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Steven Gurfinkel
Many computer systems now include both CPUs and programmable GPUs. OpenCL, a new programming framework, can program individual CPUs or GPUs; however, distributing a problem across multiple devices is more difficult. This thesis contributes three OpenCL runtimes that automatically distribute a problem across multiple devices: DualCL and m2sOpenCL, which distribute tasks across a single system’s […]
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Matthew Thomas Calef, John Greaton Wohlbier
We describe the problem of iterating over mesh zones and iterating over material data within a zone, in the context of relatively new compute architectures. We present an example for how this can be done in a way that is portable across parallel programming environments and can be made to perform well. We offer a […]
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Satoshi Tanaka, Kohji Yoshikawa, Takashi Okamoto, Kenji Hasegawa
We present a new numerical scheme to solve the transfer of diffuse radiation on three-dimensional mesh grids which is efficient on processors with highly parallel architecture such as recently popular GPUs and CPUs with multi- and many-core architectures. The scheme is based on the ray-tracing method and the computational cost is proportional to N^5/3_m where […]
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Sreeram Potluri
Accelerators (such as NVIDIA GPUs) and coprocessors (such as Intel MIC/Xeon Phi) are fueling the growth of next-generation ultra-scale systems that have high compute density and high performance per watt. However, these many-core architectures cause systems to be heterogeneous by introducing multiple levels of parallelism and varying computation/communication costs at each level. Application developers also […]
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Mikhail A. Farkov
The vast majority of problems faced by bioinformatics are very complex and time consuming. They require the use of modern high-performance computational systems and the development of algorithms for such system. Heterogeneous computing systems which include graphics processing unit (GPU) occupy a separate niche. Such systems allow to accelerate solving of some task significantly. The […]
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Jinwoong Kim, Beomseok Nam
The general purpose computing on graphics processing unit (GP-GPU) has emerged as a new cost effective parallel computing paradigm in high performance computing research that enables large amount of data to be processed in parallel. Large scale scientific data intensive applications have been playing an important role in modern high performance computing research. A common […]
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Hyungsuk Choi, Woohyuk Choi, Tran Minh Quan, David G. C. Hildebrand, Hanspeter Pfister, Senior Member, Won-Ki Jeong
As the size of image data from microscopes and telescopes increases, the need for high-throughput processing and visualization of large volumetric data has become more pressing. At the same time, many-core processors and GPU accelerators are commonplace, making high-performance distributed heterogeneous computing systems affordable. However, effectively utilizing GPU clusters is difficult for novice programmers, and […]
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Adam McLaughlin, David A. Bader
Graphs that model social networks, numerical simulations, and the structure of the Internet are enormous and cannot be manually inspected. A popular metric used to analyze these networks is betweenness centrality, which has applications in community detection, power grid contingency analysis, and the study of the human brain. However, these analyses come with a high […]
Ichitaro Yamazaki, Stanimire Tomov, Tingxing Dong, Jack Dongarra
We propose a mixed-precision orthogonalization scheme that takes the input matrix in a standard 32 or 64-bit floating-point precision, but uses higher-precision arithmetics to accumulate its intermediate results. For the 64-bit precision, our scheme uses software emulation for the higher-precision arithmetics, and requires about 20x more computation but about the same amount of communication as […]
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Ichitaro Yamazaki, Stanimire Tomov, Tingxing Dong, Jack Dongarra
We propose a mixed-precision orthogonalization scheme that takes the input matrix in a standard 32 or 64-bit floating-point precision, but accumulates its intermediate results in the doubled-precision. For a 64-bit input matrix, we use software emulation for the higher-precision arithmetics. Compared with the standard orthogonalization scheme, we require about 8:5 more computation but a much […]
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Tsuyoshi Watanabe, Naohito Nakasato
We propose a hybrid tree algorithm for reducing calculation and communication cost of collision-less N-body simulations. The concept of our algorithm is that we split interaction force into two parts: hard-force from neighbor particles and soft-force from distant particles, and applying different time integration for the forces. For hard-force calculation, we can efficiently reduce the […]
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Tran Minh Quan, Won-Ki Jeong
Discrete wavelet transform (DWT) has been widely used in many image compression applications, such as JPEG2000 and compressive sensing MRI. Even though a lifting scheme [1] has been widely adopted to accelerate DWT, only a handful of research has been done on its efficient implementation on many-core accelerators, such as graphics processing units (GPUs). Moreover, […]
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