Parallel Genetic Algorithms for Inverse Boggle Solving
Parallel Implementation of Sequential Minimal Optimization (SMO) Algorithm and Model Selection for Support Vector Machines
Parallel Landsat Data Processing
A Parallel Hybrid Framework for Graph Processing
Patch Matching for Image Segmentation
Parallel Graph-based Semi-supervised Learning
Load Balancing in Distributed Computing
Auto-tuning for scalable parallel 3-D FFT
Parallel implementation of Machine Learning algorithms using Spark/Hadoop
CPU-GPU Dynamic Approximation for Parallel Applications
Algebraic Multigrid with OpenMP, OpenACC and MPI
Developing Parallel Algorithms for Creating and Solving Sudoku Puzzle
Distributed Learning for Deep Neural Networks
Machine Learning Algorithms in Spark
Application performance studies across one or more parallel machines - e.g. satellite data processing, parallel search, computer vision algorithms, bioinformatics
Application performance studies on GPUs (1 or more machines)
Reproduce results from a paper, extend to current systems
E.g., CPU vs. GPU paper (pick a small number of application kernels)
Debunking paper
Or one of your own design