Thursday, August 25, 2011

MBA team from Maharishi University of Management, USA, places first in a national business simulation

A team from the accounting MBA class at Maharishi University of Management recently placed first in a nation-wide business simulation competition.

Dr. Andrew Bargerstock, Associate Professor of Business Administration, reported on the success of the MBA team.

The simulation compared integrated decision-making skills. The MUM team consisted of 4 international students—from Nepal, Pakistan, India and China.

This year 137 MBA teams entered from top universities across the USA, such as Harvard, Cornell, UC-Berkeley, Northwestern, Vanderbilt, North Carolina, Pittsburgh, Boston College, Iowa, and Iowa State. Even though the MUM team only had 3 weeks compared with a whole semester for other teams, it was able to come out on top.

Maharishi University of Management welcomes MBA students from all countries to join this unique programm of Consciousness-Based Education, which is structured so that its sought-after students can graduate with zero debt:

Saturday, August 20, 2011

MUM Computer Science Professor Bruce Lester Awarded Best Paper of 2011 Parallel & Distributed Computing Conference

Dr. Bruce Lester, (MIT, Ph.D.) MUM Professor of Computer Science, has received the Best Paper Award of The 2011 International Conference of Parallel and Distributed Computing held in London, U.K., July 2011. This conference was part of the annual World Congress on Engineering sponsored by the International Association of Engineers.

Dr. Lester's paper "Improving the Performance of Collection-Oriented Operations through Parallel Fusion" presents a technique for utilizing multiple processors to make computer programs run faster. All new computers today have processors with multiple "cores". Each core is essentially a separate processor capable of executing its own instruction stream in parallel with other cores. The number of cores per processor is expected to double every three years. This offers the potential for greatly improved computer performance. However, this potential offered the computer hardware is not yet fully realized by the software. One very promising technique for solving this problem is called data parallel programming in which the same operation in applied in parallel to different elements of a data structure (collection). In the ordinary implementation of data parallel operations, all the cores must synchronize with each other after each operation. In his paper, Dr. Lester presents a technique for removing this time-consuming synchronization, thus speeding up the execution by as much as 80%.

The full text of Dr. Lester's paper my be viewed using the following URL: