Voxelwise quantification of hepatic perfusion parameters from dynamic contrast enhanced (DCE) imaging greatly contributes to assessment of liver function in response to radiation therapy. However, the efficiency of the estimation of hepatic perfusion parameters voxel-by-voxel in the whole liver using a dual-input single-compartment model requires substantial improvement for routine clinical app...

Parallel computing is a form of computation in which many calculations are carried out simultaneously, operating on the principle that large problems can often be divided into smaller ones, which are then solved concurrently. Now Graphics Processing Unit (GPU) has taken a major role in high performance computing for generic applications. Compute Unified Device Architecture (CUDA) programming mo...

We present Synkhronos, an extension to Theano for multi-GPU computations leveraging data parallelism. Our framework provides automated execution and synchronization across devices, allowing users to continue to write serial programs without risk of race conditions. The NVIDIA Collective Communication Library is used for high-bandwidth inter-GPU communication. Further enhancements to the Theano ...

The SAT problem is the first NP-complete problem. So far there is no algorithm that can solve it in polynomial time. Over the past decade, the development of efficient and scalable algorithms has dramatically leveraged the ability of solving SAT problem instances involving tens of thousands of variables and millions of constraints. But as industry demand is increasing, a faster SAT solver is ne...

This paper presents a novel parallelization and quantitative characterization of various optimization strategies for dataparallel computation on a graphics processing unit (GPU) using NVIDIA’s new GPU programming framework, Compute Unified Device Architecture (CUDA). CUDA is an easy-to-use development framework that has drawn the attention of many different application areas looking for dramati...

In this paper, we have proposed sequential and parallel Discrete Cosine Transform (DCT) in compute unified device architecture (CUDA) libraries. The introduction of programmable pipeline in the graphics processing units (GPU) has enabled configurability. GPU which is available in every computer has a tremendous feat of highly parallel SIMD processing, but its capability is often under-utilized....

With the development of satellite remote sensing technology, satellite remote sensing data obtained by the amount will increase rapidly. Consequently, the process of Wallis transformation is faced with such challenges as large data size, high intensity, high computational complexity and large computational quantity, and so on. A fast algorithm and efficient implementation of Wallis filtering ba...

With the rapid progress of computational science and computer simulation ability, a lot of properties can be predicted by the powerful ability of parallel computation before the actual research and development. With the development of high performance computer architecture, GPU is more and more widely used in high performance computation field as an emerging architecture, and a growing number o...

Multiple independent runs of an evolutionary algorithm in parallel are often used to increase the efficiency of parameter tuning or to speed up optimizations involving inexpensive fitness functions. A GPU platform is commonly adopted in the research community to implement parallelization, and this platform has been shown to be superior to the traditional CPU platform in many previous studies. H...

A double-GPU code is developed to accelerate WENO schemes. The test problem is a compressible viscous flow. The convective terms are discretized using third- to ninth-order WENO schemes and the viscous terms are discretized by the standard fourth-order central scheme. The code written in CUDA programming language is developed by modifying a single-GPU code. The OpenMP library is used for parall...