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New Model Reduces Data Access Delay, Could Increase Speed by Up to 100x

II Today (03/11/14) 

Illinois Institute of Technology professor Xian-He Sun has developed Concurrent Average Memory Access Time (C-AMAT), a new mathematical model for reducing data access delay that promises to cut the penalty associated with accessing data and increase speed by up to 100 times through parallel memory access. “There’s no question the primary limits on computing performance–from mobile phones to supercomputers–are the costs associated with data movement,” says University of Chicago professor Andrew A. Chien. “Dr. Sun’s work attacks the critical problem of understanding and modeling data movement costs and systems performance and, thus, may enable better performing software [today] and improved hardware designs in the future.” C-AMAT is the first formal mathematical model to promote and evaluate the concept of parallel memory for reducing data access delay via explicit parallel data access. In addition, C-AMAT can mitigate the memory-wall effect and improve memory system performance. “The most profound research is not the design of the fastest algorithm for a given problem; it is revealing a fundamental computing property so hundreds or even thousands of algorithms can be developed upon it,” says Sun, creator of Sun-Ni’s law–one of three scalable computing laws along with Amdahl’s law and Gustafson’s law.


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