Abstract The Backward Stochastic Differential Equation (BSDE) is an important tool for pricing and hedging. Highly accurate low computation time becomes interesting minimizing monetary loss. Therefore, we explore the opportunity of parallelizing high-order multistep schemes in option pricing. In scheme computations at each space grid point are independent this fact motivates us to select massiv...

The basic operations on the graphs with millions of vertices are common in various applications. To have faster execution of such operations is very essential to reduce overall computation time. Today’s Graphics processing units (GPUs) have high computation power and low price. This device can be treated as an array of Single Instruction Multiple Data (SIMD) processors using CUDA software inter...

Graphics processing units (GPUs) have a SIMD architecture and have been widely used recently as powerful generalpurpose co-processors for the CPU. In this paper, we investigate efficient GPU-based data cubing because the most frequent operation in data cube computation is aggregation, which is an expensive operation well suited for SIMD parallel processors. H-tree is a hyper-linked tree structu...

We introduce an approach for the real-time (2Hz) creation of a dense map and alignment of a moving robotic agent within that map by rendering using a Graphics Processing Unit (GPU). This is done by recasting the scan alignment part of the dense mapping process as a rendering task. Alignment errors are computed from rendering the scene, comparing with range data from the sensors, and minimized b...

This paper presents a GPU (Graphics Processing Units) implementation of dynamic programming for the optimal polygon triangulation. Recently, GPUs can be used for general purpose parallel computation. Users can develop parallel programs running on GPUs using programming architecture called CUDA (Compute Unified Device Architecture) provided by NVIDIA. The optimal polygon triangulation problem fo...

This thesis investigates using highly parallel accelerator architectures to accelerate the simulation of nonlinear hyperbolic PDEs. Second-order accurate finite volume flux-limiter methods are implemented for the shallow water equations using cartesian grids and explicit time-stepping. The solver is implemented for three different architectures, a multicore x86 CPU using threading, IBM’s Cell P...

In data mining applications, one of the useful algorithms for classification is the kNN algorithm. The kNN search has a wide usage in many research and industrial domains like 3-dimensional object rendering, content-based image retrieval, statistics, biology (gene classification), etc. In spite of some improvements in the last decades, the computation time required by the kNN search remains the...

In the computer aided medical image process, image segmentation is always required as a preprocess stage. Fuzzy c-means (FCM) clustering algorithm has been commonly used in many medical image segmentations, particularly in the analysis of magnetic resonance (MR) brain image. However, all of these FCM methods are computation consuming that is difficult to be used in real time application. In the...

High-order gas-kinetic scheme (HGKS) has become a workable tool for the direct numerical simulation (DNS) of turbulence. In this paper, to accelerate computation, HGKS is implemented with graphical processing unit (GPU) using compute unified device architecture (CUDA). To conduct much large-scale DNS turbulence, also be further upgraded multiple GPUs message passing interface (MPI) and CUDA arc...