Open AccessON CHIP MEMORY REDUCTION TECHNIQUE FOR DATA DOMINATED EMBEDDED SYSTEMS
Author(s) -
Srilatha Chepure,
Guru C.V. Rao,
Prabhu G Benakop
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.11.2.558
Subject(s) - computer science , computing with memory , interleaved memory , flat memory model , reduction (mathematics) , chip , uniform memory access , embedded system , parallel computing , memory management , cache , registered memory , computer hardware , semiconductor memory , computer engineering , telecommunications , geometry , mathematics
This paper proposes an approach for optimization of on-chip memory size in data dominated embedded systems. Large amount of array processing is being involved in this category. In order to produce a cost effective system, efficient designing of memory module is quite critical. The memory module configuration being selected by the designer should be well suitable for the application. In this regard, this paper presents a methodology for effective optimization of on-chip memory. For sensitive applications involving large array processing, the entire processing has to be done using embedded modules. While using such module s, care should be taken to meet optimized profile for the design metrics. With help of loop transformation technique, relatively a good amount of memory size requirement is reduced for the arrays. This approach results in a very close memory estimate and an effective optimization. This methodology can be further extended to meet the high level memory optimization applications based on cache characteristics. Speech processing front end mechanism is implemented and shows that this approach gives up to an achievement 61.3% reduction of overall system memory requirement over the estimation approach. Results are provided in terms of comparison of the two approaches of memory estimation and optimization with respect to both of the program and data segments.