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006 m o d
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008 200306s2020 flu o 000 0 eng d
040 _aOCoLC-P
_beng
_cOCoLC-P
020 _a9781351682336
_q(electronic bk.)
020 _a1351682334
_q(electronic bk.)
020 _a9781315167220
_q(electronic bk.)
020 _a1315167220
_q(electronic bk.)
020 _a9781351682343
_q(electronic bk. : PDF)
020 _a1351682342
_q(electronic bk. : PDF)
020 _z1138053546
020 _z9781138053540
035 _a(OCoLC)1142892166
035 _a(OCoLC-P)1142892166
050 4 _aQA76.76.D47
072 7 _aCOM
_x012040
_2bisacsh
072 7 _aCOM
_x051230
_2bisacsh
072 7 _aCOM
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072 7 _aUB
_2bicssc
082 0 4 _a005.1
_223
100 1 _aBhattacharya, Suparna.
_919952
245 1 0 _aRESOURCE PROPORTIONAL SOFTWARE DESIGN FOR EMERGING SYSTEMS
_h[electronic resource].
260 _aBOCA RATON :
_bCRC PRESS,
_c2020.
300 _a1 online resource
520 _aEfficiency is a crucial concern across computing systems, from the edge to the cloud. Paradoxically, even as the latencies of bottleneck components such as storage and networks have dropped by up to four orders of magnitude, software path lengths have progressively increased due to overhead from the very frameworks that have revolutionized the pace of information technology. Such overhead can be severe enough to overshadow the benefits from switching to new technologies like persistent memory and low latency interconnects. Resource Proportional Software Design for Emerging Systems introduces resource proportional design (RPD) as a principled approach to software component and system development that counters the overhead of deeply layered code without removing flexibility or ease of development. RPD makes resource consumption proportional to situational utility by adapting to diverse emerging needs and technology systems evolution. Highlights: Analysis of run-time bloat in deep software stacks, an under-explored source of power-performance wastage in IT systems Qualitative and quantitative treatment of key dimensions of resource proportionality Code features: Unify and broaden supported but optional features without losing efficiency Technology and systems evolution: Design software to adapt with changing trade-offs as technology evolves Data processing: Design systems to predict which subsets of data processed by an (analytics or ML) application are likely to be useful System wide trade-offs: Address interacting local and global considerations throughout software stacks and hardware including cross-layer co-design involving code, data and systems dimensions, and non-functional requirements such as security and fault tolerance Written from a systems perspective to explore RPD principles, best practices, models and tools in the context of emerging technologies and applications This book is primarily geared towards practitioners with some advanced topics for researchers. The principles shared in the book are expected to be useful for programmers, engineers and researchers interested in ensuring software and systems are optimized for existing and next generation technologies. The authors are from both industry (Bhattacharya and Voigt) and academic (Gopinath) backgrounds.
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aComputer software
_xDevelopment.
_93349
650 7 _aCOMPUTERS / Computer Graphics / Game Programming & Design
_2bisacsh
_912289
650 7 _aCOMPUTERS / Programming / Software Development
_2bisacsh
_919953
650 7 _aCOMPUTERS / Computer Engineering
_2bisacsh
_94770
700 1 _aGopinath, Kanchi.
_919954
700 1 _aVoigt, Doug.
_919955
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781315167220
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942 _cEBK
999 _c72235
_d72235