The BG News November 14, 2005

The BGSU campus student newspaper November 14, 2005. Volume 96 - Issue 58https://scholarworks.bgsu.edu/bg-news/8515/thumbnail.jp

Big Data Now, 2015 Edition

Now in its fifth year, O’Reilly’s annual Big Data Now report recaps the trends, tools, applications, and forecasts we’ve talked about over the past year. For 2015, we’ve included a collection of blog posts, authored by leading thinkers and experts in the field, that reflect a unique set of themes we’ve identified as gaining significant attention and traction. Our list of 2015 topics include: Data-driven cultures Data science Data pipelines Big data architecture and infrastructure The Internet of Things and real time Applications of big data Security, ethics, and governance Is your organization on the right track? Get a hold of this free report now and stay in tune with the latest significant developments in big data

Web services strategy

Thesis (S.M.M.O.T.)--Massachusetts Institute of Technology, Sloan School of Management, Management of Technology Program, 2003.June 2003.Includes bibliographical references (p. 116-123).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Everything is connected to everything. El Aleph (1945), by Jorge Luis Borges[1] This thesis addresses the need to simplify and streamline web service network infrastructure and to identify business models that best leverage Web services technology and industry dynamics to generate positive business results. Web services have evolved from the simple page-display protocol of their origin and now reach beyond the links that simply updated web data dynamically from corporate databases, to where systems can automatically transact. These Web services represent a series of network business technology standards and capabilities that irrevocably change the way in which businesses will do business. In fact, every business today is a networked business and has opportunities to grow using Web services. This study focuses on the implementation challenges in the financial services market, specifically the On Line Transaction Processing (OLTP) sector where legacy mainframes interface with multiple tiers of distribution through proprietary EDI links. The OLTP industry operates under stringent regulatory requirements for availability and audit-ability of not only who performed what transaction, but who had access to the information about the information. In this environment organizational demands on network infrastructure including hardware, software and personnel are changing radically, while concurrently Information Technology (IT) budgets are under pressure. The strategic choices for deploying web services in this environment may contain lessons for other industries where cost effective large scale processing, high availability, security, manageability and Intellectual Property Rights (IPR) are paramount concerns. In this paper we use a systems dynamics model to simulate the impact of market changes on the adoption of innovative technologies and their commoditization on the industry value chain, with the aim of identifying business models and network topologies which best support the growth of an Open Systems network business. From the results of the simulation we will derive strategic recommendations for networked business models and web services integration strategies to meet Line Of Business (LOB) objectives.by Stephen B. Miles.S.M.M.O.T

GPU-Acceleration of In-Memory Data Analytics

Hardware advances strongly influence the database system design. The flattening speed of CPU cores makes many-core accelerators, such as GPUs, a vital alternative to explore for processing the ever-increasing amounts of data. GPUs have a significantly higher degree of parallelism than multi-core CPUs but their cores are simpler. As a result, they do not face the power constraints limiting the parallelism of CPUs. Their trade-off, however, is the increased implementation complexity. This thesis adapts and redesigns data analytics operators to better exploit the GPU special memory and threading model. Due to the increasing memory capacity and also the user's need for fast interaction with the data, we focus on in-memory analytics. Our techniques span different steps of the data processing pipeline: (1) Data preprocessing, (2) Query compilation, and (3) Algorithmic optimization of the operators. Our data preprocessing techniques adapt the data layout for numeric and string columns to maximize the achieved GPU memory bandwidth. Our query compilation techniques compute the optimal execution plan for conjunctive filters. We formulate \textit{memory divergence} for string matching algorithms and suggest how to eliminate it. Finally, we parallelize decompression algorithms in our compression framework \textit{Gompresso} to fit more data into the limited GPU memory. Gompresso achieves high speed-ups on GPUs over multi-core CPU state-of-the-art libraries and is suitable for any massively parallel processor

NFComms: A synchronous communication framework for the CPU-NFP heterogeneous system

This work explores the viability of using a Network Flow Processor (NFP), developed by Netronome, as a coprocessor for the construction of a CPU-NFP heterogeneous platform in the domain of general processing. When considering heterogeneous platforms involving architectures like the NFP, the communication framework provided is typically represented as virtual network interfaces and is thus not suitable for generic communication. To enable a CPU-NFP heterogeneous platform for use in the domain of general computing, a suitable generic communication framework is required. A feasibility study for a suitable communication medium between the two candidate architectures showed that a generic framework that conforms to the mechanisms dictated by Communicating Sequential Processes is achievable. The resulting NFComms framework, which facilitates inter- and intra-architecture communication through the use of synchronous message passing, supports up to 16 unidirectional channels and includes queuing mechanisms for transparently supporting concurrent streams exceeding the channel count. The framework has a minimum latency of between 15.5 μs and 18 μs per synchronous transaction and can sustain a peak throughput of up to 30 Gbit/s. The framework also supports a runtime for interacting with the Go programming language, allowing user-space processes to subscribe channels to the framework for interacting with processes executing on the NFP. The viability of utilising a heterogeneous CPU-NFP system for use in the domain of general and network computing was explored by introducing a set of problems or applications spanning general computing, and network processing. These were implemented on the heterogeneous architecture and benchmarked against equivalent CPU-only and CPU/GPU solutions. The results recorded were used to form an opinion on the viability of using an NFP for general processing. It is the author’s opinion that, beyond very specific use cases, it appears that the NFP-400 is not currently a viable solution as a coprocessor in the field of general computing. This does not mean that the proposed framework or the concept of a heterogeneous CPU-NFP system should be discarded as such a system does have acceptable use in the fields of network and stream processing. Additionally, when comparing the recorded limitations to those seen during the early stages of general purpose GPU development, it is clear that general processing on the NFP is currently in a similar state

Scalable Observation, Analysis, and Tuning for Parallel Portability in HPC

It is desirable for general productivity that high-performance computing applications be portable to new architectures, or can be optimized for new workflows and input types, without the need for costly code interventions or algorithmic re-writes. Parallel portability programming models provide the potential for high performance and productivity, however they come with a multitude of runtime parameters that can have significant impact on execution performance. Selecting the optimal set of parameters, so that HPC applications perform well in different system environments and on different input data sets, is not trivial.This dissertation maps out a vision for addressing this parallel portability challenge, and then demonstrates this plan through an effective combination of observability, analysis, and in situ machine learning techniques. A platform for general-purpose observation in HPC contexts is investigated, along with support for its use in human-in-the-loop performance understanding and analysis. The dissertation culminates in a demonstration of lessons learned in order to provide automated tuning of HPC applications utilizing parallel portability frameworks

Trusted computing or trust in computing? Legislating for trust networks

This thesis aims to address several issues emerging in the new digital world. Using Trusted Computing as the paradigmatic example of regulation though code that tries to address the cyber security problem that occurs, where the freedom of the user to reconfigure her machine is restricted in exchange for greater, yet not perfect, security. Trusted Computing is a technology that while it aims to protect the user, and the integrity of her machine and her privacy against third party users, it discloses more of her information to trusted third parties, exposing her to security risks in case of compromising occurring to that third party. It also intends to create a decentralized, bottom up solution to security where security follows along the arcs of an emergent “network of trust”, and if that was viable, to achieve a form of code based regulation. Through the analysis attempted in this thesis, we laid the groundwork for a refined assessment, considering the problems that Trusted Computing Initiative (TCI) faces and that are based in the intentional, systematic but sometimes misunderstood and miscommunicated difference (which as we reveal results directly in certain design choices for TC) between the conception of trust in informatics (“techno-trust”) and the common sociological concept of it. To reap the benefits of TCI and create the dynamic “network of trust”, we need the sociological concept of trust sharing the fundamental characteristics of transitivity and holism which are absent from techno-trust. This gives rise to our next visited problems which are: if TC shifts the power from the customer to the TC provider, who takes on roles previously reserved for the nation state, then how in a democratic state can users trust those that make the rules? The answer lies partly in constitutional and human rights law and we drill into those functions of TC that makes the TCI provider comparable to state-like and ask what minimal legal guarantees need to be in place to accept, trustingly, this shift of power. Secondly, traditional liberal contract law reduces complex social relations to binary exchange relations, which are not transitive and disrupt rather than create networks. Contract law, as we argue, plays a central role for the way in which the TC provider interacts with his customers and this thesis contributes in speculating of a contract law that does not result in atomism, rather “brings in” potentially affected third parties and results in holistic networks. In the same vein, this thesis looks mainly at specific ways in which law can correct or redefine the implicit and democratically not validated shift of power from customer to TC providers while enhancing the social environment and its social trust within which TC must operate

Bowdoin Orient v.133, no.1-25 (2001-2002)

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