LEADER 03463oam 2200493 450 001 9910299745203321 005 20190911103512.0 010 $a1-4614-7798-0 024 7 $a10.1007/978-1-4614-7798-3 035 $a(OCoLC)858403117 035 $a(MiFhGG)GVRL6USJ 035 $a(EXLCZ)992670000000427489 100 $a20140415d2014 uy 0 101 0 $aeng 135 $aurun|---uuuua 181 $ctxt 182 $cc 183 $acr 200 10$aComputing with memory for energy-efficient robust systems /$fSomnath Paul, Swarup Bhunia 205 $a1st ed. 2014. 210 1$aNew York :$cSpringer,$d2014. 215 $a1 online resource (xiii, 210 pages) $cillustrations (some color) 225 0 $aGale eBooks 300 $aDescription based upon print version of record. 311 $a1-4614-7797-2 320 $aIncludes bibliographical references. 327 $aPart I Introduction -- Challenges in Computing for Nanoscale Technologies -- A Survey of Computing Architectures -- Motivation for a Memory-Based Computing Hardware -- Part II Memory Based Computing -- Key Features of Memory-Based Computing -- Overview of Hardware and Software Architectures -- Application of Memory-Based Computing -- Part III Hardware Framework -- A Memory Based Generic Reconfigurable Framework -- MAHA Hardware Architecture -- Part IV Software Framework -- Application Analysis -- Application Mapping to MBC Hardware. 330 $aThis book analyzes energy and reliability as major challenges faced by designers of computing frameworks in the nanometer technology regime.  The authors describe the existing solutions to address these challenges and then reveal a new reconfigurable computing platform, which leverages high-density nanoscale memory for both data storage and computation to maximize the energy-efficiency and reliability. The energy and reliability benefits of this new paradigm are illustrated and the design challenges are discussed. Various hardware and software aspects of this exciting computing paradigm are described, particularly with respect to hardware-software co-designed frameworks, where the hardware unit can be reconfigured to mimic diverse application behavior.  Finally, the energy-efficiency of the paradigm described is compared with other, well-known reconfigurable computing platforms.  ·         Introduces new paradigm for hardware reconfigurable frameworks, which leverages dense memory array as a malleable resource, which can be used for information storage as well as computation; ·         Merges spatial and temporal computing to minimize interconnect overhead and achieve better scalability compared to state-of-the-art reconfigurable computing platforms; ·         Enables efficient mapping of diverse data-intensive applications from domains of signal processing, multimedia and security applications. 606 $aNanoelectromechanical systems 606 $aComputer engineering 615 0$aNanoelectromechanical systems. 615 0$aComputer engineering. 676 $a004.1 676 $a620 676 $a621.381 676 $a621.3815 700 $aPaul$b Somnath$4aut$4http://id.loc.gov/vocabulary/relators/aut$0957747 702 $aBhunia$b Swarup 801 0$bMiFhGG 801 1$bMiFhGG 906 $aBOOK 912 $a9910299745203321 996 $aComputing with Memory for Energy-Efficient Robust Systems$92169653 997 $aUNINA LEADER 04815nam 22007095 450 001 9910298561303321 005 20200705060120.0 010 $a3-319-03629-7 024 7 $a10.1007/978-3-319-03629-8 035 $a(CKB)3710000000111938 035 $a(EBL)1730968 035 $a(OCoLC)884645917 035 $a(SSID)ssj0001237567 035 $a(PQKBManifestationID)11708220 035 $a(PQKBTitleCode)TC0001237567 035 $a(PQKBWorkID)11258537 035 $a(PQKB)11443628 035 $a(MiAaPQ)EBC1730968 035 $a(DE-He213)978-3-319-03629-8 035 $a(PPN)17877880X 035 $a(EXLCZ)993710000000111938 100 $a20140507d2014 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aSoftware Project Effort Estimation $eFoundations and Best Practice Guidelines for Success /$fby Adam Trendowicz, Ross Jeffery 205 $a1st ed. 2014. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014. 215 $a1 online resource (483 p.) 300 $aDescription based upon print version of record. 311 $a3-319-03628-9 320 $aIncludes bibliographical references and index. 327 $aPART I Foundations -- Challenges of Predictable Software Development -- Principles of Effort and Cost Estimation -- Common Factors Influencing Software Project Effort -- Estimation under Uncertainty -- Basic Estimation Strategies -- PART II Selecting An Appropriate Estimation Method -- Classification of Effort Estimation Methods -- Finding the Most Suitable Estimation Method -- PART III Popular Effort Estimation Methods -- Statistical Regression Analysis -- Constructive Cost Model ? COCOMO -- Classification and Regression Trees -- Case-Based Reasoning -- Wideband Delphi -- Planning Poker -- Bayesian Belief Networks ? BBN -- CoBRA -- PART IV Establishing Sustainable Effort Estimation -- Continuously Improving Effort Estimation -- Effort Estimation Best Practices -- Appendix. 330 $aSoftware effort estimation is one of the oldest and most important problems in software project management, and thus today there are a large number of models, each with its own unique strengths and weaknesses in general, and even more importantly, in relation to the environment and context in which it is to be applied. Trendowicz and Jeffery present a comprehensive look at the principles of software effort estimation and support software practitioners in systematically selecting and applying the most suitable effort estimation approach. Their book not only presents what approach to take and how to apply and improve it, but also explains why certain approaches should be used in specific project situations. Moreover, it explains popular estimation methods, summarizes estimation best-practices, and provides guidelines for continuously improving estimation capability. Additionally, the book offers invaluable insights into project management in general, discussing issues including project trade-offs, risk assessment, and organizational learning. Overall, the authors deliver an essential reference work for software practitioners responsible for software effort estimation and planning in their daily work and who want to improve their estimation skills. At the same time, for lecturers and students the book can serve as the basis of a course in software processes, software estimation, or project management. 606 $aSoftware engineering 606 $aManagement information systems 606 $aComputer science 606 $aProject management 606 $aSoftware Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/I14029 606 $aManagement of Computing and Information Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I24067 606 $aProject Management$3https://scigraph.springernature.com/ontologies/product-market-codes/515020 606 $aSoftware Management$3https://scigraph.springernature.com/ontologies/product-market-codes/522050 615 0$aSoftware engineering. 615 0$aManagement information systems. 615 0$aComputer science. 615 0$aProject management. 615 14$aSoftware Engineering. 615 24$aManagement of Computing and Information Systems. 615 24$aProject Management. 615 24$aSoftware Management. 676 $a004 676 $a005.1 676 $a005.3068 676 $a005.74 700 $aTrendowicz$b Adam$4aut$4http://id.loc.gov/vocabulary/relators/aut$0945790 702 $aJeffery$b Ross$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910298561303321 996 $aSoftware Project Effort Estimation$92135959 997 $aUNINA