Intel shows large data Power IDF2013 course recommendation

Source: Internet
Author: User
Keywords Big data Intel curriculum innovation

"IT168" Intel Developer Forum (Intel Information Technology Summit, IDF) is a technical lecture sponsored by Intel Corporation, held in 7 regions such as USA, China, two times a year. IDF mainly by keynote speeches, technical lectures and technical presentations, the keynote speakers are Intel's top personalities, the presentations are fairly forward-looking, and as a leading company in the processor, network processor, and so on, the IDF is the best place to get the industry to know about Intel's latest trends.

The 2013 Intel Information Technology Summit is scheduled to be held at the Beijing National Convention Center from April 10 to 11th. It was also the 7th consecutive year that the IDF had chosen to start in Beijing in the spring (the autumn IDF will be held in San Francisco). Intel's mobile strategy has become one of the focuses of attention at this IDF.


▲idf2013 website Link

The current IDF theme has been identified as "the future, with" core "experience", announcing that Intel is more user experience as the core, based on Intel architecture to continue to expand and deepen industrial cooperation, the overall promotion of computing technology innovation, chip manufacturing innovation, application experience innovation, terminal form innovation and cloud intelligent innovation, With powerful computational power to open a new era of personalized experience. At that time, thousands of software and hardware developers, technical managers and media and analysts from all over China and around the world will come together to experience cutting-edge technological achievements and explore future trends in innovation.

Large data is not just a concept, it can be traced back to Apache's Open source project Nutch, when large data is used to describe a large number of data sets that need to be processed or analyzed in order to update the web search index. With the release of Google's MapReduce and Googlefile System (GFS), large data is not only used to describe a large number of data, but also to deal with the speed of data processing. The industry's most common perception of large data is its 4V characteristics, namely massive data size (volume), fast data flow and Dynamic Data systems (velocity), diverse data types (produced), and huge data values (value).

There are a number of major data-related technical courses in IDF2013, including Big data beyond Hadoop: Future research directions, big data and impact on platform architecture, and technical analytics: Big Data and roles in driving technology trends are noteworthy.

Recommendation one: "Big Data Beyond Hadoop: Future research Direction"

Hadoop brings mapreduce parallel computing into mainstream applications. However, with the expansion of large data requirements and usage patterns, Hadoop has exposed many limitations. : "Big Data Beyond Hadoop: Future research Direction" the course describes the collaborative research between Intel and university partners to go beyond these constraints, and highlights efforts to apply some of the results to the production environment.

Big Data beyond Hadoop: The future direction of research includes the following:

• Memory based computing and analysis implementations

• Parallel graphics algorithms for analysis

Speech period: April 10 15:45-16:45

Lecture Room: 306B

Speaker:

Jason dai,engineering Director and Principal Engineer,intel Corporation

Michael wrinn,research program Director, University, Office,intel Corporation

Recommendation II: "Large data and impact on platform architecture"

Large data phenomena are driving the explosion of new usage patterns and applications, increasing enterprise efficiency and competitiveness. These patterns and applications can collect massive amounts of data and extract useful information through batch analysis and real-time analysis and visualization tools to drive informed decision-making.

"Large data and impact on platform architecture" mainly includes the following:

• Rapid review of large data growth

• Large Data usage patterns

• Impact of platform architecture for efficient computing for large data deployments

Speech period: April 11 14:30-15:30

Lecture Room: 309B

Speaker: Faye Briggs,intel Fellow and figuratively Server Platform Architect,intel Corporation

Recommendation III: "Technical Analysis: large data and the role in driving technology trends"

Data centers are changing at an unprecedented pace of innovation to meet the agility and efficiency challenges of large data, while taking full advantage of the latest scientific insights in the Baiwan secondary computing age. In technical analysis: large data and role in driving technology trends, Intel Senior Academician Ponsley (Steve Pawlowski) will discuss important opportunities in the industry, such as implementing smart cities and personalized medicine, and outlining how to design future-oriented technology solutions. To deliver these solutions efficiently. Attendees will be able to easily grasp key development paths for the next round of data center innovation

Speech period: April 10 15:45-16:45

Lecture Room: 306B

Speaker: Stephen Pawlowski,intel Senior fellow,chief Marvell Officer, Datacenter and Connected Bae Corporation

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