Mustafa U. Torun, PhD candidate in the department of electrical and computer engineering, recently gave two oral presentations on papers published in the IEEE CISS 2012 conference in Princeton, NJ (http://ee-ciss.princeton.edu/schedule.php). The papers discussed are “Novel GPU Implementation of Jacobi Algorithm for Karhunen-Loeve Transform of Dense Matrices,” and “On Toeplitz Approximation to Empirical Correlation Matrix of Financial Asset Returns.”  The first paper focuses on increasing the speed of the numerical implementation of a very commonly used tool in science.  That is principal component analysis (PCA). The speed of the implementation of the PCA on a general purpose graphical processing unit (GPGPU) was improved by the authors.  GPGPU's are the mainstream parallel computing hardware today.