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@ -56,7 +56,8 @@ Courses
- [CSCI 493.75](http://compsci.hunter.cuny.edu/~sweiss/course_materials/csci493.65/csci493.65_spr14.php) **Parallel Computing** *CUNY Hunter College*
- The course is an introduction to parallel algorithms and parallel programming in C and C++, using the Message Passing Interface (MPI) and the OpenMP application programming interface. It also includes a brief introduction to parallel architectures and interconnection networks. It is both theoretical and practical, including material on design methodology, performance analysis, and mathematical concepts, as well as details on programming using MPI and OpenMP.
- [CS 107](http://web.stanford.edu/class/cs107/index.html) **Computer Organization & Systems** *Stanford University*
- CS107 is the third course in Stanford's introductory programming sequence. The course will work from the C programming language down to the microprocessor to de-mystify the machine. With a complete understanding of how computer systems execute programs and manipulate data, you will become a more effective programmer, especially in dealing with issues of debugging, performance, portability, and robustness. Topics covered include: the C programming language, data representation, machine-level code, computer arithmetic, elements of code compilation, optimization of memory and runtime performance, and memory organization and management.
- CS107 is the third course in Stanford's introductory programming sequence. The course will work from the C programming language down to the microprocessor to de-mystify the machine. With a complete understanding of how computer systems execute programs and manipulate data, you will become a more effective programmer, especially in dealing with issues of debugging, performance, portability, and robustness.
- [Lecture Videos](https://www.youtube.com/playlist?list=PL08D9FA018A965057&spfreload=10)
- [Assignments](http://web.stanford.edu/class/cs107/assignments.html)
- [ECE 459](http://patricklam.ca/p4p/) **Programming for Performance** *University of Waterloo*
- Learn techniques for profiling, rearchitecting, and implementing software systems that can handle industrial-sized inputs, and to design and build critical software infrastructure. Learn performance optimization through parallelization, multithreading, async I/O, vectorization and GPU programming, and distributed computing.