Abstract

As the gap between memory and processor speeds continues to widen, cache eficiency is an increasingly important component of processor performance. Compiler techniques have been used to improve instruction cache pet$ormance by mapping code with temporal locality to different cache blocks in the virtual address space eliminating cache conflicts. These code placement techniques can be applied directly to the problem of placing data for improved data cache pedormance.In this paper we present a general framework for Cache Conscious Data Placement. This is a compiler directed approach that creates an address placement for the stack (local variables), global variables, heap objects, and constants in order to reduce data cache misses. The placement of data objects is guided by a temporal relationship graph between objects generated via profiling. Our results show that profile driven data placement significantly reduces the data miss rate by 24% on average.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.