We present new parallel algorithms that solve continuous-state partially observable Markov decision process (POMDP) problems using the GPU (gPOMDP) and a hybrid of the GPU and CPU (hPOMDP). We choose the Monte Carlo value iteration (MCVI) method as our base algorithm and parallelize this algorithm using the multi-level parallel formulation of MCVI. For each parallel level, we propose efficient ...

Gabor-domain optical coherence microscopy (GD-OCM) is a volumetric high-resolution technique capable of acquiring three-dimensional (3-D) skin images with histological resolution. Real-time image processing is needed to enable GD-OCM imaging in a clinical setting. We present a parallelized and scalable multi-graphics processing unit (GPU) computing framework for real-time GD-OCM image processin...

Graphics Processing Units (GPUs) are being heavily used in various graphics and non-graphics applications. Many practical problems in computing can be represented as graphs to arrive at a particular solution. These graphs contains very large number, up to millions pairs of vertices and edges. In this paper, we present performance analysis of Dijkstra’s single source shortest path algorithm over...

Ultrasound simulations are a type of application that are both computationally and communicatively intensive. With better performance, implementations of these can be used in designing new ultrasound probes, developing better signal processing techniques, training new ultrasonographers, in treatment planning and many other uses [12]. The pseudo-spectral technique can be used effectively to expr...

Multi-start algorithms are a common and effective tool for metaheuristic searches. In this paper we amplify multi-start capabilities by employing the parallel processing power of the graphics processer unit (GPU) to quickly generate a diverse starting set of solutions for the Unconstrained Binary Quadratic Optimization Problem which are evaluated and used to implement screening methods to selec...

For systems including multi sensors, it is necessary to apply complex signal processing algorithms in real time with an acceptable performance to achieve the system goals. Depending on the nature of the algorithms to be implemented (suitable for parallel or sequential processing), implementation of the algorithms on the appropriate hardware, for instance graphical processing units (GPU) or cent...

In this article, we propose a method for computing convolution of large 3D images. The convolution is performed in a frequency domain using a convolution theorem. The algorithm is accelerated on a graphic card by means of the CUDA parallel computing model. Convolution is decomposed in a frequency domain using the decimation in frequency algorithm. We pay attention to keeping our approach effici...

We describe Lapedo, a novel library of hybrid parallel skeletons for programming heterogeneous multi-core/many-core CPU/GPU systems in Erlang. Lapedo’s hybrid skeletons comprise a mixture of CPU and GPU components, allowing skeletons to be flexibly and dynamically mapped to available resources. We also describe a model for deriving near-optimal division of work between CPUs and GPUs, ensuring l...

The speed at which two remote parties can exchange secret keys over a fixed-length fiber-optic cable in continuousvariable quantum key distribution (CV-QKD) is currently limited by the computational complexity of post-processing algorithms for key reconciliation. Multi-edge low-density paritycheck (LDPC) codes with low code rates and long block lengths were proposed for CV-QKD, in order to exte...

The use of GPUs to accelerate the factoring of large sparse symmetric indefinite matrices shows the potential of yielding important benefits to a large group of widely used applications. This paper examines how a multifrontal sparse solver performs when exploiting both the GPU and its multi-core host. It demonstrates that the GPU can dramatically accelerate the solver relative to one host CPU. ...