The Past, Present and Future of High Performance Computing

In this overview paper we start by looking at the birth of what is called ``High Performance Computing\u27\u27 today. It all began over 30 years ago when the Cray 1 and CDC Cyber 205 ``supercomputers\u27\u27 were introduced. This had a huge impact on scientific computing. A very turbulent time at both the hardware and software level was to follow. Eventually the situation stabilized, but not for long. Today, there are two different trends in hardware architectures and have created a bifurcation in the market. On one hand the GPGPU quickly found a place in the marketplace, but is still the domain of the expert. In contrast to this, multicore processors make hardware parallelism available to the masses. Each have their own set of issues to deal with. In the last section we make an attempt to look into the future, but this is of course a highly personal opinion

The lid method for exhaustive exploration of metastable states of complex systems

The `lid' algorithm performs an exhaustive exploration of neighborhoods of local energy minima of energy landscapes. This paper describes an implementation of the algorithm, including issues of parallel performance and scalability. To illustrate the versatility of the approach and to stress the common features present in landscapes of quite different systems, we present selected results for 1) a spin glass, 2) a ferromagnet, 3) a covalent network model for glassy systems, and 4) a polymer. The exponential nature of the local density of states found in these systems and its relation to the ordering transition is briefly commented upon.Comment: RevTeX, 11 pages, 1 figur

Using OpenMP: the next step : affinity, accelerators, tasking, and SIMD

A guide to the most recent, advanced features of the widely used OpenMP parallel programming model, with coverage of major features in OpenMP 4.5