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	April 12, 2011 12:00 AM PDT

Take a look at some of the fantastic work being done on the Intel® Manycore Testing Lab.

Academic Tech Briefs are a benefit available to any Intel Manycore Testing Lab user who has an interest in promoting their findings to the community at large. Taking the extra effort to publish a Tech Brief with the community can help you earn Software Developer Black Belt points and gives you a nice piece of collateral to share with your colleagues or administration. Additionally, it can provide your students with a proof case of their achievements.

	Computation of Automorphism Groups of q-ary Codes Yekaterina Zhmud, Novosibirsk State University, has basic computations of symmetry groups that are estimated to take around 21 days. Without this data, testing the whole algorithm is impossible. What will it take for Yakaterina to change and improve the algorithm (using OpenMP) within hours or days, rather than weeks?
	Fast Spectral Estimation of Genetic Homology Anton Pankratov and Ruslan Tetuev from Moscow State University and Russian Academy of Sciences wonder what it would be like to view the homology of all known genetic sequences as one single, albeit humongous image. Once generated, how would you browse such an image quickly?
	Matrix Multiplication, Performance and Scalability in OpenMP Nicolas Wolovick, National University of Cordoba introduced matrix multiplication to his students this year and challenged them to create the fastest serial code. How will optimizing this code to fully utilize 32 cores change the exercise?
	Benchmark of Parallel Bipartite Graph Matching and Parallel Smith Waterman Rosni Abdullah and Ibrahim Umar know that the sequence alignment algorithm plays an important role in finding the homologous groups of biological sequences. While this operation is currently one of the most heavily used operations in computational biology and most accurate sequence alignment algorithms available, it also consumes a great amount of time during its operation. Can the Intel Manycore Testing Lab exponentially reduce execution time?
	Exploring AVS Video Decoder Parallelism Konstantinos Krommydas and his advisor Wu-Chun Feng are exploring the parallel nature of the AVS video decoder, their code’s scalability, and video decoding in general. What is the effect of scaling this project from 4 cores to 32?

Find more information on the Intel Manycore Testing Lab.
Contact us at academic.community@intel.com if you'd like us to help you produce a Tech Brief around your work.

For more complete information about compiler optimizations, see our Optimization Notice.