NSF/TCPP Curriculum Planning Workshop

Joseph JaJaInstitute for Advanced Computer StudiesDepartment of Electrical and Computer EngineeringUniversity 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

2February 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

3February 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 Advanced Course in Parallel Models and AlgorithmsModels and Algorithms

February 5-6, 2010 4