relation: https://khub.utp.edu.my/scholars/9670/
title: Fine-Grained Overhead Analysis Utilizing Atomic Instructions for Cross-ISA Dynamic Binary Translation on Multicore Processor
creator: Oni, J.-O.
creator: Hussin, F.A.
creator: Zakaria, N.
description: Modern software processing often involving other apps while running active apps to fulfill task requirements, which have caused the increment of program processing time inside heterogeneous multicore system-on-chip (SoC) processor. For available core usage efficiency improvement, concurrent compilation techniques has been applied into mix modes of statically and dynamically Dynamic Binary Translation and Optimisation (DBTO) process, to better service the combined applications processing. This research deep dived into finer-grained DBTO overhead analysis, to provide categorization and characterization of overhead sources in breakdown stages during concurrent instruction processing. A dual-engine of translation and optimization architecture is constructed for finer management of start-up overheads. Helper functions, i.e. LoadLink/StoreCondition (LL/SC) are derived from atomic instructions, to create multiple helper thread supported by multiple host cores, for better instruction translation and optimization operation concurrently. Our experiment platform, evaluated through PARSEC-3.0 benchmark suite, showed performance improvement approaching 2.0x for apps based programs and 1.25x for kernel based programs, for x86 to X86-64 emulation. This technique explore performance beyond hardware and software only limitations, and possess great potential for future parallel program processing improvement. © 2018 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2018
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Oni, J.-O. and Hussin, F.A. and Zakaria, N.  (2018) Fine-Grained Overhead Analysis Utilizing Atomic Instructions for Cross-ISA Dynamic Binary Translation on Multicore Processor.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059740955&doi=10.1109%2fICIAS.2018.8540622&partnerID=40&md5=828ff2de5f4512bb3c5406fe895cdd86
relation: 10.1109/ICIAS.2018.8540622
identifier: 10.1109/ICIAS.2018.8540622