IBM Power System S822LC for Big Data Technical Overview and Introduction

IBM Power System S822LC for Big Data  Technical Overview and Introduction
Author: Scott Vetter,David Barron,Alexandre Bicas Caldeira,Volker Haug,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 88
Release: 2017-08-29
ISBN: 0738455776
Category: Computers
Language: EN, FR, DE, ES & NL

IBM Power System S822LC for Big Data Technical Overview and Introduction Book Excerpt:

This IBM® RedpaperTM publication is a comprehensive guide that covers the IBM Power System S822LC for Big Data (8001-22C) server that uses the latest IBM POWER8® processor technology and supports Linux operating systems (OSs). The objective of this paper is to introduce the Power S822LC for Big Data offerings and their relevant functions as related to targeted application workloads. The new Linux scale-out systems provide differentiated performance, scalability, and low acquisition cost, including: Consolidated server footprint with up to 66% more virtual machines (VMs) per server than competitive x86 servers Superior data throughput and performance for high-value Linux workloads, such as big data, analytic, and industry applications Up to 12 LFF drives that are installed within the chassis to meet storage-rich application requirements Superior application performance due to a 2x per core performance advantage over x86-based systems Leadership data through put enabled by POWER8 multithreading with up to 4x more threads than x86 designs Acceleration of bid data workloads with up to two GPUs and superior I/O bandwidth with Coherent Accelerator Processor Interface (CAPI) This publication is for professionals who want to acquire a better understanding of IBM Power SystemsTM products. The intended audience includes: Clients Sales and marketing professionals Technical support professionals IBM Business Partners Independent software vendors

Implementing an IBM High Performance Computing Solution on IBM Power System S822LC

Implementing an IBM High Performance Computing Solution on IBM Power System S822LC
Author: Dino Quintero,Luis Carlos Cruz Huertas,Tsuyoshi Kamenoue,Wainer dos Santos Moschetta,Mauricio Faria de Oliveira,Georgy E Pavlov,Alexander Pozdneev,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 342
Release: 2016-07-25
ISBN: 0738441872
Category: Computers
Language: EN, FR, DE, ES & NL

Implementing an IBM High Performance Computing Solution on IBM Power System S822LC Book Excerpt:

This IBM® Redbooks® publication demonstrates and documents that IBM Power SystemsTM high-performance computing and technical computing solutions deliver faster time to value with powerful solutions. Configurable into highly scalable Linux clusters, Power Systems offer extreme performance for demanding workloads such as genomics, finance, computational chemistry, oil and gas exploration, and high-performance data analytics. This book delivers a high-performance computing solution implemented on the IBM Power System S822LC. The solution delivers high application performance and throughput based on its built-for-big-data architecture that incorporates IBM POWER8® processors, tightly coupled Field Programmable Gate Arrays (FPGAs) and accelerators, and faster I/O by using Coherent Accelerator Processor Interface (CAPI). This solution is ideal for clients that need more processing power while simultaneously increasing workload density and reducing datacenter floor space requirements. The Power S822LC offers a modular design to scale from a single rack to hundreds, simplicity of ordering, and a strong innovation roadmap for graphics processing units (GPUs). This publication is targeted toward technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) responsible for delivering cost effective high-performance computing (HPC) solutions that help uncover insights from their data so they can optimize business results, product development, and scientific discoveries

Enterprise Data Warehouse Optimization with Hadoop on IBM Power Systems Servers

Enterprise Data Warehouse Optimization with Hadoop on IBM Power Systems Servers
Author: Scott Vetter,Helen Lu,Maciej Olejniczak,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 82
Release: 2018-01-31
ISBN: 0738456608
Category: Computers
Language: EN, FR, DE, ES & NL

Enterprise Data Warehouse Optimization with Hadoop on IBM Power Systems Servers Book Excerpt:

Data warehouses were developed for many good reasons, such as providing quick query and reporting for business operations, and business performance. However, over the years, due to the explosion of applications and data volume, many existing data warehouses have become difficult to manage. Extract, Transform, and Load (ETL) processes are taking longer, missing their allocated batch windows. In addition, data types that are required for business analysis have expanded from structured data to unstructured data. The Apache open source Hadoop platform provides a great alternative for solving these problems. IBM® has committed to open source since the early years of open Linux. IBM and Hortonworks together are committed to Apache open source software more than any other company. IBM Power SystemsTM servers are built with open technologies and are designed for mission-critical data applications. Power Systems servers use technology from the OpenPOWER Foundation, an open technology infrastructure that uses the IBM POWER® architecture to help meet the evolving needs of big data applications. The combination of Power Systems with Hortonworks Data Platform (HDP) provides users with a highly efficient platform that provides leadership performance for big data workloads such as Hadoop and Spark. This IBM RedpaperTM publication provides details about Enterprise Data Warehouse (EDW) optimization with Hadoop on Power Systems. Many people know Power Systems from the IBM AIX® platform, but might not be familiar with IBM PowerLinuxTM, so part of this paper provides a Power Systems overview. A quick introduction to Hadoop is provided for those not familiar with the topic. Details of HDP on Power Reference architecture are included that will help both software architects and infrastructure architects understand the design. In the optimization chapter, we describe various topics: traditional EDW offload, sizing guidelines, performance tuning, IBM Elastic StorageTM Server (ESS) for data-intensive workload, IBM Big SQL as the common structured query language (SQL) engine for Hadoop platform, and tools that are available on Power Systems that are related to EDW optimization. We also dedicate some pages to the analytics components (IBM Data Science Experience (IBM DSX) and IBM SpectrumTM Conductor for Spark workload) for the Hadoop infrastructure.

IBM Power Systems L and LC Server Positioning Guide

IBM Power Systems L and LC Server Positioning Guide
Author: Scott Vetter,Tonny Bastiaans,Andrew Laidlaw,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 32
Release: 2017-02-16
ISBN: 0738455814
Category: Computers
Language: EN, FR, DE, ES & NL

IBM Power Systems L and LC Server Positioning Guide Book Excerpt:

This IBM® RedpaperTM publication is written to assist you in locating the optimal server/workload fit within the IBM Power SystemsTM L and IBM OpenPOWER LC product lines. IBM has announced several scale-out servers, and as a partner in the OpenPOWER organization, unique design characteristics that are engineered into the LC line have broadened the suite of available workloads beyond typical client OS hosting. This paper looks at the benefits of the Power Systems L servers and OpenPOWER LC servers, and how they are different, providing unique benefits for Enterprise workloads and use cases.

IBM Power System E850C Technical Overview and Introduction

IBM Power System E850C Technical Overview and Introduction
Author: Scott Vetter,Alexandre Bicas Caldeira,Volker Haug,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 160
Release: 2017-07-12
ISBN: 0738455687
Category: Computers
Language: EN, FR, DE, ES & NL

IBM Power System E850C Technical Overview and Introduction Book Excerpt:

This IBM® RedpaperTM publication is a comprehensive guide that covers the IBM Power SystemTM E850C (8408-44E) server that supports IBM AIX®, and Linux operating systems. The objective of this paper is to introduce the major innovative Power E850C offerings and their relevant functions. The Power E850C server (8408-44E) is the latest enhancement to the Power Systems portfolio. It offers an improved 4-socket 4U system that delivers faster IBM POWER8® processors up to 4.22 GHz, with up to 4 TB of DDR4 memory, built-in IBM PowerVM® virtualization, and capacity on demand. It also integrates cloud management to help clients deploy scalable, mission-critical business applications in virtualized, private cloud infrastructures. Like its predecessor Power E850 server, which was launched in 2015, the new Power E850C server uses 8-core, 10-core, or 12-core POWER8 processor modules. However, the Power E850C cores are 13%-20% faster and deliver a system with up to 32 cores at 4.22 GHz, up to 40 cores at 3.95 GHz, or up to 48 cores at 3.65 GHz, and use DDR4 memory. A minimum of two processor modules must be installed in each system, with a minimum quantity of one processor module's cores activated. Cloud computing, in its many forms (public, private, or hybrid), is quickly becoming both the delivery and consumption models for IT. However, finding the correct mix between traditional IT, private cloud, and public cloud can be a challenge. The new Power E850C server and IBM Cloud PowerVC manager can enable clients to accelerate the transformation of their IT infrastructure for cloud while providing tremendous flexibility during the transition. IBM Cloud PowerVC Manager provides OpenStack-based cloud management to accelerate and simplify cloud deployment by providing fast and automated VM deployments, prebuilt image templates, and self-service capabilities all with an intuitive interface. PowerVC management upwardly integrates into various third-party hybrid cloud orchestration products, including IBM Cloud Orchestrator, VMware vRealize, and others. Clients can simply manage both their private cloud VMs and their public cloud VMs from a single, integrated management tool. IBM Power Systems is designed to provide the highest levels of reliability, availability, flexibility, and performance to bring you a world-class enterprise private and hybrid cloud infrastructure. Through enterprise-class security, efficient built-in virtualization that drives industry-leading workload density, and dynamic resource allocation and management, the server consistently delivers the highest levels of service across hundreds of virtual workloads on a single system. The Power E850C server includes the cloud management software and services to assist with clients' move to the cloud, both private and hybrid. Those additional capabilities include the following items: Private cloud management with IBM Cloud PowerVC Manager, Cloud-based HMC Apps as a service, and Open source cloud automation and configuration tooling for AIX Hybrid cloud support Hybrid infrastructure management tools Securely connect system of record workloads and data to cloud native applications IBM Cloud Starter Pack Flexible capacity on demand Power to Cloud Services This publication is for professionals who want to acquire a better understanding of IBM Power SystemsTM products. The intended audience includes the following roles: Clients Sales and marketing professionals Technical support professionals IBM Business Partners Independent software vendors This paper expands the current set of IBM Power Systems documentation by providing a desktop reference that offers a detailed technical description of the Power E850C system.

IBM Power System S821LC Technical Overview and Introduction

IBM Power System S821LC Technical Overview and Introduction
Author: Scott Vetter,David Barron,Alexandre Bicas Caldeira,Volker Haug,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 84
Release: 2017-08-29
ISBN: 0738455784
Category: Computers
Language: EN, FR, DE, ES & NL

IBM Power System S821LC Technical Overview and Introduction Book Excerpt:

This IBM® RedpaperTM publication is a comprehensive guide that covers the IBM Power System S821LC (8001-12C) server that uses the latest IBM POWER8® processor technology and supports the Linux operating system (OS). The Power S821LC server is designed to maximize data center floor space with its dense 1U server design, which helps to reduce infrastructure cost. The Power S821LC server delivers superior performance and exceptional throughput for data center and cloud workloads that require dense virtualization, open source database deployment, and high-performance computing applications. The Power S821LC server supports up to two processor sockets, offering 16-core 2.328 GHz (3.026 GHz turbo) or 20-core 2.095 GHz (2.827 GHz turbo) POWER8 configurations in a 19-inch rack-mount, 1U (EIA units) drawer configuration. All the cores are activated. The objective of this paper is to introduce the Power S821LC offering and its relevant functions, including: Two POWER8 processors in a 1U form factor Dense virtualization and dense database deployment capability-providing more value per server footprint than 1U x86-based alternatives Leadership data throughput that is enabled by POWER8 multithreading with up to 4X more threads than x86 designs Superior application performance due to 2x per core performance advantage over x86-based systems Acceleration of a broad range of workloads with GPUs and superior I/O bandwidth with Coherent Accelerator Processor Interface (CAPI) This publication is for professionals who want to acquire a better understanding of IBM Power SystemsTM products. The intended audience includes the following roles: Clients Sales and marketing professionals Technical support professionals IBM Business Partners Independent software vendors This paper expands the current set of IBM Power Systems documentation by providing a desktop reference that offers a detailed technical description of the Power S821LC system.

IBM Power Systems E870C and E880C Technical Overview and Introduction

IBM Power Systems E870C and E880C Technical Overview and Introduction
Author: Scott Vetter,Alexandre Bicas Caldeira,Volker Haug,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 166
Release: 2018-11-14
ISBN: 0738455636
Category: Computers
Language: EN, FR, DE, ES & NL

IBM Power Systems E870C and E880C Technical Overview and Introduction Book Excerpt:

This IBM® RedpaperTM publication is a comprehensive guide that covers the IBM Power® System E870C (9080-MME) and IBM Power System E880C (9080-MHE) servers that support IBM AIX®, IBM i, and Linux operating systems. The objective of this paper is to introduce the major innovative Power E870C and Power E880C offerings and their relevant functions. The new Power E870C and Power E880C servers with OpenStack-based cloud management and open source automation enables clients to accelerate the transformation of their IT infrastructure for cloud while providing tremendous flexibility during the transition. In addition, the Power E870C and Power E880C models provide clients increased security, high availability, rapid scalability, simplified maintenance, and management, all while enabling business growth and dramatically reducing costs. The systems management capability of the Power E870C and Power E880C servers speeds up and simplifies cloud deployment by providing fast and automated VM deployments, prebuilt image templates, and self-service capabilities, all with an intuitive interface. Enterprise servers provide the highest levels of reliability, availability, flexibility, and performance to bring you a world-class enterprise private and hybrid cloud infrastructure. Through enterprise-class security, efficient built-in virtualization that drives industry-leading workload density, and dynamic resource allocation and management, the server consistently delivers the highest levels of service across hundreds of virtual workloads on a single system. The Power E870C and Power E880C server includes the cloud management software and services to assist with clients' move to the cloud, both private and hybrid. The following capabilities are included: Private cloud management with IBM Cloud PowerVC Manager, Cloud-based HMC Apps as a service, and open source cloud automation and configuration tooling for AIX Hybrid cloud support Hybrid infrastructure management tools Securely connect system of record workloads and data to cloud native applications IBM Cloud Starter Pack Flexible capacity on demand Power to Cloud Services This paper expands the current set of IBM Power SystemsTM documentation by providing a desktop reference that offers a detailed technical description of the Power E870C and Power E880C systems. This paper does not replace the latest marketing materials and configuration tools. It is intended as another source of information that, together with existing sources, can be used to enhance your knowledge of IBM server solutions.

AI and Big Data on IBM Power Systems Servers

AI and Big Data on IBM Power Systems Servers
Author: Scott Vetter,Ivaylo B. Bozhinov,Anto A John,Rafael Freitas de Lima,Ahmed.(Mash) Mashhour,James Van Oosten,Fernando Vermelho,Allison White,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 162
Release: 2019-04-10
ISBN: 0738457515
Category: Computers
Language: EN, FR, DE, ES & NL

AI and Big Data on IBM Power Systems Servers Book Excerpt:

As big data becomes more ubiquitous, businesses are wondering how they can best leverage it to gain insight into their most important business questions. Using machine learning (ML) and deep learning (DL) in big data environments can identify historical patterns and build artificial intelligence (AI) models that can help businesses to improve customer experience, add services and offerings, identify new revenue streams or lines of business (LOBs), and optimize business or manufacturing operations. The power of AI for predictive analytics is being harnessed across all industries, so it is important that businesses familiarize themselves with all of the tools and techniques that are available for integration with their data lake environments. In this IBM® Redbooks® publication, we cover the best practices for deploying and integrating some of the best AI solutions on the market, including: IBM Watson Machine Learning Accelerator (see note for product naming) IBM Watson Studio Local IBM Power SystemsTM IBM SpectrumTM Scale IBM Data Science Experience (IBM DSX) IBM Elastic StorageTM Server Hortonworks Data Platform (HDP) Hortonworks DataFlow (HDF) H2O Driverless AI We map out all the integrations that are possible with our different AI solutions and how they can integrate with your existing or new data lake. We also walk you through some of our client use cases and show you how some of the industry leaders are using Hortonworks, IBM PowerAI, and IBM Watson Studio Local to drive decision making. We also advise you on your deployment options, when to use a GPU, and why you should use the IBM Elastic Storage Server (IBM ESS) to improve storage management. Lastly, we describe how to integrate IBM Watson Machine Learning Accelerator and Hortonworks with or without IBM Watson Studio Local, how to access real-time data, and security. Note: IBM Watson Machine Learning Accelerator is the new product name for IBM PowerAI Enterprise. Note: Hortonworks merged with Cloudera in January 2019. The new company is called Cloudera. References to Hortonworks as a business entity in this publication are now referring to the merged company. Product names beginning with Hortonworks continue to be marketed and sold under their original names.

POWER8 High performance Computing Guide IBM Power System S822LC 8335 GTB Edition

POWER8 High performance Computing Guide IBM Power System S822LC  8335 GTB  Edition
Author: Dino Quintero,Joseph Apuzzo,John Dunham,Mauricio Faria de Oliveira,Markus Hilger,Desnes Augusto Nunes Rosario,Wainer dos Santos Moschetta,Alexander Pozdneev,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 398
Release: 2017-08-04
ISBN: 0738442550
Category: Computers
Language: EN, FR, DE, ES & NL

POWER8 High performance Computing Guide IBM Power System S822LC 8335 GTB Edition Book Excerpt:

This IBM® Redbooks® publication documents and addresses topics to provide step-by-step customizable application and programming solutions to tune application and workloads to use IBM Power SystemsTM hardware architecture. This publication explores, tests, and documents the solution to use the architectural technologies and the software solutions that are available from IBM to help solve challenging technical and business problems. This publication also demonstrates and documents that the combination of IBM high-performance computing (HPC) solutions (hardware and software) delivers significant value to technical computing clients who are in need of cost-effective, highly scalable, and robust solutions. First, the book provides a high-level overview of the HPC solution, including all of the components that makes the HPC cluster: IBM Power System S822LC (8335-GTB), software components, interconnect switches, and the IBM SpectrumTM Scale parallel file system. Then, the publication is divided in three parts: Part 1 focuses on the developers, Part 2 focuses on the administrators, and Part 3 focuses on the evaluators and planners of the solution. The IBM Redbooks publication is targeted toward technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for delivering cost-effective HPC solutions that help uncover insights from vast amounts of client's data so they can optimize business results, product development, and scientific discoveries.

IBM Open Platform for DBaaS on IBM Power Systems

IBM Open Platform for DBaaS on IBM Power Systems
Author: Dino Quintero,Fabio Martins,Eduardo Luis Cerdas Moya,Rafael Camarda Silva Folco,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 234
Release: 2018-03-26
ISBN: 0738442798
Category: Computers
Language: EN, FR, DE, ES & NL

IBM Open Platform for DBaaS on IBM Power Systems Book Excerpt:

This IBM Redbooks publication describes how to implement an Open Platform for Database as a Service (DBaaS) on IBM Power Systems environment for Linux, and demonstrate the open source tools, optimization and best practices guidelines for it. Open Platform for DBaaS on Power Systems is an on-demand, secure, and scalable self-service database platform that automates provisioning and administration of databases to support new business applications and information insights. This publication addresses topics to help sellers, architects, brand specialists, distributors, resellers and anyone offering secure and scalable Open Platform for DBaaS on Power Systems solution with APIs that are consistent across heterogeneous open database types. An Open Platform for DBaaS on Power Systems solution has the capability to accelerate business success by providing an infrastructure, and tools leveraging Open Source and OpenStack software engineered to optimize hardware and software between workloads and resources so you have a responsive, and an adaptive environment. Moreover, this publication provides documentation to transfer the how-to-skills for cloud oriented operational management of Open Platform for DBaaS on Power Systems service and underlying infrastructure to the technical teams. Open Platform for DBaaS on Power Systems mission is to provide scalable and reliable cloud database as a service provisioning functionality for both relational and non-relational database engines, and to continue to improve its fully-featured and extensible open source framework. For example, Trove is a database as a service for OpenStack. It is designed to run entirely on OpenStack, with the goal of allowing users to quickly and easily utilize the features of a relational or non-relational database without the burden of handling complex administrative tasks. Cloud users and database administrators can provision and manage multiple database instances as needed. Initially, the service focuses on providing resource isolation at high performance while automating complex administrative tasks including deployment, configuration, patching, backups, restores, and monitoring. In the context of this publication, the monitoring tool implemented is Nagios Core which is an open source monitoring tool. Hence, when you see a reference of Nagios in this book, Nagios Core is the open source monitoring solution implemented. Also note that the implementation of Open Platform for DBaaS on IBM Power Systems is based on open source solutions. This book is targeted toward sellers, architects, brand specialists, distributors, resellers and anyone developing and implementing Open Platform for DBaaS on Power Systems solutions.

IBM PowerAI Deep Learning Unleashed on IBM Power Systems Servers

IBM PowerAI  Deep Learning Unleashed on IBM Power Systems Servers
Author: Dino Quintero,Bing He,Bruno C. Faria,Alfonso Jara,Chris Parsons,Shota Tsukamoto,Richard Wale,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 278
Release: 2019-06-05
ISBN: 0738442941
Category: Computers
Language: EN, FR, DE, ES & NL

IBM PowerAI Deep Learning Unleashed on IBM Power Systems Servers Book Excerpt:

This IBM® Redbooks® publication is a guide about the IBM PowerAI Deep Learning solution. This book provides an introduction to artificial intelligence (AI) and deep learning (DL), IBM PowerAI, and components of IBM PowerAI, deploying IBM PowerAI, guidelines for working with data and creating models, an introduction to IBM SpectrumTM Conductor Deep Learning Impact (DLI), and case scenarios. IBM PowerAI started as a package of software distributions of many of the major DL software frameworks for model training, such as TensorFlow, Caffe, Torch, Theano, and the associated libraries, such as CUDA Deep Neural Network (cuDNN). The IBM PowerAI software is optimized for performance by using the IBM Power SystemsTM servers that are integrated with NVLink. The AI stack foundation starts with servers with accelerators. graphical processing unit (GPU) accelerators are well-suited for the compute-intensive nature of DL training, and servers with the highest CPU to GPU bandwidth, such as IBM Power Systems servers, enable the high-performance data transfer that is required for larger and more complex DL models. This publication targets technical readers, including developers, IT specialists, systems architects, brand specialist, sales team, and anyone looking for a guide about how to understand the IBM PowerAI Deep Learning architecture, framework configuration, application and workload configuration, and user infrastructure.

IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences

IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences
Author: Dino Quintero,Frank N. Lee,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 89
Release: 2019-09-08
ISBN: 073845690X
Category: Computers
Language: EN, FR, DE, ES & NL

IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences Book Excerpt:

This IBM® Redpaper publication provides an update to the original description of IBM Reference Architecture for Genomics. This paper expands the reference architecture to cover all of the major vertical areas of healthcare and life sciences industries, such as genomics, imaging, and clinical and translational research. The architecture was renamed IBM Reference Architecture for High Performance Data and AI in Healthcare and Life Sciences to reflect the fact that it incorporates key building blocks for high-performance computing (HPC) and software-defined storage, and that it supports an expanding infrastructure of leading industry partners, platforms, and frameworks. The reference architecture defines a highly flexible, scalable, and cost-effective platform for accessing, managing, storing, sharing, integrating, and analyzing big data, which can be deployed on-premises, in the cloud, or as a hybrid of the two. IT organizations can use the reference architecture as a high-level guide for overcoming data management challenges and processing bottlenecks that are frequently encountered in personalized healthcare initiatives, and in compute-intensive and data-intensive biomedical workloads. This reference architecture also provides a framework and context for modern healthcare and life sciences institutions to adopt cutting-edge technologies, such as cognitive life sciences solutions, machine learning and deep learning, Spark for analytics, and cloud computing. To illustrate these points, this paper includes case studies describing how clients and IBM Business Partners alike used the reference architecture in the deployments of demanding infrastructures for precision medicine. This publication targets technical professionals (consultants, technical support staff, IT Architects, and IT Specialists) who are responsible for providing life sciences solutions and support.

High Performance Computing

High Performance Computing
Author: Esteban Meneses,Harold Castro,Carlos Jaime Barrios Hernández,Raul Ramos-Pollan
Publsiher: Springer
Total Pages: 338
Release: 2019-03-30
ISBN: 3030162052
Category: Computers
Language: EN, FR, DE, ES & NL

High Performance Computing Book Excerpt:

This book constitutes the proceedings of the 5th Latin American Conference, CARLA 2018, held in Bucaramanga, Colombia, in September 2018. The 24 papers presented in this volume were carefully reviewed and selected from 38 submissions. They are organized in topical sections on: Artificial Intelligence; Accelerators; Applications; Performance Evaluation; Platforms and Infrastructures; Cloud Computing.

High Performance Computing

High Performance Computing
Author: Michèle Weiland,Guido Juckeland,Sadaf Alam,Heike Jagode
Publsiher: Springer Nature
Total Pages: 659
Release: 2019-12-02
ISBN: 3030343561
Category: Computers
Language: EN, FR, DE, ES & NL

High Performance Computing Book Excerpt:

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.

High Performance Computing

High Performance Computing
Author: Julian M. Kunkel,Rio Yokota,Michela Taufer,John Shalf
Publsiher: Springer
Total Pages: 743
Release: 2017-10-18
ISBN: 331967630X
Category: Computers
Language: EN, FR, DE, ES & NL

High Performance Computing Book Excerpt:

This book constitutes revised selected papers from 10 workshops that were held as the ISC High Performance 2017 conference in Frankfurt, Germany, in June 2017. The 59 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They stem from the following workshops: Workshop on Virtualization in High-Performance Cloud Computing (VHPC) Visualization at Scale: Deployment Case Studies and Experience Reports International Workshop on Performance Portable Programming Models for Accelerators (P^3MA) OpenPOWER for HPC (IWOPH) International Workshop on Data Reduction for Big Scientific Data (DRBSD) International Workshop on Communication Architectures for HPC, Big Data, Deep Learning and Clouds at Extreme Scale Workshop on HPC Computing in a Post Moore's Law World (HCPM) HPC I/O in the Data Center ( HPC-IODC) Workshop on Performance and Scalability of Storage Systems (WOPSSS) IXPUG: Experiences on Intel Knights Landing at the One Year Mark International Workshop on Communication Architectures for HPC, Big Data, Deep Learning and Clouds at Extreme Scale (ExaComm)

A Greater Foundation for Machine Learning Engineering

A Greater Foundation for Machine Learning Engineering
Author: Dr. Ganapathi Pulipaka
Publsiher: Xlibris Corporation
Total Pages: 510
Release: 2021-10-01
ISBN: 1664151273
Category: Computers
Language: EN, FR, DE, ES & NL

A Greater Foundation for Machine Learning Engineering Book Excerpt:

This research scholarly illustrated book has more than 250 illustrations. The simple models of supervised machine learning with Gaussian Naïve Bayes, Naïve Bayes, decision trees, classification rule learners, linear regression, logistic regression, local polynomial regression, regression trees, model trees, K-nearest neighbors, and support vector machines lay a more excellent foundation for statistics. The author of the book Dr. Ganapathi Pulipaka, a top influencer of machine learning in the US, has created this as a reference book for universities. This book contains an incredible foundation for machine learning and engineering beyond a compact manual. The author goes to extraordinary lengths to make academic machine learning and deep learning literature comprehensible to create a new body of knowledge. The book aims at readership from university students, enterprises, data science beginners, machine learning and deep learning engineers at scale for high-performance computing environments. A Greater Foundation of Machine Learning Engineering covers a broad range of classical linear algebra and calculus with program implementations in PyTorch, TensorFlow, R, and Python with in-depth coverage. The author does not hesitate to go into math equations for each algorithm at length that usually many foundational machine learning books lack leveraging the JupyterLab environment. Newcomers can leverage the book from University or people from all walks of data science or software lives to the advanced practitioners of machine learning and deep learning. Though the book title suggests machine learning, there are several implementations of deep learning algorithms, including deep reinforcement learning. The book's mission is to help build a strong foundation for machine learning and deep learning engineers with all the algorithms, processors to train and deploy into production for enterprise-wide machine learning implementations. This book also introduces all the concepts of natural language processing required for machine learning algorithms in Python. The book covers Bayesian statistics without assuming high-level mathematics or statistics experience from the readers. It delivers the core concepts and implementations required with R code with open datasets. The book also covers unsupervised machine learning algorithms with association rules and k-means clustering, metal-learning algorithms, bagging, boosting, random forests, and ensemble methods. The book delves into the origins of deep learning in a scholarly way covering neural networks, restricted Boltzmann machines, deep belief networks, autoencoders, deep Boltzmann machines, LSTM, and natural language processing techniques with deep learning algorithms and math equations. It leverages the NLTK library of Python with PyTorch, Python, and TensorFlow's installation steps, then demonstrates how to build neural networks with TensorFlow. Deploying machine learning algorithms require a blend of cloud computing platforms, SQL databases, and NoSQL databases. Any data scientist with a statistics background that looks to transition into a machine learning engineer role requires an in-depth understanding of machine learning project implementations on Amazon, Google, or Microsoft Azure cloud computing platforms. The book provides real-world client projects for understanding the complete implementation of machine learning algorithms. This book is a marvel that does not leave any application of machine learning and deep learning algorithms. It sets a more excellent foundation for newcomers and expands the horizons for experienced deep learning practitioners. It is almost inevitable that there will be a series of more advanced algorithms follow-up books from the author in some shape or form after setting such a perfect foundation for machine learning engineering.

Cognitive Computing Featuring the IBM Power System AC922

Cognitive Computing Featuring the IBM Power System AC922
Author: Scott Vetter,Ivaylo Bozhinov,Boran Lee,Gustavo Santos,IBM Redbooks
Publsiher: IBM Redbooks
Total Pages: 55
Release: 2019-10-17
ISBN: 0738458112
Category: Computers
Language: EN, FR, DE, ES & NL

Cognitive Computing Featuring the IBM Power System AC922 Book Excerpt:

This IBM® Redpaper publication describes the advantages of using IBM Power System AC922 for cognitive solutions, and how it can enhance clients' businesses. In order to optimize the hardware and software, IBM partners with NVIDIA, Mellanox, H2O.ai, SQream, Kinetica, and other prominent companies to design the Power AC922 server, specifically enhanced for the cognitive era. Most of its outstanding hardware features, such as NVIDIA NVLink 2.0 and PCIe 4.0, are described in this publication to illustrate the advantages that clients can realize in comparison with IBM competitors. We also include a brief description about what cognitive computing is, and how to use IBM Watson® Machine Learning cognitive solutions to bring more value to your business ecosystem. Additionally, we show performance charts that show the advantages of using Power AC922 versus x86 competitors. In the last chapter, we describe the most remarkable use cases in which IBM solves real problems using cognitive solutions. This IBM Redpaper publication is aimed at IT technical audiences, especially decision-making levels that need a full look at the benefits and improvements that an IBM Cognitive Solution can offer. It also provides valuable information to data science professionals, enabling them to plan their modeling needs. Finally, it offers information to the infrastructure support group in charge of maintaining the solution.

Neural Information Processing

Neural Information Processing
Author: Tom Gedeon,Kok Wai Wong,Minho Lee
Publsiher: Springer Nature
Total Pages: 792
Release: 2019-12-05
ISBN: 3030368025
Category: Computers
Language: EN, FR, DE, ES & NL

Neural Information Processing Book Excerpt:

The two-volume set CCIS 1142 and 1143 constitutes thoroughly refereed contributions presented at the 26th International Conference on Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019. For ICONIP 2019 a total of 345 papers was carefully reviewed and selected for publication out of 645 submissions. The 168 papers included in this volume set were organized in topical sections as follows: adversarial networks and learning; convolutional neural networks; deep neural networks; embeddings and feature fusion; human centred computing; human centred computing and medicine; human centred computing for emotion; hybrid models; image processing by neural techniques; learning from incomplete data; model compression and optimization; neural network applications; neural network models; semantic and graph based approaches; social network computing; spiking neuron and related models; text computing using neural techniques; time-series and related models; and unsupervised neural models.

Medical Image Computing and Computer Assisted Intervention MICCAI 2019

Medical Image Computing and Computer Assisted Intervention     MICCAI 2019
Author: Dinggang Shen,Tianming Liu,Terry M. Peters,Lawrence H. Staib,Caroline Essert,Sean Zhou,Pew-Thian Yap,Ali Khan
Publsiher: Springer Nature
Total Pages: 888
Release: 2019-10-10
ISBN: 3030322483
Category: Computers
Language: EN, FR, DE, ES & NL

Medical Image Computing and Computer Assisted Intervention MICCAI 2019 Book Excerpt:

The six-volume set LNCS 11764, 11765, 11766, 11767, 11768, and 11769 constitutes the refereed proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, held in Shenzhen, China, in October 2019. The 539 revised full papers presented were carefully reviewed and selected from 1730 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: optical imaging; endoscopy; microscopy. Part II: image segmentation; image registration; cardiovascular imaging; growth, development, atrophy and progression. Part III: neuroimage reconstruction and synthesis; neuroimage segmentation; diffusion weighted magnetic resonance imaging; functional neuroimaging (fMRI); miscellaneous neuroimaging. Part IV: shape; prediction; detection and localization; machine learning; computer-aided diagnosis; image reconstruction and synthesis. Part V: computer assisted interventions; MIC meets CAI. Part VI: computed tomography; X-ray imaging.