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The emergence of power efficiency as a primary constraint in processor and system designs poses new challenges concerning power and energy awareness for numerical libraries and scientific applications. Power consumption also plays a major role in the design of data centers in particular for peta- and exa-scale systems. Understanding and improving the energy efficiency of numerical simulation becomes...
Many applications — from data compression to numerical weather prediction and information retrieval — need to compute large dense singular value decompositions (SVD). When the problems are too large to fit into the computer's main memory, specialized out-of-core algorithms that use disk storage are required. A typical example is when trying to analyze a large data set through tools like MATLAB or...
Triangle counting serves as a key building block for a set of important graph algorithms in network science. In this paper, we address the IEEE HPEC Static Graph Challenge problem of triangle counting, focusing on obtaining the best parallel performance on a single multicore node. Our implementation uses a linear algebra-based approach to triangle counting that has grown out of work related to our...
We propose a method for semi-supervised classification using a combination of ensemble clustering and kernel based learning. The method works in two steps. In the first step, a number of variants of clustering partition are obtained with some clustering algorithm working on both labeled and unlabeled data. Weighted averaged co-association matrix is calculated using the results of partitioning. We...
SIMD vectors help improve the performance of certain applications. The code gets vectorized into SIMD form either by hand, or automatically with auto-vectorizing compilers. The Superword-Level Parallelism (SLP) vectorization algorithm is a widely used algorithm for vectorizing straight-line code and is part of most industrial compilers. The algorithm attempts to pack scalar instructions into vectors...
In this paper we propose a vectorized sorted set intersection approach for the task of counting the exact number of triangles of a graph on CPU cores. The computation is factorized into reordering and counting kernels where the reordering kernel builds upon the Reverse Cuthill-McKee heuristic.
A malt is one of intermediate ingredients for a brewing industry. The quality of barley used for malting have essential impact on the final product flavor. An automatic system for a barley grains inspection, utilizing computer vision methods, can provide an objective quality assessment. We present image preprocessing steps of grain inspection system. Main preprocessing steps are: segmentation of grain...
In this paper, we propose an analog circuit for binary neural firing model that can extract various image features. Both computational and hardware models were designed for feature extraction algorithm that explores the dependency of firing rates on the pixel intensity in alignment with inhibition and excitation principles. The circuit for translating each pixel intensity into a series of pulses is...
A routing graph allows to find paths in buildings quickly. Raster images of floor plans are simple to obtain but display poor performance. A manually constructed graph is quite optimal if designed by an informed person, but the process is time consuming and expensive. We describe a fast method to calculate a 2D routing graph from raster images. We adapt image processing techniques and apply a conditional...
The Volterra model is a well-established option in nonlinear black-box system identification. However, the estimated model is often over-parametrized. This paper presents an approach to reducing the number of parameters of a Volterra model with the kernels parametrized in the orthonormal basis of Laguerre functions by estimating it with a sparse estimation algorithm subject to constraints. The resulting...
One of the key aspects in the successful use of kernel methods such as Support Vector Machines is the proper choice of the kernel function. While there are several well known kernel functions which can produce satisfactory results for various applications (e.g. RBF), they do not take into account specific characteristics of the data sets. Moreover, they have a set of parameters to be tuned. In this...
In Gradient-Based Cross-Spectral Stereo Matching (GB-CSSM) output disparity maps tend to produce coarse results that are, for the most part, reliable. However, general methods of improving the performance of disparity maps generated from the Cross-Spectral comparison of visual and full infrared input images are non-existent. In particular, previous works fail to address the role and interaction of...
The Gaussian kernel least-mean-square (Gaussian KLMS) algorithm has been studied under different implementation conditions. Though analytical models that predict its behavior are available, methodologies for determining the algorithm parameter values to satisfy given design criteria is still missing from the literature. In this paper we propose, test, and validate a methodology for the design of the...
Aiming at the multiple attribute decision making problem with three-parameter interval grey numbers, a grey-incidence clustering decision making method based on regret theory is proposed in this paper. First, according to the idea of TOPSIS method, a kind of comprehensive grey interval incidence coefficient of three-parameter interval grey number is defined, and the “regret-rejoice” value is calculated...
Fuzzy clustering has emerged as an important tool for discovering the structure of data. Kernel based clustering has emerged as an interesting and quite visible alternative in fuzzy clustering. Aimed at the problems of both a local optimum and depending on initialization strongly in the fuzzy c-means clustering algorithm (FCM), a method of kernel-based fuzzy c-means clustering based on fruit fly algorithms...
This paper deals with the visibility properties of monotone paths connecting two points in the presence of polygonal obstacles. We examine the development of efficient algorithms for constructing a monotone watchman path from which any point on the boundary of obstacles is visible from some point along the path. Specifically, we formulate visibility aware monotone watchman path (VAMWM) problem and...
Data clustering methods have been used extensively for image segmentation in the past decade. In our previous work, we had established that combining the traditional clustering algorithms with a meta-heuristic like Firefly Algorithm improves the stability of the output as well as the speed of convergence. In this paper, we have replaced the Euclidean distance formula with kernels. We have combined...
The home-grown SW26010 many-core processor enabled the production of China’s first independently developed number-one ranked supercomputer – the Sunway TaihuLight. The design of the limited off-chip memory bandwidth, however, renders the SW26010 a highly memory-bound processor. To compensate for this limitation, the processor was designed with a unique hardware feature, "Register Level Communication"...
The exponential growth of available data has increased the need for interactive exploratory analysis. Dataset can no longer be understood through manual crawling and simple statistics. In Geographical Information Systems (GIS), the dataset is often composed of events localized in space and time; and visualizing such a dataset involves building a map of where the events occurred.We focus in this paper...
With the increase of CMP (Chip-Multiprocessor) scale, moving data to computation on chip becomes more expensive. Accordingly, moving computation to data has potential to improve efficiency. We propose an in-place computation co-design of many-simple-core CMP for irregular applications. The computing paradigm is that an application's critical irregular data (or part of them) is partitioned into on-chip...
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