In recent years, significant advances have been made in the design and evaluation of
balanced (hyper) graph partitioning algorithms. We survey trends of the past decade in …

Several manufacturers have already started to commercialize near-bank Processing-In-
Memory (PIM) architectures, after decades of research efforts. Near-bank PIM architectures …

Krylov subspace methods (KSMs) are iterative algorithms for solving large, sparse linear
systems and eigenvalue problems. Current KSMs rely on sparse matrix-vector multiply …

Several manufacturers have already started to commercialize near-bank Processing-In-
Memory (PIM) architectures, after decades of research efforts. Near-bank PIM architectures …

We investigate an efficient parallelization of the most common iterative sparse tensor
decomposition algorithms on distributed memory systems. A key operation in each iteration …

In this paper, we discuss the concept of the smart city, summarize its development, analyze
the motivation and goals of building smart cities in China, and illustrate the supporting …

We consider two-dimensional partitioning of general sparse matrices for parallel sparse
matrix-vector multiply operation. We present three hypergraph-partitioning-based methods …

Combinatorial techniques have become essential tools across the landscape of
computational science, and some of the combinatorial ideas undergirding these tools are …

We investigate hypergraph partitioning-based methods for efficient parallelization of
communicating tasks. A good partitioning method should divide the load among the …

We propose a comprehensive and generic framework to minimize multiple and different
volume-based communication cost metrics for sparse matrix dense matrix multiplication …