We investigate runtime strategies for data-intensive applications that involve generalized reductions on large, distributed datasets. Our set of strategies includes replicated fi...
We propose and study algorithms for computing minimal models, stable models and answer sets of 2- and 3-CNF theories, and normal and disjunctive 2- and 3-programs. We are especiall...
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to perform poorly on modern processors, largely because of its high ratio of memory op...
Many years of CMOS technology scaling have resulted in increased power densities and higher core temperatures. Power and temperature concerns are now considered to be a primary cha...
Daniel C. Vanderster, Amirali Baniasadi, Nikitas J...
We describe a new subdivision method to efficiently compute the topology and the arrangement of implicit planar curves. We emphasize that the output topology and arrangement are g...