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报告题目:
Architecture and Algorithm Design to Improve the Concurrency of Multi-core Computing
 报告人:
Bo Hong
Dr. 
Assistant Professor
ECE Department of Drexel University
报告时间:
2008-06-23 15:00
报告地点:
3-125, FIT Building
主办单位:
信研院
  简介:

2008年清华大学信息技术研究院系列学术报告10

 Dr. Bo Hong is currently an assistant professor at the ECE Department of Drexel University. He received his Ph.D. degree in Computer Engineering from the University of Southern California in 2005. Prior to that, he received his Master and Bachelor's degree from Tsinghua University, China in 2000 and 1997, respectively.

Dr. Bo Hong's research interests include High performance computing, multi-core computer architecture, parallel and multi-threaded algorithms, and distributed computing. His current research effort is concentrating on thread synchronization in multi-core processors. In this hardware-software integrated research, new algorithms are being explored to improve the efficiency of multi-core computing through new synchronization circuitry.

 

Abstract

Given the increasing emphasis on multi-core architectures, the extent to which an application can be multi-threaded to keep the multiple processor cores busy is likely to be one of the greatest constraints on the performance of next generation computing platforms. However, Amdahl’s law has pointed out that only a portion of a program’s processing can be run in parallel. Only this portion scales with machines having more and more processors. The rest of the work load is sequential and needs to be protected from shared accesses, and locking is the mostly used method. With the current industry trend where almost all hardware manufacturers are now aggressively exploring multi-core platforms, lock contention is becoming a pressing concern for developers looking to write performance code. In this talk, the design and performance drawbacks of locks will be examined, together with recent development in the alternatives of locking. As an illustrative example, a new lock-free multi-threaded algorithm for the maximum network flow problem will be presented with significantly improved execution speed and scalability on multi-core architectures.
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