21. Computer Science: Pipelined Processor Topic computer science. will the size of the data bus affect the speed of the computer? pages 1.www.nuvisionmiami.com/books/asm/3rd/workbook/pipelining.htm 2 http://experts.about.com/q/3197/3227527.htm

zJs=10 zJs=11 zJs=12 zJs=13 zc(5,'jsc',zJs,9999999,'') About AllExperts Experts Search Web Hosting Experts: Computer Science Volunteer Answers to one of thousands of questions Home More Questions Question Library zmhp('style="color:#fff"') Subjects More Topic Questions Question Library A B ... Link to Us Newsletter Signup Subscribe to ExperTease Advertising Free Credit Report Topic: Computer Science Expert: Samarth Bartaria Date: Subject: pipelined processor Question hi i have 2 questions if you dont mind: Q1)could you give me sites that are talking about pipelined processors with some exercises because i tried some but i didnt get good knowledge Q2) if we are trying to buy a computer with speed 5GHTZ will the size of the data bus affect the speed of the computer? Answer Hi Hanaa. You see, if my processor has only 16 bit registers, I dont thing having a bigger 50 bit data bus will help.Speed may increase If I bank my memory into several banks. I still need to get a clearer answer.You will agree that the answer above is not very satisfactory. The reason being, that if I increase my data bus size, would it increase the speed at which processor writes data into main memory? But if I can only put d0 to d16 at a time what good would a bigger data bus do? I will still look for better answers and when I find one I will send you a followup.

22. UCR: Computer Science Parallel and Distributed Processing. (4) S. Prerequisite(s) computer science 161 or equivalent. Parallel programming languages. pipelining and supercomputing. http://www.students.ucr.edu/9697catalog/cs.html

1996-97 University of California, Riverside General Catalog This page was last updated Thursday, August 15, 1996. COMPUTER SCIENCE Faculty Department Undergraduate Curricula Graduate Curricula ... Graduate Courses Thomas H. Payne, Ph.D., Chair Department Office, A242 Bourns Hall Professors: Mart L. Molle, Ph.D. Teodor C. Przymusinski, Ph.D. Professor Emeritus: Lawrence L. Larmore, Ph.D. Associate Professors: Marek Chrobak, Ph.D. Yang-Chang Hong, Ph.D. Yu-Chin Hsu, Ph.D. Thomas H. Payne, Ph.D. Assistant Professors: Brett D. Fleisch, Ph.D. Gary S. Tyson, Ph.D. Frank N. Vahid, Ph.D. Adjunct Associate Professor: Halina Przymusinska, Ph.D. MAJOR The Computer Science Department offers a B.S. degree in Computer Science and an M.S. and a Ph.D. degree in Computer Science. These programs provide the basis for careers in research and development in the computer science field as well as technical and nontechnical related fields that are dependent on a working knowledge of computers. The Computer Science major has been designed to provide the student with a broad background in science and humanities and to provide an understanding of fundamental principles of computing and modern computing technology. It prepares the student for professional work with computer systems as well as for graduate work in computer science. Each Computer Science major is assigned a Departmental Advisor who assists the student in formulating educational goals and who monitors the student's subsequent progress in an academic program. Each quarter a study list must be approved by this advisor and filed by the student in the Department office.

23. Computer Science Courses and timing, instruction pipeline design, arithmetic pipeline design, and superscalar pipelining. 3 CSCI 381 Special Topics in computer science 381.1381.4 http://www.cs.qc.edu/undergrad/courses/description.shtml

Undergraduate Computer Science Course Descriptions CSCI 012: Understanding and Using Personal Computers CSCI 018 : Computers with Business Applications CSCI 080 : Problem Solving with Computers CSCI 081 : HTML and WWW Programming ... CSCI 700-LEVEL: Graduate Courses for Undergraduates CSCI 012: Understanding and Using Personal Computers Two and one-half years of high school mathematics, including intermediate algebra, or Mathematics 6 or 8. Hands-on introduction to computers, computation, and the basics of computer hardware and software. Students will have experience during the instructed microcomputer lab with a number of software environments including an operating system, a word processor, a spreadsheet and a database package. The course will focus on problem solving and programming with the context of these packages. In addition, students will acquire the skills needed to learn other software packages on their own. Not open for credit to students who have taken Computer Science 18. Prerequisite(s): Two and one-half years of high school mathematics, including intermediate algebra, or Mathematics 6 or 8. Credits: 3 CSCI 018 : Computers with Business Applications Fundamentals of using the operating system and application software. Business-oriented uses of software applications including: word processing, spreadsheets, presentations, and database management. Emphasis on realistic situations and problem solving strategies used in business. An important part of the course is a research project/presentation of topics involving current issues arising from the use of computer technology in a business environment.

24. GW Bulletin | COMPUTER SCIENCE Theoretical foundations of computer science. Introduction to highspeed computer architecture Principles of pipelining and vector processing, pipeline computers http://www.gwu.edu/~bulletin/grad/csci.html

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25. ECS 154B, Department Of Computer Science to RISC philosophy, and interactions with pipelining, orthogonal instruction sets, etc. computer Usage Engineering science 2 units Engineering Design 2 units. http://www.cs.ucdavis.edu/courses/exp_course_desc/154B.html

ECS 154B: Upper Division Home Courses Course Descriptions ECS 154B COMPUTER ARCHITECTURE (4) I, II, III Lecture: 3 hours Discussion: 1 hour Prerequisites: Course ECS 154A or EEC 170, and course ECS 110 Grading: Letter; two midterms (20% each), final exam (40%) and programming and digital design work (20%) Catalog Description: Hardwired and microprogrammed CPU design. Memory hierarchies. Uniprocessor performance analysis under varying program mixes. Introduction to pipelining and multiprocessors. Expanded Course Description: Hardwired and Microprogrammed CPU Design Internal bus systems. Register transfer languages. Microprogramming. Homework using digital design software to implement part or all of a simple CPU. Memory Hierarchies General idea of multilevel memory systems. Emphasis here is on caches, since virtual memory is covered in courses 154A, 150, 151AB. Uniprocessor Performance Analysis Instruction set profile analyses under varying program mixes. Cost/performance tradeoffs. Introduction to RISC philosophy, and interactions with pipelining, orthogonal instruction sets, etc. Multiprocessor Speedup Introduction to shared-memory and message-passing multiprocessor systems.

26. Selected Graduate Courses, Graduate Group In Computer Science WithinCPU parallelism, through pipelining. Offered in alternate years. ECS 289A-M - Special Topics in computer science Special topics in http://www.cs.ucdavis.edu/graduate/grad-crs.html

Selected Graduate Courses Home Graduate Recruitment Department of Computer Science (ECS Department of Electrical and Computer Engineering (EEC ECS 201A (Formerly ECS 250A) - Advanced Computer Architecture: Introduction to modern research topics and methods in computer architecture. Design implications of memory latency and bandwidth limitations. Performance enhancement via within-processor and between-processor parallelism. Term project involving student-proposed extensions/modifications of work in the research literature. ECS 201B (Formerly ECS 250B) - High-Performance Uniprocessing: Maximizing uniprocessor performance. Barriers to high performance; solutions to the problems; historical and current processor designs. ECS 201C (Formerly ECS 250C) - Parallel Architectures: Evolution of parallel architectures from special-purpose machines to commodity servers. Emphasis on recent machines and applications that drive them. Not open for credit to students who have completed course 250C. EEC 207 - Pattern Recognition and Classification: Topics in statistical pattern recognition and classification: linear decision functions and minimum distance classification, Bayes decision theory, clustering algorithms, the generalized perceptron, multi-layer neural networks, and feature extraction.

27. Institute Of Computer Science: Courses: Graduate Associative processor architectures; parallel processing and pipelining; multiprocessors; multi CMSC 391, Special Topics (3). Special topics in computer science. http://www.ics.uplb.edu.ph/courses/grad.shtml

Jobs@ICS OnSET Alumni Registry Directory ... HOME LIST OF GRADUATE COURSES Quick Links Graduate Diploma Courses Applied Science Course Information Technology Courses Computer Science Courses ... List of Undergraduate Courses DIPLOMA COURSES CMSC A Discrete Structures in Computer Science (3). Logical structures; sets; combinatorial structures; graphs; formal systems. CMSC B Principles of Programming (3). Algorithm representation, implementation using a high-level language, systematic program development using top-down design, and program verification. CMSC C Computer Systems and Organization (3). Internal organization of a computer; how this organization is used to represent data, execute programs and communicate to the outside world; assembly language programming; and basic operating system concepts. CMSC D Data Structures and Algorithms (3). Abstract data type; their implementations and use in algorithm design. COI CMSC E Data Communications and Networking (3). Principles of data communications and computer networks. CMSC C or COI CMSC F Database Management Systems (3). Design and implementation of database management systems; relational database and query optimization; and future trends in database design. CMSC B and CMSC D, or

28. Institute Of Computer Science: Courses: Undergraduate Mathematical Structures in computer science II (3 3). Advanced topics in computer systems organization of view multiprocessing, pipelining, array processors http://www.ics.uplb.edu.ph/courses/ugrad.shtml

Jobs@ICS OnSET Alumni Registry Directory ... HOME LIST OF UNDERGRADUATE COURSES Quick Link List of Graduate Courses UNDERGRADUATE COURSES IT 1 Information Technology Literacy CMSC 1 Introduction to Personal Computing CMSC 2 Introduction to the Internet (3). Tools and services of the Internet. Internet protocols, search engines, file transfer protocols (FTP), e-mail, list servers, and hypertext markup languages programming. (1, 2) CMSC 11 Introduction to Computer Science (3). Introduction to the major areas of computer science; software systems and methodology; computer theory; computer organization and architecture. Students learn to write programs using high-level block-structured programming language. (1, 2, S), MATH 11 or MATH 17. CMSC 21 Fundamentals of Programming (3). Expansion and development of materials introduced in CMSC 11; processing of files and linked-lists; programing in the C language; recursion; systematic program development; top-down design and program verification. (1, 2), CMSC 11. CMSC 22 Object-Oriented Programming (3). Objects; design and implementation of object-oriented programs. (1, 2), CMSC 11.

29. Computer Science Course Listing assemblers and assembly language programming, memory hierarchies, caches, RISC architectures, and pipelining. Prerequisite computer science 127 or consent of http://www.mathcs.carleton.edu/courses/cs.html

The Structure of the Internet Introduction to Computer Science Data Structures Parallel Computing ... Integrative Exercise (Senior Examination) The Structure of the Internet An introduction to computer science through the study of the architecture of the Internet. Protocols, clients and servers, the TCP/IP protocol suite, HTTP, HTML, database-driven Web page programming, network security, distributed algorithms, and the history and administrative structure of the Internet. This course is designed for students who have never previously taken a programming course. Students who have taken Computer Science 127 may not enroll in Computer Science 107. 6 credits, MS Introduction to Computer Science Elements of procedure-oriented languages. Problem solving and implementation of algorithms. Program design and documentation. Measures of efficiency and complexity. Iterative and recursive techniques. Non-numerical and numerical applications. Files, pointers and linked structures. 6 credits, MS Data Structures An introduction to abstract data types, recursion, searching, sorting, stacks, queues, linked lists, trees and graphs.

30. Computer Science Department CCNY computer science Department CCNY. set architecture,. Representing instructions in the computer,; pipelining. Pipelined datapath; Pipelined control; Control and data http://www-cs.engr.ccny.cuny.edu/~gertner/Cs342Spring2004/ROOTCs342/MainSyllabus

Computer Science Department CCNY Computer Organization: Hardware/Software Interface Computer Abstraction. The role of performance. Computer arithmetic: Computer representation of integers, fractions, rational, irrational numbers; Negative number representation and arithmetic; Multiplication algorithms, Division algorithms Students will explore arithmetic instructions using (SPIM) simulator. Machine language, instruction set architecture, Representing instructions in the computer, Addressing modes Control instructions Procedure call instructions RISC versus CISC instructions Students will perform projects using SPIM simulator and assembler. Construction of arithmetic logic unit(ALU) Design of 32 bit ALU Carry lookahead Overflow detection Student will design complete 4bit ALU using VHDL and simulate it (using MAXPLUS2 Software from ALTERA Corp.) The processor Datapath Single clock cycle control Multiple clock cycle control Microprogramming RISC versus CISC Student will design controller using graphical FSM design tools and VHDL. Pipelining Pipelined datapath Pipelined control Control and data hazards, stalls

31. Computer Science At Bard College // Courses Topics include instruction sets, pipelining, instructionlevel parallelism, caches, memory Corequisite computer science 142, with Physics 212 recommended. http://inside.bard.edu/academic/division/science/computer/courses/

Core Courses (offered every year or every other year) Computer Science 141, Computer Science I Computer Science 142, Computer Science II Computer Science 225, Computer Architecture Computer Science 243, Functional Programming ... Computer Science 351, Artificial Intelligence Elective Courses (offered at least once every three years or by tutorial) Computer Science 321, Databases: Theory and Practice Computer Science 352, Biologically-Inspired Machine Learning Computer Science 373, Software Interface Design Computer Science 401, Topics in Computational Complexity ... Computer Science 451, Topics in Advanced Artificial Intelligence Tutorials The Computer Science Program also offers tutorials on advanced topics not included in the topics offered during the current semester. Course Descriptions Great Ideas in Computer Science (and How They Make the Internet Work) Computer Science 103 Introduction to Robotics Computer Science 104 This course introduces students to ideas that are fundamental to robotics and to computing in general. Teams of students will design and build shoebox-sized robots, with guidance from the instructor. These rather minimalist robots will be mobile and will have multiple sensors. The student teams will use a simple programming language to program their robots to carry out simple tasks, and will move to a more robust programming language and more complex tasks by the end of the semester. Prerequisite: eligibility for Q courses.

32. Research Papers Available in SpringerVerlag Lecture Notes in computer science Series. Improving Software pipelining with Unroll-and-Jam , S. Carr, C. Ding and P. Sweany, in http://www.cs.rochester.edu/~cding/publications.html

Research Papers " Adaptive Data Partition for Sorting using Probability Distribution ", Xipeng Shen, and Chen Ding, in Proceedings of International Conference on Parallel Processing , Montreal, Canada, August 2004. " Array Regrouping and Structure Splitting Using Whole-Program Reference Affinity ", Yutao Zhong, Maksim Orlovich, Xipeng Shen, and Chen Ding, in Proceedings of ACM SIGPLAN Conference on Programming Language Design and Implementation , Washington DC, June 2004. " Improving Effective Bandwidth through Compiler Enhancement of Global Cache Reuse ", Chen Ding and Ken Kennedy, Journal of Parallel and Distributed Computing, Volume 64, Issue 1, January 2004, Elsevier Press " Regression-Based Multi-Model Prediction of Data Reuse Signature ", Xipeng Shen, Yutao Zhong, and Chen Ding, in Proceedings of the th Annual Symposium of the Los Alamos Computer Science Institute , Sante Fe, New Mexico, October 2003. " A Hierarchical Model of Reference Affinity ", Yutao Zhong, Xipeng Shen, and Chen Ding, in Proceedings of the th International Workshop on Languages and Compilers for Parallel Computing , College Station, Texas, October 2003.

33. UTD Computer Science Course Descriptions (30) S CS 5330 computer science II (3 semester hours) Basic concepts of computer organization Numbering generation process, CPU datapath, pipelining, RISC vs http://www.utdallas.edu/student/catalog/grad02/CS-EE-TE/CS/4.CScourse-desc022802

Back to Catalog Contents Course Descriptions CS 5301 (EE 5301) Advanced Professional and Technical Communication (3 semester hours) CS 5301 utilizes an integrated approach to writing and speaking for the technical professions. The advanced writing components of the course focus on writing professional quality technical documents such as proposals, memos, abstracts, reports, letters, emails, etc. The advanced oral communication components of the course focus on planning, developing, and delivering dynamic, informative and persuasive presentations. Advanced skills in effective teamwork, leadership, listening, multimedia and computer generated visual aids are also emphasized. Graduate students will have a successful communication experience working in a functional team environment using a real time, online learning environment. (3-0) Y CS 5303 Computer Science I (3 semester hours ) Computer science problem solving. The structure and nature of algorithms and their corresponding computer program implementation. Programming in a high level block-structured language (e.g., PASCAL

34. Department Of Comptuer Science| Saint Louis University systems; protection mechanisms for accessing jobs; pipelining and parallelism Project (3) Prerequisite Senior Standing in Applied computer science or computer http://cs.slu.edu/cscourses.html

CS Home Contact CS SLU Links Computer Science Courses updated: Fall 2003 CS-P101 Freshman Computer Science (1) Prerequisite: Declared CS major. Parks College orientation: majors, library resources, internship and co-op opportunities, student services; overview of computer science as a discipline and as a career; computer systems, operating systems; the Unix environment; the web and web languages. Fall semesters. CS-P105 Computing and Society (3) Prerequisite: None. Ethical, social, legal, and economic issues as they relate to the computer science profession; ethical theory; history of computing; impact of computers on society; computer professional's code of ethics; information privacy; information reliability; computer laws, crimes, and punishments; intellectual property; ethical concerns relating from emerging technologies. Spring semesters. CS-P111 Introduction to Computer Programming with Fortran 90 (3) Prerequisite: MT-A120 or equivalent. Use of computers as problem-solving tools; construction and implementation of algorithms in the FORTRAN programming language; decision structures, loops, arrays, and modular, structured programming techniques are employed in assignments which cover a range of scientific and engineering applications. Credit will not be given for both CS-P111 and CS-P125. Fall and Spring semesters. CS-P115 Discrete Structures (3) Prerequisite: MT-A120 or equivalent.

35. Computer Science-Course Catalog Bucknell University Switching theory, processor design, pipelining, cache and storage systems. 376. computer science Honors Thesis (I and II and S; R) Half to full course. http://www.bucknell.edu/Academics/Academic_Offices_Resources/Course_Catalog/Cour

Home Academics Course Catalog Course Descriptions ... University Directory Computer Science Computer Science (CSCI) Professors : Maurice F. Aburdene, Gary Haggard (Chair) Associate Professors : Daniel C. Hyde, Jerud J. Mead, Xiannong Meng, Patricia A.Wenner, Richard J. Zaccone Assistant Professors : Stephen M. Guattery, Antonio Miranda (visiting), Luiz Felipe Perrone Students who wish to major in computer science may enroll in the bachelor of science in computer science and engineering curriculum (see page 240), in the bachelor of science curriculum (see page 56), or the bachelor of arts curriculum (see page 56). The minor in computer science requires five computer science courses: CSCI 203, 204, 206, and two additional courses chosen from CSCI 208 or the 300-level computer science courses. 180. Introduction to a Microcomputer Environment (I and II; 3, 1) Topics include the history of computers, hardware, software, file organization, data communications, systems analysis and design, programming, and societal issues. Labs use an operating system, a wordprocessor, a spreadsheet, and a programming language. Not open to computer science majors or students who have taken CSCI 203, CSCI 204, or who are enrolled in the College of Engineering. 203. Introduction to Computer Science I (I or II; 3, 2)

36. IEEE Symposium On Foundations Of Computer Science -- 1989 pipelining computations in a tree of processors (preliminary version). In 30th Annual Symposium on Foundations of computer science , pages 184189, Research http://theory.lcs.mit.edu/~dmjones/FOCS/focs89.html

IEEE Symposium on Foundations of Computer Science 1989 Bonnie Berger and John Rompel . Simulating (log^ c n )-wise independence in NC. In 30th Annual Symposium on Foundations of Computer Science , pages 2-7, Research Triangle Park, North Carolina, 30 October-1 November 1989. IEEE. Citations. BibTeX entry Rajeev Motwani Joseph Naor , and Moni Naor . The probabilistic method yields deterministic parallel algorithms. In 30th Annual Symposium on Foundations of Computer Science , pages 8-13, Research Triangle Park, North Carolina, 30 October-1 November 1989. IEEE. Citations, etc. BibTeX entry Aviad Cohen and Avi Wigderson . Dispersers, deterministic amplification, and weak random sources (extended abstract). In 30th Annual Symposium on Foundations of Computer Science , pages 14-19, Research Triangle Park, North Carolina, 30 October-1 November 1989. IEEE. Citations. BibTeX entry Alan Siegel . On universal classes of fast high performance hash functions, their time-space tradeoff, and their applications (extended abstract). In 30th Annual Symposium on Foundations of Computer Science , pages 20-25, Research Triangle Park, North Carolina, 30 October-1 November 1989. IEEE.

37. CUA Electrical Engineering / Computer Science Suitable for computer science, mathematics, engineering, and CSC 691 Advanced computer Architecture 3 Advanced pipelining and instruction level parallelism http://engineering.cua.edu/eecs/courses/courses_csc.cfm

Navigate CUA CUA Home President Admissions CUA Athletics Campus Ministry Home@CUA Web Mail Cardinal Card Phone Book Cardinal Students Mullen Library Public Affairs Summer Sessions Alumni Message from the Chair Undergraduate Programs Graduate Programs Current Course Schedule ... Calendar Course Descriptions Computer Science (CSC) To view the complete schedule of courses for each semester, go to Cardinal Students CSC 104: Introduction to Computers I 3 Credits Intended for liberal arts majors who want an introduction to computing history, computer concepts, hardware, software, and application software such as operating systems, graphics, word processing, databases and spreadsheets. Introduces general problem-solving techniques including the concepts of step-wise refinement applied to the development of algorithms. Elementary programming in a high-level language. Not open to students who have completed MIS 104. Faculty. CSC 105: Introduction to Computers II 3 Credits CSC 113: Computer Programming 3 Credits Intended for engineering students and others who want a comprehensive introduction to fundamental programming concepts using a block-structured language. General problem-solving techniques, including the concept of step-wise refinement applied to the development of algorithms. Programming style, structure, documentation, and testing.

38. Home Page For David Lowenthal Kartek Balasubramanian, MS in computer science, August 1999. ``Efficient Support for pipelining in DistributedShared Memory Systems (Current employment http://www.cs.uga.edu/~dkl/

David Lowenthal Associate Professor and Coordinator, Experimental Systems Group Department of Computer Science The University of Georgia 415 Graduate Studies Research Center Athens, GA 30602-7404 (706) 542 9269 tel (706) 542 2911 dept (706) 542 2966 fax Email: dkl@cs.uga.edu Vita (as of May 2004) [ PDF PS Education Ph.D, 1996, Department of Computer Science, The University of Arizona Dissertation: Fine-Grain Parallelism and Run-Time Decision Making Advisor: Gregory R. Andrews M.S., 1992, Department of Computer Science, The University of Arizona B.S., 1990 Department of Computer Science, The University of California at Davis Research ([ Publication List My research centers on parallel and distributed computing and operating systems. I am currently involved in three broad areas. First, I am interested in solving fundamental parallel computing problems, such as distributing data, through system software techniques such compiler and run-time analysis. Second, more recently I have become involved in saving energy in peripheral devices (such as the network or disk) in mobile computers. We are doing this through modifications to to system software. Third, I am interested in using OS protection to solve fundamental problems in programming languages and compilers. I am involved in the following projects ( note : this is not currently up to date, but will be soon).

39. Electronics Engineering And Computer Science level knowledge in computer science and engineering. 3. computer Architecture and Digital Design. Datapath and Control; pipelining (pipelined control, hazards http://fens.sabanciuniv.edu/doktora/CS.htm

Computer Science Package Core Subjects The core subjects below test if the PhD candidate has an acceptable mastery of basic undergraduate level knowledge in computer science and engineering. The syllabi for the core subjects are given below: 1. Programming Languages and Compiler Design Topics Related to Programming Languages Describing Syntax and Semantics Names, Bindings, Type Checking, and Scopes Data Types Expressions and the Assignment Statement Statement-Level Control Structures Procedures Abstract Data Types Functional Programming Languages Logic Programming Languages Object Oriented Design Topics Related to Compiler Design Lexical processing: tokenization and lexical analysis Parsing Basics of symbol table organization, type checking and handling of user-defined types Data representation issues, memory management Runtime environment organization Code generation and optimization References Ravi Sethi, Programming Languages Concepts and Constructs nd ed., Addison-Wesley. Alfred Aho, Ravi Sethi, Jeffrey Ullman, and Compilers: Principles, Techniques, and Tools

40. UMASS Boston Department Of Computer Science University of Massachusetts, Boston computer science Colloquium. Monday, 12 March 2001, 230 PM S/2/063. pipelining LU Decomposition Automatically Transforming http://www.cs.umb.edu/News_Events/Lectures_Seminars/Colloquiums/talk03-12-01.htm

Colloquiums/Seminars University of Massachusetts, Boston Computer Science Colloquium Monday, 12 March 2001, 2:30 PM S/2/063 Pipelining LU Decomposition: Automatically Transforming Loop Computations for Distributed-Memory Machines Carl D. Offner Gem Compiler Group, Compaq Computer Corporation There are two big issues that a compiler encounters when generating code for a distributed-memory machine (or more generally, for a multi-processor machine with non-uniform memory access): 1. Distribute data over the memories of the machine, and distribute computations over the processors of the machine in such a way that the processor executing a particular computation is near the memory holding the data it accesses. 2. Schedule the execution of computations with respect to each other for maximum parallelism while respecting the semantics of the original program. One way of dealing with the first problem is to have the programmer specify an appropriate mapping of data to memories. Given this mapping, the compiler can generally do a pretty good job of mapping computations to processors so that as many computations as possible use only local, as opposed to remote, memory references.

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