Current high-performance computer systems used for scientific computing typically combine
shared memory computational nodes in a distributed memory environment. Extracting high …

On modern GPU clusters, the role of the CPUs is often restricted to controlling the GPUs and
handling MPI communication. The unused computing power of the CPUs, however, can be …

In the state-of-the-art parallel programming approaches OpenCL and CUDA, so-called host
code is required for program's execution. Efficiently implementing host code is often a …

This paper describes the design and implementation of a suit of static analyses and code
generation techniques to annotate programs with OpenMP pragmas for task parallelism …

Cloud computing is inherently service-oriented: cloud applications are delivered to
consumers as services via the Internet. Therefore, these applications can potentially benefit …

Dynamic programming is an important technique widely used in many scientific applications.
Due to the massive volume of applications' data in practice, parallel and distributed DP is a …

We develop a modeling and simulation framework capable of massively parallel simulation
of multicellular systems with spatially resolved stochastic kinetics in individual cells. By the …

For the first decades of the semiconductor industry, processor chips had a single CPU core.
Processor architecture evolved gradually to include many features that extracted …

This thesis presents the development of a new eigensolver for the use in massively parallel
systems. Current implementations lack in both, parallel and sequential efficiency on modern …

The authors present a performance study of a switching system being designed for use in
the high-performance switching system (HPSS) project at the Lawrence Livermore National …