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020 _a9783031381331
_9978-3-031-38133-1
024 7 _a10.1007/978-3-031-38133-1
_2doi
050 4 _aTK7895.E42
072 7 _aUKM
_2bicssc
072 7 _aCOM092000
_2bisacsh
072 7 _aUKM
_2thema
100 1 _aAlsuhli, Ghada.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_965856
245 1 0 _aNumber Systems for Deep Neural Network Architectures
_h[electronic resource] /
_cby Ghada Alsuhli, Vasilis Sakellariou, Hani Saleh, Mahmoud Al-Qutayri, Baker Mohammad, Thanos Stouraitis.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer Nature Switzerland :
_bImprint: Springer,
_c2024.
300 _aXI, 94 p. 30 illus., 28 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Engineering, Science, and Technology,
_x2690-0327
505 0 _aIntroduction -- Conventional number systems -- DNN architectures based on Logarithmic Number System (LNS) -- DNN architectures based on Residue Number System (RNS) -- DNN architectures based on Block Floating Point (BFP) number system -- DNN architectures based on Dynamic Fixed Point (DFXP) number system -- DNN architectures based on Posit number system.
520 _aThis book provides readers a comprehensive introduction to alternative number systems for more efficient representations of Deep Neural Network (DNN) data. Various number systems (conventional/unconventional) exploited for DNNs are discussed, including Floating Point (FP), Fixed Point (FXP), Logarithmic Number System (LNS), Residue Number System (RNS), Block Floating Point Number System (BFP), Dynamic Fixed-Point Number System (DFXP) and Posit Number System (PNS). The authors explore the impact of these number systems on the performance and hardware design of DNNs, highlighting the challenges associated with each number system and various solutions that are proposed for addressing them.
650 0 _aEmbedded computer systems.
_964625
650 0 _aMicroprocessors.
_959300
650 0 _aComputer architecture.
_965857
650 0 _aNeural networks (Computer science) .
_964231
650 1 4 _aEmbedded Systems.
_965858
650 2 4 _aProcessor Architectures.
_965859
650 2 4 _aMathematical Models of Cognitive Processes and Neural Networks.
_965860
700 1 _aSakellariou, Vasilis.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_965861
700 1 _aSaleh, Hani.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_965862
700 1 _aAl-Qutayri, Mahmoud.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_965863
700 1 _aMohammad, Baker.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_965864
700 1 _aStouraitis, Thanos.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_965865
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031381324
776 0 8 _iPrinted edition:
_z9783031381348
776 0 8 _iPrinted edition:
_z9783031381355
830 0 _aSynthesis Lectures on Engineering, Science, and Technology,
_x2690-0327
856 4 0 _uhttps://doi.org/10.1007/978-3-031-38133-1
912 _aZDB-2-SXSC
999 _c56259
_d56259