Accelerating communication for parallel programming models on GPU systems

Accelerating parallel particle swarm optimization via GPU

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Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

We present a review of the current best practices in parallel programming models for dense linear algebra (DLA) on heterogeneous architectures. We consider multicore CPUs, stand alone manycore coprocessors, GPUs, and combinations of these. Of interest is the evolution of the programming models for DLA libraries – in particular, the evolution from the popular LAPACK and ScaLAPACK libraries to th...

Communication Bandwidth of Parallel Programming Models on Hybrid Architectures

GPU-Vote: A Framework for Accelerating Voting Algorithms on GPU

Voting algorithms, such as histogram and Hough transforms, are frequently used algorithms in various domains, such as statistics and image processing. Algorithms in these domains may be accelerated using GPUs. Implementing voting algorithms efficiently on a GPU however is far from trivial due to irregularities and unpredictable memory accesses. Existing GPU implementations therefore target only...

Geometric Programming for Communication Systems Geometric Programming for Communication Systems

Geometric Programming (GP) is a class of nonlinear optimization withmany useful theoretical and computational properties. Over the last fewyears, GP has been used to solve a variety of problems in the analysisand design of communication systems in several ‘layers’ in the commu-nication network architecture, including information theory problems,signal processing algorithms, ...