroom to make parallelism engaging and interactive. TickerTape is a demo of a particle system that can help professors instruct data parallel programming to college sophomores and juniors.





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