The University of Texas at Arlington News Releases
Computer memory capacity has expanded greatly, allowing machines to access data and perform tasks very quickly, but accessing the computer’s central processing unit, or CPU, for each task slows the machine and negates the gains that a large memory provides.
Song Jiang, a UTA associate professor in the Department of Computer Science and Engineering, received an NSF grant to improve computer accessibility.
To counteract this issue, which is known as a memory wall, computers use a cache, which is a hardware component that stores recently accessed data that has already been accessed so that it can be accessed faster in the future. Song Jiang, an associate professor in the Department of Computer Science and Engineering at The University of Texas at Arlington, is using a three-year, $345,000 grant from the National Science Foundation to explore how to make better use of the cache by allowing programmers to directly access it in software.
“Efficient use of a software-defined cache allows quick access to data along with large memory. With memory becoming more expansive, we need to involve programmers to make it more efficient. The programmer knows best how to use the cache for a particular application, so they can add efficiency without making the cache a burden,” Jiang said.
When a computer accesses its memory, it must go through the index of all the data stored there, and it must do so each time it goes back to the memory. Each step slows the process. With a software-defined cache, the computer can combine or skip steps to access the data it needs automatically without having to go through the memory from the beginning each time. Jiang has studied these issues for several years and has developed four prototypes which he will test to determine if they can serve large memories without slowing CPU speeds at the same time.
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