Performance and energy are the two most important objectives for optimization on modern
parallel platforms. In this article, we show that moving from single-objective optimization for …

Modern homogeneous parallel platforms are composed of tightly integrated multicore CPUs.
This tight integration has resulted in the cores contending for various shared on-chip …

Focusing on algorithms for distributed-memory parallel architectures, Parallel Algorithms
presents a rigorous yet accessible treatment of theoretical models of parallel computation …

Modern HPC platforms have become highly heterogeneous owing to tight integration of
multicore CPUs and accelerators (such as Graphics Processing Units, Intel Xeon Phis, or …

In this paper, we address the problem of optimal distribution of computational tasks on a
network of heterogeneous computers when one or more tasks do not fit into the main …

This paper is an overview the ongoing academic research, development, and uses of
heterogeneous parallel and distributed computing. This work is placed in the context of …

We revisit the master-slave tasking paradigm in the context of heterogeneous processors.
We assume that communications are handled by a bus and, therefore, at most one …

An analytical overview of the state of the art, open problems, and future trends in
heterogeneous parallel and distributed computing This book provides an overview of the …

In this paper we deal with two geometric problems arising from heterogeneous parallel
computing: how to partition the unit square into p rectangles of given area s 1, s 2,..., sp …

Matrix multiplication (MM) is one of the core problems in the high performance computing
domain and its efficiency impacts performances of almost all matrix problems. The high …