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dc.contributor.authorSadeghi, Mohamad Mehdi
dc.contributor.authorTimarchi, Somayyeh
dc.contributor.authorFazlali, Mahmood
dc.date.accessioned2023-07-21T11:00:02Z
dc.date.available2023-07-21T11:00:02Z
dc.date.issued2023-07-07
dc.identifier.citationSadeghi , M M , Timarchi , S & Fazlali , M 2023 , ' High-Performance Memory Allocation on FPGA with reduced Internal Fragmentation : Memory Allocation on FPGA ' , IEEE Access , vol. 11 , pp. 66672-66681 . https://doi.org/10.1109/ACCESS.2023.3290100
dc.identifier.issn2169-3536
dc.identifier.otherORCID: /0000-0002-7760-3411/work/139115112
dc.identifier.otherORCID: /0000-0002-1701-5562/work/139115132
dc.identifier.urihttp://hdl.handle.net/2299/26535
dc.description© 2023 The Author(s). This is an open access article under the CC BY-NC-ND licence. https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.description.abstractIn this paper, we present two distinct hardware dynamic memory allocation schemes that are based on the binary buddy system algorithm. Our aim is to mitigate internal fragmentation without impacting the area and performance of the system. The first scheme introduces a parallel design for calculating the addresses of free blocks, which results in a decrease in allocation latency while maintaining acceptable resource utilization. This scheme is particularly well-suited for managing a limited number of minimum allocable units (MAU). On the other hand, the second allocator can handle a large number of MAUs due to its innovative searching mechanism. This allocator exhibits lower resource consumption and operates with an acceptable allocation latency. Furthermore, to decrease internal fragmentation, we develop a novel update mechanism for allocating information data structures in both methods. By employing these two allocator schemes, we can improve the efficiency and resource management of dynamic memory allocation for hardware systems. Experimental results demonstrate that the first and second proposed schemes achieve a minimum allocation speed-up of ×2 and ×1.8 compared to their counterparts. At the same time, they achieve a reduction of at least 78% and %88 in resource utilization, respectively. The results show that the total fragmentation is reduced by at least 14% due to the lower internal fragmentation.en
dc.format.extent10
dc.format.extent4718904
dc.language.isoeng
dc.relation.ispartofIEEE Access
dc.subjectDynamic memory allocator
dc.subjectDynamic scheduling
dc.subjectField programmable gate arrays
dc.subjectHardware
dc.subjectHeuristic algorithms
dc.subjectMemory management
dc.subjectRegisters
dc.subjectResource management
dc.subjectfield programmable gate array (FPGA)
dc.subjecthigh-performance
dc.subjectinternal fragmentation
dc.subjectGeneral Computer Science
dc.subjectGeneral Materials Science
dc.subjectGeneral Engineering
dc.titleHigh-Performance Memory Allocation on FPGA with reduced Internal Fragmentation : Memory Allocation on FPGAen
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Computer Science
dc.description.statusPeer reviewed
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85163566782&partnerID=8YFLogxK
rioxxterms.versionofrecord10.1109/ACCESS.2023.3290100
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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