NSF/TCPP Curriculum Planning Workshop Joseph JaJa Institute for Advanced Computer Studies Department of Electrical and Computer Engineering University of Maryland

Machine Learning and Data Mining – graduate and undergraduate VLSI Architectures – graduate Data Structures and Algorithms – graduate Probability – undergraduate Parallel Algorithms - graduate Recent Teaching Experience 2 February 5-6, 2010

Techniques for mapping algorithms onto parallel architectures with signal processing computations as the main driving applications. – Pipelining and parallelism; retiming and loop unrolling; mapping algorithms into systolic architectures; etc. –Target architectures: DSPs; VLIW; FPGAs; GPUs;multicore; etc. Overview of VLSI Architectures 3 February 5-6, 2010

Data Parallelism –Model: parallel time and total work –Examples from: image processing; prefix sums; matrix computations; FFT; graph algorithms etc. Multithreading –Shared Memory Model: synchronization costs –Examples: prefix sums; matrix computations; FFT; etc. Distributed Memory –Model: message passing; communication costs –Broadcast, reduce, all-to-all operations –Examples: matrix computations; FFT; sorting; etc. Advanced Course in Parallel Models and Algorithms February 5-6,