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By: IBM     Published Date: Sep 02, 2014
Life Sciences organizations need to be able to build IT infrastructures that are dynamic, scalable, easy to deploy and manage, with simplified provisioning, high performance, high utilization and able to exploit both data intensive and server intensive workloads, including Hadop MapReduce. Solutions must scale, both in terms of processing and storage, in order to better serve the institution long-term. There is a life cycle management of data, and making it useable for mainstream analyses and applications is an important aspect in system design. This presentation will describe IT requirements and how Technical Computing solutions from IBM and Platform Computing will address these challenges and deliver greater ROI and accelerated time to results for Life Sciences.
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     IBM
By: IBM     Published Date: Sep 02, 2014
Whether in high-performance computing, Big Data or analytics, information technology has become an essential tool in today’s hyper-competitive business landscape. Organizations are increasingly being challenged to do more with less and this is fundamentally impacting the way that IT infrastructure is deployed and managed. In this short e-book, learn the top ten ways that IBM Platform Computing customers are using technologies like IBM Platform LSF and IBM Platform Symphony to help obtain results faster, share resources more efficiently, and improve the overall cost-effectiveness of their global IT infrastructure.
Tags : ibm, ibm platform computing, save money
     IBM
By: IBM     Published Date: Sep 02, 2014
IBM Platform Computing Cloud Service lets users economically add computing capacity by accessing ready-to-use clusters in the cloud-delivering high performance that compares favorably to cloud offerings from other providers. Tests show that the IBM service delivers the best (or ties for the best) absolute performance in all test categories. Learn More.
Tags : ibm, platform computing, cloud services, benchmark performance
     IBM
By: IBM     Published Date: Sep 02, 2014
With tougher regulations and continuing market volatility, financial firms are moving to active risk management with a focus on counterparty risk. Firms are revamping their risk and trading practices from top to bottom. They are adopting new risk models and frameworks that support a holistic view of risk. Banks recognize that technology is critical for this transformation, and are adding state-of-the-art enterprise risk management solutions, high performance data and grid management software, and fast hardware. Join IBM Algorithmics and IBM Platform Computing to gain insights on this trend and on technologies for enabling active "real-time" risk management.
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     IBM
By: IBM     Published Date: May 20, 2015
Whether in high-performance computing, Big Data or analytics, information technology has become an essential tool in today’s hyper-competitive business landscape. Organizations are increasingly being challenged to do more with less and this is fundamentally impacting the way that IT infrastructure is deployed and managed. In this short e-book, learn the top ten ways that IBM Platform Computing customers are using technologies like IBM Platform LSF and IBM Platform Symphony to help obtain results faster, share resources more efficiently, and improve the overall cost-effectiveness of their global IT infrastructure.
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     IBM
By: IBM     Published Date: May 20, 2015
IBM Platform Symphony - accelerate big data analytics – This demonstration will highlight the benefits and features of IBM Platform Symphony to accelerate big data analytics by maximizing distributed system performance, fully utilizing computing resources and effectively harnessing the power of Hadoop.
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     IBM
By: IBM     Published Date: May 20, 2015
According to our global study of more than 800 cloud decision makers and users are becoming increasingly focused on the business value cloud provides. Cloud is integral to mobile, social and analytics initiatives – and the big data management challenge that often comes with them and it helps power the entire suite of game-changing technologies. Enterprises can aim higher when these deployments are riding on the cloud. Mobile, analytics and social implementations can be bigger, bolder and drive greater impact when backed by scalable infrastructure. In addition to scale, cloud can provide integration, gluing the individual technologies into more cohesive solutions. Learn how companies are gaining a competitive advanatge with cloud computing.
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By: IBM     Published Date: Sep 16, 2015
6 criteria for evaluating a high-performance cloud services providers Engineering, scientific, analytics, big data and research workloads place extraordinary demands on technical and high-performance computing (HPC) infrastructure. Supporting these workloads can be especially challenging for organizations that have unpredictable spikes in resource demand, or need access to additional compute or storage resources for a project or to support a growing business. Software Defined Infrastructure (SDI) enables organizations to deliver HPC services in the most efficient way possible, optimizing resource utilization to accelerate time to results and reduce costs. SDI is the foundation for a fully integrated environment, optimizing compute, storage and networking infrastructure to quickly adapt to changing business requirements, and dynamically managing workloads and data, transforming a s
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     IBM
By: GridGain     Published Date: Sep 24, 2014
In-memory computing (IMC) is an emerging field of importance in the big data industry. It is a quickly evolving technology, seen by many as an effective way to address the proverbial 3 V’s of big data—volume, velocity, and variety. Big data requires ever more powerful means to process and analyze growing stores of data, being collected at more rapid rates, and with increasing diversity in the types of data being sought—both structured and unstructured. In-memory computing’s rapid rise in the marketplace has the big data community on alert. In fact, Gartner picked in-memory computing as one of the Top Ten Strategic Initiatives.
Tags : gridgain, in memory computing, big data industry, 3v's of big data-volume
     GridGain
By: IBM     Published Date: Nov 14, 2014
Join Gartner, Inc. and IBM Platform Computing for an informative webinar where you will learn how to combine best of breed analytic solutions to provide a low latency, shared big data infrastructure. This helps government IT departments make faster decisions by analyzing massive amounts of data, improving security, detecting fraud, enabling faster decisions and saving cost by optimizing and sharing your existing infrastructure.
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     IBM
By: IBM     Published Date: Nov 14, 2014
View this series of short webcasts to learn how IBM Platform Computing products can help you ‘maximize the agility of your distributed computing environment’ by improving operational efficiency, simplify user experience, optimize application using and license sharing, address spikes in infrastructure demand and reduce data management costs.
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By: IBM     Published Date: Feb 13, 2015
This demonstration shows how an organization using IBM Platform Computing workload managers can easily and securely tap resources in the IBM SoftLayer public cloud to handle periods of peak demand and reduce total IT infrastructure costs.
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     IBM
By: IBM     Published Date: Feb 13, 2015
To quickly and economically meet new and peak demands, Platform LSF (SaaS) and Platform Symphony (SaaS) workload management as well as Elastic Storage on Cloud data management software can be delivered as a service, complete with SoftLayer cloud infrastructure and 24x7 support for technical computing and service-oriented workloads. Watch this demonstration to learn how the IBM Platform Computing Cloud Service can be used to simplify and accelerate financial risk management using IBM Algorithmics.
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     IBM
By: IBM     Published Date: Feb 13, 2015
IBM® has created a proprietary implementation of the open-source Hadoop MapReduce run-time that leverages the IBM Platform™ Symphony distributed computing middleware while maintaining application-level compatibility with Apache Hadoop.
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     IBM
By: IBM     Published Date: Feb 13, 2015
In the age of "big data," it's essential for any organization to know how to analyze and manage their ever increasing stores of information. Packed with everything you need to know about Hadoop analytics, this handy guide provides you with a solid understanding of the critical big data concepts and trends, and suggests ways for you to revolutionize your business operations through the implementation of cost-effective, high performance Hadoop technology.
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     IBM
By: IBM     Published Date: Feb 13, 2015
Organizations of all sizes need help building clusters and grids to support compute- and data-intensive application workloads. Read how the Hartree Centre is building several high-performance computing clusters to support a variety of research projects.
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     IBM
By: Intel     Published Date: Aug 06, 2014
Purpose-built for use with the dynamic computing resources available from Amazon Web Services ™, the Intel Lustre* solution provides the fast, massively scalable storage software needed to accelerate performance, even on complex workloads. Intel is a driving force behind the development of Lustre, and committed to providing fast, scalable, and cost effective storage with added support and manageability. Intel ® Enterprise Edition for Lustre* software is the ideal foundation. *Other names and brands may be claimed as the property of others.
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     Intel
By: Intel     Published Date: Aug 06, 2014
Around the world and across all industries, high-performance computing is being used to solve today’s most important and demanding problems. More than ever, storage solutions that deliver high sustained throughput are vital for powering HPC and Big Data workloads. Intel® Enterprise Edition for Lustre* software unleashes the performance and scalability of the Lustre parallel file system for enterprises and organizations, both large and small. It allows users and workloads that need large scale, high- bandwidth storage to tap into the power and scalability of Lustre, but with the simplified installation, configuration, and monitoring features of Intel® Manager for Lustre* software, a management solution purpose-built for the Lustre file system.Intel ® Enterprise Edition for Lustre* software includes proven support from the Lustre experts at Intel, including worldwide 24x7 technical support. *Other names and brands may be claimed as the property of others.
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     Intel
By: Intel     Published Date: Aug 06, 2014
Powering Big Data Workloads with Intel® Enterprise Edition for Lustre* software The Intel® portfolio for high-performance computing provides the following technology solutions: • Compute - The Intel® Xeon processor E7 family provides a leap forward for every discipline that depends on HPC, with industry-leading performance and improved performance per watt. Add Intel® Xeon Phi coprocessors to your clusters and workstations to increase performance for highly parallel applications and code segments. Each coprocessor can add over a teraflops of performance and is compatible with software written for the Intel® Xeon processor E7 family. You don’t need to rewrite code or master new development tools. • Storage - High performance, highly scalable storage solutions with Intel® Lustre and Intel® Xeon Processor E7 based storage systems for centralized storage. Reliable and responsive local storage with Intel® Solid State Drives. • Networking - Intel® True Scale Fabric and Networking technologies – Built for HPC to deliver fast message rates and low latency. • Software and Tools: A broad range of software and tools to optimize and parallelize your software and clusters. Further, Intel Enterprise Edition for Lustre software is backed by Intel, the recognized technical support providers for Lustre, and includes 24/7 service level agreement (SLA) coverage.
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     Intel
By: GridGain     Published Date: Mar 10, 2015
Software as a Service (SaaS) is a software distribution model in which applications are hosted by a vendor or service provider and made available to customers over the Internet. Instead of companies installing software on their own servers, known as the on premises distribution model, application software providers host the software in the cloud and charge customers according to the time they spend using the software, or based on a monthly or annual fee. SaaS is becoming increasingly popular, and as the industry develops, more and more companies are dropping older business models in favor of this rapidly evolving methodology.
Tags : gridgain, saas, saas perfomance and scalability, in memory computing, data fabric, paas for saas, data grid, real-time streaming, hadoop
     GridGain
By: snowflake     Published Date: Jun 09, 2016
Why Read This Report In the era of big data, enterprise data warehouse (EDW) technology continues to evolve as vendors focus on innovation and advanced features around in-memory, compression, security, and tighter integration with Hadoop, NoSQL, and cloud. Forrester identified the 10 most significant EDW software and services providers — Actian, Amazon Web Services (AWS), Hewlett Packard Enterprise (HPE), IBM, Microsoft, Oracle, Pivotal Software, SAP, Snowflake Computing, and Teradata — in the category and researched, analyzed, and scored them. This report details our findings about how well each vendor fulfills our criteria and where they stand in relation to each other to help enterprise architect professionals select the right solution to support their data warehouse platform.
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     snowflake
By: Adaptive Computing     Published Date: Feb 27, 2014
Big data applications represent a fast-growing category of high-value applications that are increasingly employed by business and technical computing users. However, they have exposed an inconvenient dichotomy in the way resources are utilized in data centers. Conventional enterprise and web-based applications can be executed efficiently in virtualized server environments, where resource management and scheduling is generally confined to a single server. By contrast, data-intensive analytics and technical simulations demand large aggregated resources, necessitating intelligent scheduling and resource management that spans a computer cluster, cloud, or entire data center. Although these tools exist in isolation, they are not available in a general-purpose framework that allows them to inter operate easily and automatically within existing IT infrastructure.
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     Adaptive Computing
By: Dell APAC     Published Date: May 29, 2019
Digital transformation (DX) is reaching a macroeconomic scale. DX business objectives are balanced between tactical and strategic objectives and range from improvement in operational efficiencies and customer satisfaction to increasing existing product revenue to improving profit margins to launching new digital revenue streams. Successful DX relies on utilizing data for services as well as converting data into actionable insights. This reliance on data is contributing to a new digital era. 3rd Platform (cloud, social, mobile, and Big Data) computing is the underpinning of DX worldwide. It enables collection of a vast breadth of data sets and delivers the agility and efficiency needed to accelerate DX
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     Dell APAC
By: Dell APAC     Published Date: May 30, 2019
Digital transformation (DX) is reaching a macroeconomic scale. DX business objectives are balanced between tactical and strategic objectives and range from improvement in operational efficiencies and customer satisfaction to increasing existing product revenue to improving profit margins to launching new digital revenue streams. Successful DX relies on utilizing data for services as well as converting data into actionable insights. This reliance on data is contributing to a new digital era. 3rd Platform (cloud, social, mobile, and Big Data) computing is the underpinning of DX worldwide. It enables collection of a vast breadth of data sets and delivers the agility and efficiency needed to accelerate DX
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     Dell APAC
By: Dell APAC     Published Date: May 30, 2019
Digital transformation (DX) is reaching a macroeconomic scale. DX business objectives are balanced between tactical and strategic objectives and range from improvement in operational efficiencies and customer satisfaction to increasing existing product revenue to improving profit margins to launching new digital revenue streams. Successful DX relies on utilizing data for services as well as converting data into actionable insights. This reliance on data is contributing to a new digital era. 3rd Platform (cloud, social, mobile, and Big Data) computing is the underpinning of DX worldwide. It enables collection of a vast breadth of data sets and delivers the agility and efficiency needed to accelerate DX
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     Dell APAC
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