Fpga Accelerated Analytics

DOWNLOAD
Download Fpga Accelerated Analytics PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Fpga Accelerated Analytics book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Fpga Accelerated Analytics
DOWNLOAD
Author : Zsolt István
language : en
Publisher:
Release Date : 2020-09-28
Fpga Accelerated Analytics written by Zsolt István and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-28 with categories.
Datacenters hosting the data-intensive applications used in machine learning and online services are facing an important challenge: the amount of data that needs to be stored and processed is increasing at an exponential rate whereas traditional processor performance has been stagnating for years as Moore's Law tapers off. Driven by these trends, data processing and management applications have become increasingly distributed leading to new data movement bottlenecks at various levels of the software and hardware architecture. The authors show how specialized hardware accelerators can provide an answer to the compute stagnation problem and be helpful in reducing data movement bottlenecks by placing them in the right location within the computer architecture. They concentrate on Field Programmable Gate Arrays (FPGAs) and show how they make it possible to express algorithms in ways that are fundamentally different from CPUs or GPUs. Many major companies are using these accelerator techniques in their storage and processing offerings. The authors discuss the benefits of using FPGAs in the context of analytical processing, both as an accelerator within a single node database and as part of distributed data analytics pipelines. They present guidelines for accelerator design in both scenarios and examples of integration within full-fledged Relational Databases. They do so through the prism of recent research projects that explore how emerging compute-intensive operations in databases can benefit from FPGAs. Finally, they highlight future research challenges in programmability and integration and cover architectural trends that are propelling the rapid adoption of accelerators in datacenters and the cloud. The monograph provides researchers and practitioners a concise insight into how FPGAs can play an important role in designing modern data-intensive computing systems. Drawing on both theory and practical implementations the readers are brought quickly up to speed on a technique that will significantly improve a system's performance.
Security Of Fpga Accelerated Cloud Computing Environments
DOWNLOAD
Author : Jakub Szefer
language : en
Publisher: Springer Nature
Release Date : 2023-12-28
Security Of Fpga Accelerated Cloud Computing Environments written by Jakub Szefer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-28 with Technology & Engineering categories.
This book addresses security of FPGA-accelerated cloud computing environments. It presents a comprehensive review of the state-of-the-art in security threats as well as defenses. The book further presents design principles to help in the evaluation and designs of cloud-based FPGA deployments which are secure from information leaks and potential attacks.
Analyzing Analytics
DOWNLOAD
Author : Rajesh Bordawekar
language : en
Publisher: Springer Nature
Release Date : 2022-05-31
Analyzing Analytics written by Rajesh Bordawekar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-31 with Technology & Engineering categories.
This book aims to achieve the following goals: (1) to provide a high-level survey of key analytics models and algorithms without going into mathematical details; (2) to analyze the usage patterns of these models; and (3) to discuss opportunities for accelerating analytics workloads using software, hardware, and system approaches. The book first describes 14 key analytics models (exemplars) that span data mining, machine learning, and data management domains. For each analytics exemplar, we summarize its computational and runtime patterns and apply the information to evaluate parallelization and acceleration alternatives for that exemplar. Using case studies from important application domains such as deep learning, text analytics, and business intelligence (BI), we demonstrate how various software and hardware acceleration strategies are implemented in practice. This book is intended for both experienced professionals and students who are interested in understanding core algorithms behind analytics workloads. It is designed to serve as a guide for addressing various open problems in accelerating analytics workloads, e.g., new architectural features for supporting analytics workloads, impact on programming models and runtime systems, and designing analytics systems.
Emerging Technology And Architecture For Big Data Analytics
DOWNLOAD
Author : Anupam Chattopadhyay
language : en
Publisher: Springer
Release Date : 2017-04-19
Emerging Technology And Architecture For Big Data Analytics written by Anupam Chattopadhyay and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-19 with Technology & Engineering categories.
This book describes the current state of the art in big-data analytics, from a technology and hardware architecture perspective. The presentation is designed to be accessible to a broad audience, with general knowledge of hardware design and some interest in big-data analytics. Coverage includes emerging technology and devices for data-analytics, circuit design for data-analytics, and architecture and algorithms to support data-analytics. Readers will benefit from the realistic context used by the authors, which demonstrates what works, what doesn’t work, and what are the fundamental problems, solutions, upcoming challenges and opportunities. Provides a single-source reference to hardware architectures for big-data analytics; Covers various levels of big-data analytics hardware design abstraction and flow, from device, to circuits and systems; Demonstrates how non-volatile memory (NVM) based hardware platforms can be a viable solution to existing challenges in hardware architecture for big-data analytics.
Hybrid Analytics Solution Using Ibm Db2 Analytics Accelerator For Z Os V3 1
DOWNLOAD
Author : Paolo Bruni
language : en
Publisher: IBM Redbooks
Release Date : 2013-09-27
Hybrid Analytics Solution Using Ibm Db2 Analytics Accelerator For Z Os V3 1 written by Paolo Bruni and has been published by IBM Redbooks this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-09-27 with Computers categories.
The IBM® DB2® Analytics Accelerator Version 3.1 for IBM z/OS® (simply called Accelerator in this book) is a union of the IBM System z® quality of service and IBM Netezza® technology to accelerate complex queries in a DB2 for z/OS highly secure and available environment. Superior performance and scalability with rapid appliance deployment provide an ideal solution for complex analysis. In this IBM Redbooks® publication, we provide technical decision-makers with a broad understanding of the benefits of Version 3.1 of the Accelerator's major new functions. We describe their installation and the advantages to existing analytical processes as measured in our test environment. We also describe the IBM zEnterprise® Analytics System 9700, a hybrid System z solution offering that is surrounded by a complete set of optional packs to enable customers to custom tailor the system to their unique needs..
Iot And Analytics For Sensor Networks
DOWNLOAD
Author : Padmalaya Nayak
language : en
Publisher: Springer Nature
Release Date : 2021-09-11
Iot And Analytics For Sensor Networks written by Padmalaya Nayak and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-11 with Technology & Engineering categories.
This book includes high-quality research papers presented at the 1st International Conference on Wireless Sensor Networks, Ubiquitous Computing and Applications (ICWSNUCA, 2021), which is held at Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India, during 26–27 February, 2021. This volume focuses on the applications, use-cases, architectures, deployments, and recent advances of wireless sensor networks as well as ubiquious computing. Different research topics are illustrated in this book, like wireless sensor networks for the Internet of Things; IoT applications for eHealth; smart cities; architectures for WSNs and IoT, WSNs hardware and new devices; low-power wireless technologies; wireless ad hoc sensor networks; routing and data transfer in WSNs; multicast communication in WSNs; security management in WSNs and in IoT systems; and power consumption optimization in WSNs.
Data Driven Mining Learning And Analytics For Secured Smart Cities
DOWNLOAD
Author : Chinmay Chakraborty
language : en
Publisher: Springer Nature
Release Date : 2021-04-28
Data Driven Mining Learning And Analytics For Secured Smart Cities written by Chinmay Chakraborty and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Computers categories.
This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.
High Performance Computing
DOWNLOAD
Author : Michèle Weiland
language : en
Publisher: Springer Nature
Release Date : 2019-12-02
High Performance Computing written by Michèle Weiland and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-02 with Computers categories.
This book constitutes the refereed post-conference proceedings of 13 workshops held at the 34th International ISC High Performance 2019 Conference, in Frankfurt, Germany, in June 2019: HPC I/O in the Data Center (HPC-IODC), Workshop on Performance & Scalability of Storage Systems (WOPSSS), Workshop on Performance & Scalability of Storage Systems (WOPSSS), 13th Workshop on Virtualization in High-Performance Cloud Computing (VHPC '18), 3rd International Workshop on In Situ Visualization: Introduction and Applications, ExaComm: Fourth International Workshop on Communication Architectures for HPC, Big Data, Deep Learning and Clouds at Extreme Scale, International Workshop on OpenPOWER for HPC (IWOPH18), IXPUG Workshop: Many-core Computing on Intel, Processors: Applications, Performance and Best-Practice Solutions, Workshop on Sustainable Ultrascale Computing Systems, Approximate and Transprecision Computing on Emerging Technologies (ATCET), First Workshop on the Convergence of Large Scale Simulation and Artificial Intelligence, 3rd Workshop for Open Source Supercomputing (OpenSuCo), First Workshop on Interactive High-Performance Computing, Workshop on Performance Portable Programming Models for Accelerators (P^3MA). The 48 full papers included in this volume were carefully reviewed and selected. They cover all aspects of research, development, and application of large-scale, high performance experimental and commercial systems. Topics include HPC computer architecture and hardware; programming models, system software, and applications; solutions for heterogeneity, reliability, power efficiency of systems; virtualization and containerized environments; big data and cloud computing; and artificial intelligence.
Computational Intelligence And Data Analytics
DOWNLOAD
Author : Alejandro C. Frery
language : en
Publisher: Springer Nature
Release Date : 2025-05-03
Computational Intelligence And Data Analytics written by Alejandro C. Frery and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-03 with Computers categories.
This book presents high-quality research papers presented at the International Conference on Computational Intelligence and Data Analytics (ICCIDA 2024), organized by the Department of Information Technology, Vasavi College of Engineering, Hyderabad, India, in June 2024. ICCIDA provides an excellent platform for exchanging knowledge with the global community of scientists, engineers, and educators. This book covers cutting-edge research in two prominent areas—computational intelligence and data analytics and allied research areas.
Practical Big Data Analytics
DOWNLOAD
Author : Nataraj Dasgupta
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-01-15
Practical Big Data Analytics written by Nataraj Dasgupta and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-15 with Computers categories.
Get command of your organizational Big Data using the power of data science and analytics Key Features A perfect companion to boost your Big Data storing, processing, analyzing skills to help you take informed business decisions Work with the best tools such as Apache Hadoop, R, Python, and Spark for NoSQL platforms to perform massive online analyses Get expert tips on statistical inference, machine learning, mathematical modeling, and data visualization for Big Data Book Description Big Data analytics relates to the strategies used by organizations to collect, organize and analyze large amounts of data to uncover valuable business insights that otherwise cannot be analyzed through traditional systems. Crafting an enterprise-scale cost-efficient Big Data and machine learning solution to uncover insights and value from your organization's data is a challenge. Today, with hundreds of new Big Data systems, machine learning packages and BI Tools, selecting the right combination of technologies is an even greater challenge. This book will help you do that. With the help of this guide, you will be able to bridge the gap between the theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on exposure to Hadoop and Spark, build machine learning dashboards using R and R Shiny, create web-based apps using NoSQL databases such as MongoDB and even learn how to write R code for neural networks. By the end of the book, you will have a very clear and concrete understanding of what Big Data analytics means, how it drives revenues for organizations, and how you can develop your own Big Data analytics solution using different tools and methods articulated in this book. What you will learn - Get a 360-degree view into the world of Big Data, data science and machine learning - Broad range of technical and business Big Data analytics topics that caters to the interests of the technical experts as well as corporate IT executives - Get hands-on experience with industry-standard Big Data and machine learning tools such as Hadoop, Spark, MongoDB, KDB+ and R - Create production-grade machine learning BI Dashboards using R and R Shiny with step-by-step instructions - Learn how to combine open-source Big Data, machine learning and BI Tools to create low-cost business analytics applications - Understand corporate strategies for successful Big Data and data science projects - Go beyond general-purpose analytics to develop cutting-edge Big Data applications using emerging technologies Who this book is for The book is intended for existing and aspiring Big Data professionals who wish to become the go-to person in their organization when it comes to Big Data architecture, analytics, and governance. While no prior knowledge of Big Data or related technologies is assumed, it will be helpful to have some programming experience.