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NSF/TCPP Curriculum Planning Workshop
Joseph JaJaInstitute for Advanced Computer StudiesDepartment of Electrical and Computer EngineeringUniversity of Maryland
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• 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
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• 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
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• 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