SUMMARY In 1907, Erhard Schmidt published a paper in which he introduced an
orthogonalization algorithm that has since become known as the classical Gram‐Schmidt …

We highlight the trends leading to the increased appeal of using hybrid multicore+ GPU
systems for high performance computing. We present a set of techniques that can be used to …

We present parallel and sequential dense QR factorization algorithms that are both optimal
(up to polylogarithmic factors) in the amount of communication they perform and just as …

Mechanical complexity, wide dimensions, and big data volume may hamper the
implementation of Internet of Things (IoT)-enabled structural health monitoring (SHM) …

This paper presents a unified communication optimization framework for sparse triangular
solve (SpTRSV) algorithms on CPU and GPU clusters. The framework builds upon a 3D …

We introduce a dynamically weighted Halley (DWH) iteration for computing the polar
decomposition of a matrix, and we prove that the new method is globally and asymptotically …

Designing communication-avoiding algorithms is crucial for high performance computing on
a large-scale parallel system. The TSQR algorithm is a communication-avoiding algorithm …

This paper presents a heterogeneous CPU-GPU implementation for a sparse iterative
eigensolver–the Locally Optimal Block Preconditioned Conjugate Gradient (LOBPCG). For …

Sparse matrix factorization involves a mix of regular and irregular computation, which is a
particular challenge when trying to obtain high-performance on the highly parallel general …

In this paper we unveil some performance and energy efficiency frontiers for sparse
computations on GPU-based supercomputers. We compare the resource efficiency of …