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Array region analysis plays a significant role in various optimizations at compile time. Displaying array access information efficiently in HPC applications has been a vital challenge for scientists and developers for the past few years. Dragon array region analysis tool is a powerful and interactive tool that was built on top of the Open UH compiler, an open source C/C++/Fortran compiler, that supports...
In this paper, we propose a source-to-source code optimization framework for general purpose computing on graphics processing units (GPGPU). Our framework is based on a re-formulation of the polyhedral loop transformation theory under the context of GPGPU. We prove that the number of actual memory transactions can be used as a performance metric to guide the code optimization process. In addition,...
Due to their outstanding computational performance, many acceleration devices, such as GPUs, the Cell Broadband Engine (Cell/B.E.), and multi-core computing are attracting a lot of attention in the field of high-performance computing. Although there are many programming models and languages de-signed for programming accelerators, such as CUDA, AMD Accelerated Parallel Processing (AMD APP), and OpenCL,...
As the demand for research on Image/ Content authentication has significantly increased, many authentication schemes have been proposed so far. But most of them are time consuming. This research concentrates on decreasing the time needed by an Image authentication algorithm. In this paper, we have shown a CUDA-based implementation of content authentication algorithm with NVIDIA's GeForce 8400 GS GPU...
GPU (Graphics Processing Unit) provides high computational speed at a very low cost as compared to high end systems. The field of parallel processing using GPU is advancing very fast with a new technology being introduced in the field every day. With such advancements, it is necessary to review the major works done in this field. Graph traversal is one of the major challenges in this field. So far...
Computational fluid dynamics (CFD) applications have an ever-growing demand for the power of high performance computing (HPC) infrastructure. Many CFD simulations have benefited from newly-acknowledged GPU clusters. However, few of them have exploited both the CPU and the GPU computational resources within the heterogeneous HPC platforms. In this paper, we endeavor to demonstrate the approach of making...
In the paper, particle gradient multi-objective evolutionary algorithm (PGMOEA) on GPU is presented. PGMOEA extends the classical particle dynamic multi-objective evolutionary algorithm by incorporating the gradient information of each particle from evolutionary programming. We perform experiments to compare PGMOEA on GPU with PGMOEA on CPU and demonstrate that PGMOEA on GPU is much more effective...
Space is a very important aspect in the simulation of biochemical models, recently, the need for simulation algorithms able to cope with space is becoming more and more compelling. Complex and large models of biochemical systems need to deal with the movement of single molecules and particles, taking into consideration localised fluctuations, transportation phenomena and diffusion. A common drawback...
Multiple-precision integer operations are key components of many security applications; but unfortunately they are computationally expensive on contemporary CPUs. In this paper, we present our design and implementation of a multiple-precision integer library for GPUs which is implemented by CUDA. We report our experimental results which show that a significant speedup can be achieved by GPUs as compared...
This paper describes the techniques used to describe and synthesize FPGA circuits expressed in a data-parallel domain specific language (DSL) called Accelerator. We identify the subset of data-parallel descriptions that are supported by our system and explain how we track memory access patterns which allow us to generate efficient FPGA circuits.
Because of the very favorable price to performance ratio of the GPUs, a popular parallel programming configuration today is a cluster of GPUs. However, extracting performance on such a configuration would typically require programming in both MPI and CUDA, thus requiring a high degree of expertise and effort. It is clearly desirable to be able to support higher-level programming of this emerging high-performance...
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...
Optimization algorithms are becoming increasingly more important in many areas, such as finance and engineering. Typically, real problems involve several hundreds of variables, and are subject to as many constraints. Several methods have been developed trying to reduce the theoretical time complexity. Nevertheless, when problems exceed reasonable sizes they end up being very computationally intensive...
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