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 address the issue of implementing matrix multiplication on heterogeneous platforms. We
target two different classes of heterogeneous computing resources: heterogeneous …

Sparse matrix operations dominate the performance of many scientific and engineering
applications. In particular, iterative methods are commonly used in algorithms for linear …

We present a new approach to utilizing all CPU cores and all GPUs on heterogeneous
multicore and multi-GPU systems to support dense matrix computations efficiently. The main …

The authors study the implementation of dense linear algebra kernels, such as matrix
multiplication or linear system solvers, on heterogeneous networks of workstations. The …

Iterative stencil loops are used in scientific programs to implement relaxation methods for
numerical simulation and signal processing. Such loops iteratively modify the same array …

Scheduling problems are already difficult on traditional parallel machines, and they become
extremely challenging on heterogeneous clusters. In this paper, we deal with the problem of …

GPU-based heterogeneous clusters continue to draw attention from vendors and HPC users
due to their high energy efficiency and much improved single-node computational …

This paper discusses algorithmic issues when computing with a heterogeneous network of
work-stations (the typical poor man's parallel computer). Dealing with processors of different …

Tiling is a known problem especially in the field of computational geometry and its related
engineering branches. In fact, a tile is a set of points in the Cartesian space. The goal is to …