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B.Tech. Degree Programme Computer Science & Engineering

B.Tech. Degree Programme Computer Science & Engineering

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Lingaya’s University, Faridabad3. http://en.wikipedia.org/wiki/Data_compression4. http://www.debugmode.com/imagecmp/CS-431ADVANCED COMPUTER L T P CrARCHITECTURE 5 0 0 3OBJECTIVETo introduce various technological aspects aboutparallelism in super computing, microprocessorssupporting such high scale computing, other hardwarearchitectures, ultimately leading to high performancecomputing through grid computing.PRE-REQUISITESKnowledge of digital electronics, digital system design,computer networks and computer organization &architecture1. PARALLEL COMPUTER MODELS: The state ofcomputing, multiprocessors and multicomputers;multi-vector and SIMD computers; architecturaldevelopment tracks.2. PROGRAM AND NETWORK PROPERTIES:Conditions of parallelism; data and resourcedependences; hardware and software parallelism;program partitioning and scheduling; grain sizeand latency; program flow mechanisms; controlflow versus data flow, data flow architecture;demand driven mechanisms; comparisons of flowmechanisms3. SYSTEMS INTERCONNECT ARCHITECTURES:Network properties and routing, staticinterconnection networks; dynamic interconnectionnetworks; multiprocessor system interconnects;hierarchical bus systems; crossbar switch andmultiport memory; multistage and combiningnetwork.4. PROCESSORS AND MEMORY HIERARCHY:Advanced processor technology; instruction-setarchitectures; CISC scalar processors; RISC scalarprocessors; superscalar processors, VLIWarchitectures; vector and symbolic processorsmemory technology: hierarchical memorytechnology, inclusion, coherence and locality,memory capacity planning, virtual memorytechnology5. BACKPLANE BUS SYSTEM: Backplane busspecification; addressing and timing protocols;arbitration transaction and interrupt; cacheaddressing models; direct mapping andassociative caches.6. PIPELINING: Linear pipeline processor; nonlinearpipeline processor; instruction pipeline design;mechanisms for instruction pipelining; dynamicinstruction scheduling; branch handlingtechniques; arithmetic pipeline design; computerarithmetic principles; static arithmetic pipeline,multifunctional arithmetic pipelines.7. VECTOR PROCESSING PRINCIPLES: Vectorinstruction types; vector-access memory schemes;synchronous parallel processing: SIMDarchitecture and programming principles; SIMDparallel algorithms; SIMD computers andperformance enhancementTEXT BOOKHwang Kai and Briggs A., “Advanced <strong>Computer</strong>Architecture”, Tata McGraw Hill, 2008REFERENCE BOOKS1. Hennessy John L. and Patterson David A.,“<strong>Computer</strong> Architecture: A Quantitative Approach”,3rd edition, 20022. Flynn Michael J., “Pipelined and Parallel ProcessorDesign”, Narosa Publications, Reprint 20093. Hwang Kai and Briggs A., “<strong>Computer</strong>Architecture and Parallel Processing”, McGraw-Hill, 19904. Sima Dezso, Fountain Terence and Kacsuk Peter,“Advanced <strong>Computer</strong> Architectures”, PearsonEducationWEB REFERENCES1. http://www.doc.ic.ac.uk/~phjk/AdvancedCompArchitecture/Lectures/2. http://www.ecs.syr.edu/faculty/ercanli/cse661/3. http://cs.binghamton.edu/~nael/classes/cs325/CS-432NATURAL LANGUAGE L T P CrPROCESSING 5 0 0 3OBJECTIVETo motivate understanding of issues related to naturallanguage understanding, generation and translation,which ultimately linked to machine learning, computervision and expert systems. This course provides anintroduction to the field of computational linguistics,also called natural language processing (NLP) - thecreation of computer programs that can understandand generate natural languages (such as English).Natural language understanding as a vehicle will beused to introduce the three major subfields of NLP:syntax (which concerns itself with determining thestructure of an utterance), semantics (which concernsitself with determining the explicit truth-functionalmeaning of a single utterance), and pragmatics (whichconcerns itself with deriving the context-dependentmeaning of an utterance when it is used in a specificdiscourse context). The course will introduce bothknowledge-based and statistical approaches to NLP,illustrate the use of NLP techniques and tools in avariety of application areas, and provide insight intomany open research problems.PRE-REQUISITESKnowledge of theory of computations1. INTRODUCTION TO NATURAL LANGUAGEUNDERSTANDING: The study of language;applications of NLP; evaluating languageunderstanding systems; different levels oflanguage analysis; representations andunderstanding; organization of natural languageunderstanding systems; linguistic background: anoutline of English syntax.2. GRAMMARS AND PARSING: Grammars andsentence structure; top-down and bottom-upparsers; transition network grammars; top-downchart parsing; feature systems and augmentedgrammars: basic feature system for English37

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