Fast kk-NNG construction with GPU-based quick multi-select

In this paper we describe a new brute force algorithm for building the $k$-Nearest Neighbor Graph ($k$-NNG). The $k$-NNG algorithm has many applications in areas such as machine learning, bio-informatics, and clustering analysis. While there are very efficient algorithms for data of low dimensions, for high dimensional data the brute force search is the best algorithm. There are two main parts to the algorithm: the first part is finding the distances between the input vectors which may be formulated as a matrix multiplication problem. The second is the selection of the $k$-NNs for each of the query vectors. For the second part, we describe a novel graphics processing unit (GPU) -based multi-select algorithm based on quick sort. Our optimization makes clever use of warp voting functions available on the latest GPUs along with use-controlled cache. Benchmarks show significant improvement over state-of-the-art implementations of the $k$-NN search on GPUs

Efficient Computation of K-Nearest Neighbor Graphs for Large High-Dimensional Data Sets on GPU Clusters

The k-Nearest Neighbor Graph (k-NNG) and the related k-Nearest Neighbor (k-NN) methods have a wide variety of applications in areas such as bioinformatics, machine learning, data mining, clustering analysis, and pattern recognition. Our application of interest is manifold embedding. Due to the large dimensionality of the input data (\u3c15k), spatial subdivision based techniques such OBBs, k-d tree, BSP etc., are not viable. The only alternative is the brute-force search, which has two distinct parts. The first finds distances between individual vectors in the corpus based on a pre-defined metric. Given the distance matrix, the second step selects k nearest neighbors for each member of the query data set. This thesis presents the development and implementation of a distributed exact k-Nearest Neighbor Graph (k-NNG) construction method. The proposed method uses Graphics Processing Units (GPUs) and exploits multiple levels of parallelism for distributed computational systems using GPUs. It is scalable for different cluster sizes, with each compute node in the cluster containing multiple GPUs. The distance computation is formulated as a basic matrix multiplication and reduction operation. The optimized CUBLAS matrix multiplication library is used for this purpose. Various distance metrics such as Euclidian, cosine, and Pearson are supported. For k-NNG construction, two different methods are presented. The first is based on an approach called batch index sorting to build the k-NNG with three sorting operations. This method uses the optimized radix sort implementation in the Thrust library for GPU. The second is an efficient implementation using the latest GPU functionalities of a variant of the quick select algorithm. Overall, the batch index sorting based k-NNG method is approximately 13x faster than a distributed MATLAB implementation. The quick select algorithm itself has a 5x speedup over state-of-the art GPU methods. This has enabled the processing of k-NNG construction on a data set containing 20 million image vectors, each with dimension 15,000, as part of a manifold embedding technique for analyzing the conformations of biomolecules

Extracting the Structure and Conformations of Biological Entities from Large Datasets

In biology, structure determines function, which often proceeds via changes in conformation. Efficient means for determining structure exist, but mapping conformations continue to present a serious challenge. Single-particles approaches, such as cryogenic electron microscopy (cryo-EM) and emerging diffract & destroy X-ray techniques are, in principle, ideally positioned to overcome these challenges. But the algorithmic ability to extract information from large heterogeneous datasets consisting of unsorted snapshots - each emanating from an unknown orientation of an object in an unknown conformation - remains elusive. It is the objective of this thesis to describe and validate a powerful suite of manifold-based algorithms able to extract structural and conformational information from large datasets. These computationally efficient algorithms offer a new approach to determining the structure and conformations of viruses and macromolecules. After an introduction, we demonstrate a distributed, exact k-Nearest Neighbor Graph (k-NNG) construction method, in order to establish a firm algorithmic basis for manifold-based analysis. The proposed algorithm uses Graphics Processing Units (GPUs) and exploits multiple levels of parallelism in distributed computational environment and it is scalable for different cluster sizes, with each compute node in the cluster containing multiple GPUs. Next, we present applications of manifold-based analysis in determining structure and conformational variability. Using the Diffusion Map algorithm, a new approach is presented, which is capable of determining structure of symmetric objects, such as viruses, to 1/100th of the object diameter, using low-signal diffraction snapshots. This is demonstrated by means of a successful 3D reconstruction of the Satellite Tobacco Necrosis Virus (STNV) to atomic resolution from simulated diffraction snapshots with and without noise. We next present a new approach for determining discrete conformational changes of the enzyme Adenylate kinase (ADK) from very large datasets of up to 20 million snapshots, each with ~104 pixels. This exceeds by an order of magnitude the largest dataset previously analyzed. Finally, we present a theoretical framework and an algorithmic pipeline for capturing continuous conformational changes of the ribosome from ultralow-signal (-12dB) experimental cryo-EM. Our analysis shows a smooth, concerted change in molecular structure in two-dimensional projection, which might be indicative of the way the ribosome functions as a molecular machine. The thesis ends with a summary and future prospects

Competing Universalities in Kardar-Parisi-Zhang (KPZ) Growth Models

We report on the universality of height fluctuations at the crossing point of two interacting (1+1)-dimensional Kardar-Parisi-Zhang (KPZ) interfaces with curved and flat initial conditions. We introduce a control parameter p as the probability for the initially flat geometry to be chosen and compute the phase diagram as a function of p. We find that the distribution of the fluctuations converges to the Gaussian orthogonal ensemble Tracy-Widom (TW) distribution for p0.5. For p=0.5 where the two geometries are equally weighted, the behavior is governed by an emergent Gaussian statistics in the universality class of Brownian motion. We propose a phenomenological theory to explain our findings and discuss possible applications in nonequilibrium transport and traffic flow.Comment: 5 pages, 6 figures, Phys. Rev. Lett. (2019) (accepted

The effect of online journalism on the freedom of the press: the case of Kuwait

Online journalism has brought new features of journalism practices for local journalists and forced the expansion of their freedom. The Internet as a whole became the tool for freedom of expression for many suppressed countries, and online journalism became an alternative for press freedom in cyberspace. The diffusion of information enabled more opportunities for freedom of expression and speech prosperity, leading to a higher level of freedom in local press. This research project aims to examine the effect of online journalism on the freedom of the local press in the state of Kuwait. Since mid 1990s, when the Internet was introduced in Kuwait, a new phenomenon of press freedom started to rise. After many decades of relying heavily on local newspapers and controlled radio and TV, many Kuwaitis switched to the Internet to obtain information, news and political analysis. The political dispute of power after the death of Kuwaiti Emir Sheikh Jabber Al-Ahmad Al-Sabah on 15 of January 2006, followed by the public demand to change the electoral constituencies voting system of the National Assembly, and the dissolving of the National Assembly in May 2006 forced many Kuwaitis to go online to get the latest news and analysis regarding the two issues. Kuwaiti online journalism became the source for instant updated information during the disputes. Many local writers praised their work on local press. Mohammad Abdul Qader Al-Jasim, a columnist and former editor in chief for Alwatan local newspaper, in his online Web site ‘Meezan’, provided non-censored detailed analysis of these situations without any restrictions or fear of government interference which was considered as a taboo “red line” no one was permitted to cross. The researcher used three different tools (survey, online content analysis, and interviews) to determine the effect of online journalism on journalist’s practices and the freedom of the press in Kuwait, focusing on the most popular Kuwaiti personal writers’ sites, weblogs and forums. The results show that online journalism affected journalist’s practices but did not replace the traditional practices. The Internet became a source and communication platform for many local journalists. At the same time, online journalism became one of the tools that helped increase the level of freedom in the local press. The language of online journalism took a different direction from the local press with more freedom to write, discuss, and share ideas online with less fear of government retribution. What was considered a taboo “red line” in the local press became an acceptable “green line” online. Local press officials recognized this effect on the local freedom, but disagree on the factors that really caused the freedom of the local press to increase

Qualitative principles for designing children’s educational environments based on nurturing creativity approach

All children show a lot of creativity themselves, but gradually due to the influence of adults and the environments in which they are, their creative power is reduced and finally they become those who lack these superior characteristics. Therefore, centers should be established which make environmental element and materials and required tools to maintain and enhance the creativity of children available to them and enable them to the permanent use of this divine gift by the necessary training. Taking precautions in the design of such spaces which match their physical and mental characteristics, physical flexibility, as well as flexibility in the planning and organization of spaces and activities can dramatically provide an environment in which children’s creativity is properly revealed and promoted. In order to achieve the desired goals, the method of library studies to review the literature and also case and field studies were used. According to the results of this study, it can be stated that rich environmental motivators and appropriate trainings, influence intelligence growth and primary learning and on the other hand ignoring environmental qualitative elements in various forms can have irreparable negative effects on various aspects of growth including motion growth, intelligence and creativity. The purpose of decorating the environment in children's educational space is to simplify the learning of children and teaching of instructors. Materials and tools which are used must be chosen in such a way that they provide multiple opportunities for children to learn different skills. The method used to organize internal and external spaces is vital in creating opportunities for children to express their creativity

Study of geothermal energy potential as a green source of energy with a look at energy consumption in Iran

Regarding disadvantages of fossil fuels, renewables like geothermals can be an eco-friendly source of energy. In Iran, the availability of fossil fuels and poor policies surrounding subsidies (ranked as the first in giving subsidies) caused high energy consumption (1.75 times higher than the global average). Energy is mainly provided by fossil fuels that leads to high CO$_{2}$ emission. This study evaluates the energy consumption trend and potentials of more sustainable resources like geothermals in Iran. The formation of geothermals is tightly linked with geological prerequisites that are partly present within Iran. Adjacency of the metamorphic with volcanic zones, existence of numerous faults and seismic activity of Iran are notable geological characteristics confirming the geothermal potential. In Iran, 18 regions are being explored as the most promising geothermal prospects. To test the potentials of one of these regions, a geothermal power plant with a capacity of 5 MWe is installed in the Sabalan Field. Northwest (where Sabalan Field is located), central (like Mahalat Region) and southeast of Iran (Makran Zone) can be regarded as promising zones for hosting geothermal prospects