PPT-Introduction to Parallel Processing

Dr Guy Tel Zur Lecture 10 Agenda Administration Final presentations Demos Theory Next week plan Home assignment 4 last Final Projects Next Sunday Groups 11 6 will present Next Monday Groups 1. 1 Parallel Processing A parallel processing system is able to perform concurrent data processing to achieve faster execution time The system may have two or more ALUs and be able to execute two or more instructions at the same time Also the system m 1 2 Code within a parallel region is executed by all threads. Fortran: !$OMP PARALLEL!$OMP END PARALLEL C/C++: #pragmaompparallel 2 #pragmaompparallel Often useful to find out number of threads b CUDA Lecture 1. Introduction to Massively Parallel Computing. A quiet revolution and potential buildup. Computation: TFLOPs . vs. . 100 GFLOPs. CPU in every PC – massive volume and potential impact. STUDY AND IMPLEMENTATION OF POPULAR PARALLELING TECHNIQUES APPLIED TO HEVC. Unde. r the guidance of. Dr. K. R. . Rao. By:. Karthik Suresh . (1000880819). Overview. HEVC. Improvements . Need for parallel processing. Thomas Sangild Sørensen. Course overview. Department of Computer Science. Introduction . to computer graphics and image processing (Q1). Data-parallel computing (Q1). Advanced image processing (Q2). Programming & Cluster Computing. Applications and. Types of Parallelism. Joshua Alexander, U Oklahoma. Ivan . Babic. , Earlham College. Michial. Green, Contra Costa College. Mobeen. . Ludin. , Earlham College. Anthony Waterman. Topics to Discuss. Are online games . c. onceptually. . p. arallel?. What portions of a game benefit from parallelization?. Graphics Processing Units (GPUs) . General-Purpose . C. omputing . For many years, R had a reputation for being slow, unable to process large datasets. This was true until c2012 when its compiler caw switched from `parse tree’ to `byte code’. Its speed is now similar to Python, Java, . Pipelining. Instruction Pipeline. Pipeline Hazards and their solution. Array and Vector Processing. Pipelining and Vector Processing. Parallel Processing. It refers to techniques that are used to provide simultaneous data processing.. Mohammadhossein . Behgam. Agenda. Need for parallelism. Challenges. Image processing algorithms. Data handling & Load Balancing. Communication cost & performance. What is the problem?. Image Processing applications can be very computationally demanding due to:. Inside a Processor. Chip in Package. Circuits. Primarily Crystalline Silicon. 1 mm – 25 mm on a side. 100 million to billions of transistors. current “feature size” . (process). ~ 14 nanometers. Division of Special Education 1500 Highway 36 West Roseville, Minnesota 55113-4266 Introduction to Auditory Processing Disorders 2 APD Work Team Regional Low Incidence Facilitator/State Other We will Study …. Concurrency . Parallelism. Distributed computing. Evaluation. Assignments 40%, . Minor-1 15%, . Minor-2 15%, . Major 30%. Plagiarism is unacceptable. Offenders will be . penalized by a failing. Introduction. Papadakis Harris. Dept. of Engineering Informatics. ΤΕΙ . of Crete. Distributed Systems. - . Contents. Definition. Parallel. . Processing. Distributed . Computin. Clusters. Examples.