As silicon technology enters sub-20nm nodes, new materials, structures and processes are
being introduced in order to continue with the advantages of dimensional scaling, eg, 3D …

The traditional metric for the efficiency of a numerical algorithm has been the number of
arithmetic operations it performs. Technological trends have long been reducing the time to …

The present book provides an introduction to using space-filling curves (SFC) as tools in
scientific computing. Special focus is laid on the representation of SFC and on resulting …

Parallel programming on SMP and multi-core architectures is hard. In this paper we present
a programming model for those environments based on automatic function level parallelism …

Communication-optimal algorithms are known for square matrix multiplication. Here, we
obtain the first communication-optimal algorithm for all dimensions of rectangular matrices …

We investigate how graph partitioning adversely affects the performance of graph analytics.
We demonstrate that graph partitioning induces extra work during graph traversal and that …

We discuss an algorithm that optimizes the driving style of a train. The objective is to
minimize the electrical energy used for traction subject to constraints such as the travel time …

We discuss the high-performance parallel implementation and execution of dense linear
algebra matrix operations on SMP architectures, with an eye towards multi-core processors …

The Gaussian Elimination Paradigm (GEP) was introduced by the authors in [6] to represent
the triply-nested loop computation that occurs in several important algorithms including …

Scientific applications face serious performance challenges on multicore processors, one of
which is caused by access contention in last level shared caches from multiple running …