Data sets in large applications are often too massive to fit completely inside the computers
internal memory. The resulting input/output communication (or I/O) between fast internal …

Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer
time resolution. The resulting data rates require reproducible analysis pipelines that are …

Current systems for graph computation require a distributed computing cluster to handle
very large real-world problems, such as analysis on social networks or the web graph. While …

This handbook provides an up-to-date compendium of fundamental computer science
topics, techniques, and applications. Along with updating and revising many of the existing …

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

We present lower bounds on the amount of communication that matrix multiplication
algorithms must perform on a distributed-memory parallel computer. We denote the number …

This book is intended for researchers and practitioners as a foundation for modern parallel
computing with several of its important parallel applications, and also for students as a basic …

Data sets in large applications are often too massive to fit completely inside the computer's
internal memory. The resulting input/output communication (or I/O) between fast internal …

We describe a hierarchical approach to improving the efficiency of gradient-domain
compositing, a technique that constructs seamless composites by combining the gradients of …

With the emergence of thread-level parallelism as the primary means for continued
performance improvement, the programmability issue has reemerged as an obstacle to the …