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What Every Data Scientist Needs to Know

Sooner or later, every data science project faces an inevitable challenge: speed. Working with larger data sets leads to slower processing thereof, so you'll eventually have to think about optimizing your algorithm's run time. As most of you already know, parallelization is a necessary step of this optimization. Python offers...

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PPT – Advanced Computing Techniques & Applications PowerPoint Presentation

Advanced Computing Techniques & Applications Dr. Bo Yuan E-mail: Profile • Lecturer: Dr. Bo Yuan • Contact • Phone: 2603 6067 • E-mail: • Room: F-301B • Time: 10:25 am – 12:00pm, Friday • Venue: CI-208 • Teaching Assistant • Mr. Shiquan YangWe will study ... • MPI...

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Deep Learning and Parallel Computing Environment for Bioengineering Systems

Dr. Arun Kumar Sangaiah received his Master of Engineering from Anna University and Ph.D. from VIT University, India. He is currently as a Professor at the School of Computing Science and Engineering, VIT University, Vellore, India. His areas of research interest include machine learning, Internet of Things, Sustainable Computing. Moreover,...

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Parallel Programming with Dask in Python

Course Description Python is now well established as a major platform for data analysis and data science. For many data scientists, the largest limitation of Python is that all data must fit into the resident memory of the available workstation. Further, traditionally, Python has only been able to utilize one...

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Ever Wondered What Computers are Going to Be Like in the Future?

Have you thought about the future of computing? Have you imagined what computers in the future are going to be like? Let’s try to find out. Fifth Generation Computer Systems Project (FGCS) In 1982, the Ministry of International Trade and Industry of Japan started working on creating a computer using...

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Parallel Processing for Artificial Intelligence 1, Volume 14

Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic,...

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Given a web graph, compute the page rank of each node. Use MPI – vineethshankar/pagerank. Introduction to Parallel Computing, 2nd Edition. Ananth Grama. George Karypis, Purdue University. Ananth Grama, Purdue University. Vipin Kumar, University of. Introducation to Parallel Computing is a complete end-to-end source of information on almost all aspects...

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Python Parallel Computing (in 60 Seconds or less) –

Basically, parallel computing allows you to carry out many calculations at the same time, thus reducing the amount of time it takes to run your program to completion. I know, this sounds fairly vague and complicated somehow…but bear with me for the next 50 seconds or so. Here’s an end-to-end...

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Parallel Computing Course | Engineering Courses

CS52500 Credit Hours: 3 Learning Objective: Parallel Computing deals with emerging trends in the use of large scale computing platforms ranging from desktop multicore processors, tightly coupled SMPs, message passing platforms, and state-of-the-art virtualized cloud computing environments.Description: Parallel computing for science and engineering applications: parallel programming and performance evaluation, parallel...

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Overview, Definitions, Examples and Explanations

What is Parallel Computing?A Not Too Serious Explanation. Before I explain parallel computing, it's important to understand that You can run, but you can't hide. I'll come back to this later.   Suppose you have a lot of work to be done, and want to get it done much faster,...

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