high performance computing on graphics processing units: hgpu.org

We present the conditions of a data science challenge from Kaggle, which can be viewed as a multi-instance multilabel learning problem in the image domain, and describe the official training dataset provided. We discuss our technical approach, and address the challenges in using transfer learning and with finetuning, trying out different strategies to tackle the […]

We present a mechanism to symbolically gather performance-relevant operation counts from numerically-oriented subprograms (‘kernels’) expressed in the Loopy programming system, and apply these counts in a simple, linear model of kernel run time. We use a series of ‘performance-instructive’ kernels to fit the parameters of a unified model to the performance characteristics of GPU hardware […]

Scan (or prefix sum) is a fundamental and widely used primitive in parallel computing. In this paper, we present LightScan, a faster parallel scan primitive for CUDA-enabled GPUs, which investigates a hybrid model combining intra-block computation and inter-block communication to perform a scan. Our algorithm employs warp shuffle functions to implement fast intra-block computation and […]

Large-scale deep learning requires huge computational resources to train a multi-layer neural network. Recent systems propose using 100s to 1000s of machines to train networks with tens of layers and billions of connections. While the computation involved can be done more efficiently on GPUs than on more traditional CPU cores, training such networks on a […]

This paper presents a survey of Smoothed Particle Hydrodynamics (SPH) and its use in computational fluid dynamics. As a truly mesh-free particle method based upon the Lagrangian formulation, SPH has been applied to a variety of different areas in science, computer graphics and engineering. It has been established as a popular technique for fluid based […]

This paper compares different Krylov methods based on short recurrences with respect to their efficiency when implemented on GPUs. The comparison includes BiCGSTAB, CGS, QMR, and IDR using different shadow space dimensions. These methods are known for their good convergence characteristics. For a large set of test matrices taken from the University of Florida Matrix […]

OpenCL is a standard for parallel programming of heterogeneous systems. The benefits of a common programming standard are clear; multiple vendors can provide support for application descriptions written according to the standard, thus reducing the program porting effort. While the standard brings the obvious benefits of platform portability, the performance portability aspects are largely left […]

Data mining tasks such as clustering, outlier detection and similarity search typically employ a series of algorithms to operate on a large set of data, making them amenable to parallelization. Thus parallelization of data mining operations such as distance computation has been extensively studied in the literature. In recent years, the use of Graphics Processing […]

Index Ei Compendex, Inspec, DOAJ, CPCI (Web of Science) and Scopus. COMMITTEE Conference Chairs Prof. Chen-Huei Chou, College of Charleston, USA Prof. Yongsheng Ma, University of Alberta, Canada Prof. Jiangping Wang, Webster University, USA Local Chair Dr. Xiaoyu Zeng, Beijing Wuzi University, China   AGENDA July 22, 2016 – Registration & Conference Materials Collection July […]

The conference committees are consisted of professors, specialists and distinguished researchers from all over the world. Publication All registered will be published in Conference Proceedings, which will be indexed by Ei Compendex and Scopus. Some Excellent papers will be recommended to International Journal of Engineering and Technology (IJET) and International Journal of Mechanical Engineering and […]

Publication All accepted papers of ICCBB 2016 will be published in Conference Proceedings, which will be indexed by Ei Compendex and Scopus. Some of registered papers will be recommended to be published in International Journal of Bioscience, Biochemistry and Bioinformatics (IJBBB). Supported by University of Malaya, Malaysia Universiti Teknologi MARA, Malaysia Universiti Teknologi Malaysia, Malaysia […]

Breadth First Search (BFS) is a building block for graph algorithms and has recently been used for large scale analysis of information in a variety of applications including social networks, graph databases and web searching. Due to its importance, a number of different parallel programming models and architectures have been exploited to optimize the BFS. […]