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00189162981000. Wireless Microphone Systems 5 Wireless Microphone Systems range from simple to sophisticated. But they all include various combinations of Transmitters: Handheld Microphone Transmitter  Hardware Parallelism. Computing: execute instructions that operate on data.. Flynn’s . taxonomy (Michael Flynn, 1967) classifies computer architectures based on the number of instructions that can be executed and how they operate on data.. Performance Theory - 1. Parallel Computing. CIS . 410/. 510. Department of Computer and Information Science. Outline. Performance scalability. Analytical performance measures. Amdahl. ’. s. law and Gustafson-. Improving Computer Performance. What performance translates into:. Time taken to do computation. Improving performance . → reducing time taken. What key benefits improving performance can bring:. Can solve “now-computationally-attainable” problems in . 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 . Software Architecture. Describe how the various software components are to be organized and how they should interact.. It describe the organization and interaction of software components.. System Architecture. Thread Level Parallelism. Chapter 4, Appendix H. CS448. 2. The Greed for Speed. Two general approaches to making computers faster. Faster uniprocessor. All the techniques we’ve been looking at so far, plus others…. By:. Atena. . Daneshmandi. Outline. Introduction. Typology of Parallel . Tasks. Task . Graphs. A Deterministic module . A Deterministic module by Gantt . Chart. C# Example(Three Tasks in Parallel). Complexity . Performance. The speed at which a computer executes a program is affected by . the design of its hardware – processor speed, clock rate, memory access time etc.. the machine language (ML) instructions – the instruction format, instruction set etc. Dr Susan Cartwright. Dept of Physics and Astronomy. University of Sheffield. Parallel Universes. Are you unique?. Could there be another “you” differing only in what you had for breakfast this morning?. Evangelia A. Sitaridi, Kenneth A. Ross. Columbia University. DaMoN Workshop. 21st May 2012. . Introduction (1/2). Earlier GPU implementations of data processing operators have resulted in significant speedups. CUDA Lecture 3. Parallel Architectures and Performance Analysis. Conventional Von Neumann architecture consists of a processor executing a program stored in a (main) memory:. Each main memory location located by its address. Addresses start at zero and extend to 2. Recall: Microprocessors are classified by how memory is organized. Tightly-coupled multiprocessor systems use the same memory. They are also referred to as . shared memory multiprocessors. .. The processors do not necessarily have to share the same block of physical memory: . Quarter: Summer 2017. CSE 373: Data Structures and Algorithms. Lecture . 23: Parallelism: Map, Reduce, Analysis. Today. More on parallelism. Map & Reduce . Analysis of Efficiency. Reminder: . C. ome visit my office hours to pick up midterm.