ࡱ> XZW (bjbjWW DP55vv8TYL%c%e%e%e%e%e%e%$'*%%%###Fc%#c%##V##T#$Ew# O%%0%#0<+E<+##<+# r#\%%B%<+v :  San Jose State University CS 159: Parallel Processing Spring 2014 Course Syllabus Description: A combination hardware architecture and software development class focused on multi-threaded, parallel processing algorithms and techniques. Overview of high-performance parallel processing hardware architectures ranging from on-chip Instruction-Level Parallelism to multi-core microprocessor chips to large distributed supercomputing systems including Clusters, Grids, and Clouds. Discussion and hands-on exercises using a sample of various parallel programming paradigms and languages such as Pthreads, MPI, OpenMP, Map-Reduce Hadoop, CUDA and OpenCL. The class focus will be on understanding the fundamental concepts associated with the design and analysis of parallel processing systems. Special emphasis will be placed on avoiding the unique non-deterministic software defects that can arise in parallel processing systems including race conditions and deadlocks. The class will also provide an overview of current parallel software development toolkits including debuggers and performance profilers. A term project and presentation on a student-selected topic is required. Meeting Time: Section 1: MW 6:00pm 7:15pm MH222 Prerequisites: CS 146 (CS 147 and CS 149 highly recommended), or instructor consent. Instructor: Robert K. Chun (Course Web Site: www.sjsu.edu/people/robert.chun) Contact Info: EMAIL: ProfessorChun@gmail.com, PHONE: (408) 924-5137, OFFICE: MH 413 Office Hours: MW 4:30pm 5:30pm Textbooks: Required: Multi-Core Programming, Shameem Akhter and Jason Roberts, 2006, Intel Press, ISBN 0-9764832-4-6 Required: Using OpenMP, Barbara Chapman and Gabriele Jost, 2008, MIT Press, ISBN 978-0-262-53302-7. Optional: Scientific Parallel Computing, Ridgway Scott and Terry Clark, 2005, Princeton University Press, ISBN 0-691-11935-X Grading: Grading consists of two midterms, one final, and a set of projects (consisting of a combination of written problems and programming assignments) weighted as follows. Grading is based on a class curve. All assignments must be completed by the student on the due date specified to receive credit for the class. Late assignments or exams are not accepted. All students must uphold academic integrity per university policy detailed at http://www2.sjsu.edu/senate/f88-10.htm 15% Midterm Exam 1 Week 6 (Approximate) 15% Midterm Exam 2 Week 12 (Approximate) 20% HW and Programming Projects Due as announced in class 20% Term Project Due as announced in class 30% Final Exam Wed May 21, 2014 5:15pm-7:30pm Student Learning Outcomes: Upon successful completion of this course, students should be able to understand: The Technical and Business motivation and need for current state-of-the-art computing systems to incorporate Parallel Processing into the Hardware and Software Subsystems. The Micro-Hardware Architectural Evolutionary Trends leading to on-chip Instruction-Level Parallelism, and Pipelining, SuperScalar, Multi-Function Unit Parallel Processing. The Macro-Hardware Architectural Evolutionary Trends leading to Parallel Processing including Flynns Taxonomy and the recent progression in high-performance supercomputing architectures from Clusters to Grids and to Clouds. Data dependency analysis and hazards which, along with Amdahls Law, limits the amount of practical speedup and scalability that can be achieved with Parallel Processing. Design and Analysis Techniques for Parallel Processing Systems including the identification of data vs. task partitioning in algorithms and applications. The Different Models for implementing parallelism in Computing Systems such as shared memory and message passing. The software challenges associated with Parallel Processing including the difference between concurrent vs. parallel execution models, deadlocks and race conditions. A sample of current parallel programming paradigms and languages and be able to write parallel programs using them. Schedule (Tentative): LectureTopic 1 - 3 Introduction, Motivation and Overview of Parallel Processing with an emphasis on the Micro- and Macro-Hardware Evolutionary Trends leading to Parallelism and the Software Challenges of Parallelism 4 - 6 Hardware Parallel Processing including pipelining and Instruction-Level Parallelism (ILP) 7 - 8 Multi-Function Parallelism in Hardware 9 Data dependency analysis and control hazard analysis including RAW, WAR, WAW, and Branch Prediction 10 Limitations of Hardware-based, Software-transparent ILP 11 - 17 Software Challenges of Parallel Processing including Concurrent vs. Parallel Execution Models, Amdahls Law, Deadlocks, Race Conditions, Semaphores 18 Models of Parallelism such as Shared Memory, Message Passing 19 - 25 Parallel Programming Paradigms including Unix Process Forking, PVM, MPI, OpenMP, CUDA, OpenCL, Hadoop Map-Reduce, GPGPU computing, Toolsets for Parallel Program Software Development and Debugging 26 28 Term Project Presentations General University Policies DISABILITIES: If you need course adaptations or accommodations because of a disability, or if you need special arrangements in case the building must be evacuated, please inform the instructor as soon as possible. Presidential Directive 97-03 requires that students with disabilities register with DRC to establish a record of their disability. ACADEMIC INTEGRITY: Academic integrity is essential to the mission of San Jos State University. As such, students are expected to perform their own work (except when collaboration is expressly permitted by the course instructor) without the use of any outside resources. Students are not permitted to use old tests or quizzes when preparing for exams, nor may they consult with students who have already taken the exam. When practiced, academic integrity ensures that all students are fairly graded. We all share the obligation to maintain an environment which practices academic integrity. Violations to the Academic Integrity Policy undermine the educational process and will not be tolerated. It also demonstrates a lack of respect for oneself, fellow students and the course instructor, and can ruin the universitys reputation and the value of the degrees it offers. Violators of the Academic Integrity Policy will be subject to failing this course and being reported to the Office of Judicial Affairs for disciplinary action which could result in suspension or expulsion from San Jos State University. CHEATING: At 91, cheating is the act of obtaining or attempting to obtain credit for academic work through the use of any dishonest, deceptive, or fraudulent means. Cheating at 91 includes but is not limited to: Copying in part or in whole, from anothers test or other evaluation instrument; Submitting work previously graded in another course unless this has been approved by the course instructor or by departmental policy. Submitting work simultaneously presented in two courses, unless this has been approved by both course instructors or by departmental policy. Altering or interfering with grading or grading instructions; Sitting for an examination by a surrogate, or as a surrogate; any other act committed by a student in the course of his or her academic work which defrauds or misrepresents, including aiding or abetting in any of the actions defined above. PLAGIARISM: At 91 plagiarism is the act of representing the work of another as ones own (without giving appropriate credit) regardless of how that work was obtained, and submitting it to fulfill academic requirements. Plagiarism at 91 includes but is not limited to: The act of incorporating the ideas, words, sentences, paragraphs, or parts thereof, or the specific substances of anothers work, without giving appropriate credit, and representing the product as ones own work; and representing anothers artistic/scholarly works such as musical compositions, computer programs, photographs, painting, drawing, sculptures, or similar works as ones own. 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