Accelerated Computing for Machine Learning

3 Credits

Introduction to hardware architectures and parallel computing systems that facilitate high speed machine learning. Graphics processing units (GPUs), hardware architecture of parallel computers, memory allocation and data parallelism, multidimensional kernel configuration, kernel-based parallel programming, principles and patterns of parallel algorithms, application of parallel computing to machine learning. Students may not obtain credit for more than one of DSCI 421 , ECE 303 and ECE 403 . Prerequisites: DSCI 310 and DSCI 321