System-level data-format exploration for dynamically allocated data structures

System-level exploration of memory organizations is a key issue in successf ul implementation of data dominated applications based on dynamically alloc ated data structures involving records and access keys. This paper presents a formalized technique for exploring different memory data-format alternat ives when only the system level functional behavior of the application has been defined. Our data-format exploration approach allows to substantially minimize the number of accessed bits by rearranging the format of the data records. The technique exploits parallelism in the data transfer by analyzi ng the dependencies between data-record accesses. As a result, significant reduction in memory size, bandwidth, and power are obtained. We have valida ted our techniques using several real-life asynchronous transfer mode cell processing applications, where we have obtained reductions in memory size ( up to 20%), power (up to a 60%), and bandwidth.