Parallel and Distributed Computing

Systems, architectures, algorithms, programming models, languages and software tools. Topics covered include parallelization and distribution models (MPI, Map-Reduce, etc.); Parallel architectures; Cluster and parallel and distributed computing systems, distributed and parallel algorithms, data structures and programming methodologies; applications; And performance analysis.

  1. Georg Hager and Gerhard Wellein. Introduction to High-Performance Computing for Scientists and Engineers. CRC Press, Boca Raton, FL, 1 edition, July 2010.
  2. Victor Eijkhout. Introduction to High-Performance Scientific Computing. lulu.com, Raleigh, N.C., January 2015.
  3. K. G. Srinivasa and Anil Kumar Muppalla. Guide to High-Performance Distributed Computing: Case Studies with Hadoop, Scalding, and Spark. Springer, New York, NY, 2015 edition, February 2015.
  4. Mahmoud Parsian. Data Algorithms: Recipes for Scaling Up with Hadoop and Spark. O’Reilly Media, Sebastopol, 1 edition, July 2015.
  5. Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills. Advanced Analytics with Spark: Patterns for Learning from Data at Scale. O’Reilly Media, Beijing, 1 edition, April 2015.
  6. Pethuru Raj, Anupama Raman, Dhivya Nagaraj, and Siddhartha Duggirala. High-Performance Big-Data Analytics: Computing Systems and Approaches. Springer, S.l., 2015 edition, August 2015.
  7.  Vijay Srinivas Agneeswaran. Big Data Analytics Beyond Hadoop: Real-Time Applications with Storm, Spark, and More Hadoop Alternatives. Pearson FT Press, Upper Saddle River, 1 edition, May 2014.

This course is regularly offered once a year at CEFET/RJ (PPCIC).

Slides and schedule available at Moodle.

 

About Eduardo Ogasawara
I am a Professor of the Computer Science Department of the Federal Center for Technological Education of Rio de Janeiro (CEFET / RJ) since 2010. I hold a PhD in Systems Engineering and Computer Science at COPPE / UFRJ. Between 2000 and 2007 I worked in the Information Technology (IT) field where I acquired extensive experience in workflows and project management. I have solid background in the Databases and my primary interest is Data Science. He currently studies space-time series, parallel and distributed processing, and data preprocessing methods. I am a member of the IEEE, ACM, INNS, and SBC. Throughout my career I have been presenting consistent number of published articles and projects approved by the funding agencies, such as CNPq and FAPERJ. I am also reviewer of several international journals, such as VLDB Journal, IEEE Transactions on Service Computing and The Journal of Systems and Software. Currently, I am heading the Post-Graduate Program in Computer Science (PPCIC) of CEFET / RJ.

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