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This paper analyses several parallel approaches for the development of a physical model of Non-linear ODT for its application in velocimetry techniques. The main benefits of its application in HPIV are the high accuracy with non-damaging radiation and its imaging capability to recover information from the vessel wall of the flow. Thus ODT-HPIV is suitable for microfluidic devices and biofluidic applications...
As the size and complexity of scientific problems and datasets grow, scientists from a broad range of discipline areas are relying more and more on computational methods and simulations to help solve their problems. This paper presents a summary of heterogeneous algorithms and applications that have been developed by a large research organization (CSIRO) for solving practical and challenging science...
Many of the basic image processing tasks suffer from processing overhead to operate over the whole image. In real time applications the processing time is considered as a big obstacle for its implementations. A High Performance Computing (HPC) platform is necessary in order to solve this problem. The usage of hardware accelerator make the processing time low. In recent developments, the Graphics Processing...
Graphics Processing Units (GPUs) have enabled significant improvements in computational performance compared to traditional CPUs in several application domains. Until recently, GPUs have been programmed using C/C++ based methods such as CUDA (NVIDIA) and OpenCL (NVIDIA and AMD). Using these approaches, Fortran Numerical Weather Prediction (NWP) codes would have to be completely re-written to take...
The development of the hardware changes program structure. Now the Graphic Processing Unit (GPU) has evolved into an extremely flexible, powerful and cost-efficient processor, which is specialized for compute intensive, massively data parallel computation. In the field of financial derivatives pricing and risk management, the Backward Stochastic Differential Equation (BSDE) is a robust tool. The aim...
GPUs (Graphics Processing Units) have become one of the main co-processors that contributed to desktops towards high performance computing. Together with multi-core CPUs, a powerful heterogeneous execution platform is built for massive calculations. To improve application performance and explore this heterogeneity, a distribution of workload in a balanced way over the PUs (Processing Units) plays...
The computational power of modern graphics processing units (GPUs) has become an interesting alternative in high performance computing. The specialized hardware of GPUs delivers a high degree of parallelism and performance. Various applications in scientific computing have been implemented such that computationally intensive parts are executed on GPUs. In this article, we present a GPU implementation...
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