Realistic workloads are essential in evaluating middleware for computational grids. One important component is the raw grid itself: a network topology graph annotated with the har...
We investigate runtime strategies for data-intensive applications that involve generalized reductions on large, distributed datasets. Our set of strategies includes replicated fi...
We investigate the use of the multistep successive preconditioning strategies (MSP) to construct a class of parallel multilevel sparse approximate inverse (SAI) preconditioners. W...
Abstract. A novel framework for the design and analysis of energy-aware algorithms is presented, centered around a deterministic Bit-level (Boltzmann) Random Access Machine or BRAM...
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...