A new set of benchmarks has been developed for the performance evaluation of highly
parallel supercomputers. These benchmarks consist of five ‘parallel kernel” benchmarks and …

The problem of computing a small vertex separator in a graph arises in the context of computing
a good ordering for the parallel factorization of sparse, symmetric matrices. An algebraic …

Current nonnegative matrix factorization (NMF) deals with X = FG T type. We provide a
systematic analysis and extensions of NMF to the symmetric W = HH T , and the weighted W = …

Many large-scale computational problems are based on unstructured computational domains.
Primary examples are unstructured grid calculations based on finite volume methods in …

An important application of graph partitioning is data clustering using a graph model - the
pairwise similarities between all data objects form a weighted graph adjacency matrix that …

If problems involving unstructured meshes are to be solved efficiently on distributed‐memory
parallel computers, the meshes must be partitioned and distributed across processors in a …

An “industrial strength” algorithm for solving sparse symmetric generalized eigenproblems
is described. The algorithm has its foundations in known techniques in solving sparse …

The Lanczos algorithm is becoming accepted as a powerful tool for finding the eigenvalues
and for solving linear systems of equations. Any practical implementation of the algorithm …

In the quest for cognitive computing, we have built a massively parallel cortical simulator, C2,
that incorporates a number of innovations in computation, memory, and communication. …

The most commonly used p-way partitioning method is recursive bisection (RB). It first divides
a graph or a mesh into two equal-sized pieces, by a "good" bisection algorithm, and then …