We propose COSMA: a parallel matrix-matrix multiplication algorithm that is near
communication-optimal for all combinations of matrix dimensions, processor counts, and …

Matrix factorizations are among the most important building blocks of scientific computing.
However, state-of-the-art libraries are not communication-optimal, underutilizing current …

Determining I/O lower bounds is a crucial step in obtaining communication-efficient parallel
algorithms, both across the memory hierarchy and between processors. Current approaches …

Currently, a major bottleneck for several scientific computations is communication, both
communication between different processors, so-called horizontal communication, and …

Technology trends will cause data movement to account for the majority of energy
expenditure and execution time on emerging computers. Therefore, computational …

Multilinear algebra kernel performance on modern massively-parallel systems is determined
mainly by data movement. However, deriving data movement-optimal distributed schedules …

A tight lower bound for required I/O when computing an ordinary matrix-matrix multiplication
on a processor with two layers of memory is established. Prior work obtained weaker lower …

Dense linear algebra kernels are fundamental components of many scientific computing
applications. In this work we present a novel method of deriving parallel I/O lower bounds for …

Technology trends are making the cost of data movement increasingly dominant, both in
terms of energy and time, over the cost of performing arithmetic operations in computer …

Red-blue pebble games model the computation cost of a two-level memory hierarchy. We
present various hardness results in different red-blue pebbling variants, with a focus on the …