Tag: hpc
Making Hadoop Relevant to HPC
Despite its proven ability to affordably process large amounts of data, Apache Hadoop and its MapReduce framework are being taken seriously only at a subset of U.S. supercomputing facilities and only by a subset of profe Read more…
ISC’14
The International Supercomputing Conference (ISC) is the most significant conference and exhibition in Europe for the HPC community. The 2014 focus is on supercomputers solving real life problems, extreme computing chall Read more…
How In-Memory Data Grids Can Analyze Fast-Changing Data in Real-Time
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The ability to continuously analyze operational data unlocks the potential for organizations to extract important patterns. Popular big data systems are not well suited for this challenge. However, in-memory data grid technology (IMDGs) offers important breakthroughs that enable real-time analysis of operational data. Benchmarks have demonstrated that an IMDG can complete map/reduce analyses every four seconds across a changing, terabyte data set. This article discusses how IMDGs deliver this new capability to analyze fast-changing, operational data. Read more…
The Big Data Security Gap: Protecting the Hadoop Cluster
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Hadoop enables the distributed processing of large data sets across clusters of computers, but its approach presents a unique set of security challenges that many enterprise organizations aren’t equipped to handle. Open source approaches to securing Hadoop are still in their infancy, and lack robustness. Zettaset Orchestrator™ is the only solution that has been specifically designed to meet enterprise security requirements in big data and Hadoop environments. Learn what every organization should know about Hadoop security. Read more…
Accelerate Hadoop MapReduce Performance using Dedicated OrangeFS Servers
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Recent tests performed at Clemson University achieved a 25 percent improvement in Apache Hadoop Terasort run times by replacing Hadoop Distributed File System (HDFS) with an OrangeFS configuration using dedicated servers. Key components included extension of the MapReduce “FileSystem” class and a Java Native Interface (JNI) shim to the OrangeFS client. No modifications of Hadoop were required, and existing MapReduce jobs require no modification to utilize OrangeFS. Read more…
IDC Talks Convergence in High Performance Data Analysis
At the International Supercomputing Conference (ISC’13) this week, convergence is in the air as many discussions are including talk about the merging of traditional high performance technical computing with the rising data tides of the enterprise. Putting data and use cases on display, the analysts at IDC gave their view of this convergence space – and shared their own name for it: High Performance Data Analysis (or HPDA). Read more…
Why Big Data Needs InfiniBand to Continue Evolving
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Increasingly, it’s a Big Data world we live in. Just in case you’ve been living under a rock and need proof of that, <a href="http://www.forbes.com/sites/kashmirhill/2012/02/16/how-target-figured-out-a-teen-girl-was-pregnant-before-her-father-did/" target="_blank">a major retailer can use an unimaginable number of data points to predict the pregnancy of a teenage girl outside Minneapolis before she gets a chance to tell her family</a>. That’s just one example, but there are countless others that point to the idea that mining huge data volumes can uncover gold nuggets of actionable proportions (although sometimes they freak people out...) Read more…
Big Data & Virtual Prototyping Changing Auto Design Culture
Design and engineering teams at Jaguar Land Rover say that big data and virtual prototyping are changing the culture and way they think about their work. Read more…
Sharing Infrastructure: Can Hadoop Play Well With Others?
A lot of big data/Hadoop implementations are swimming against the currents of what recent history has taught about large scale computing and the result is a significant amount of waste, says Univa CEO, Gary Tyreman, who believes that Hadoop shared-infrastructure environments are on the rise. Read more…
Study: Reverse Debuggers can Decrease Debugging Time by an Average of 26%
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According to a <a href="http://www.roguewave.com/company/news-events/press-releases/2013/university-of-cambridge-reverse-debugging-study.aspx?utm_source=HPCwire&utm_medium=Spotlight&utm_campaign=ITS-20130325" target="_blank">recent study</a> at the University of Cambridge, researchers found that when respondents use reverse debugging tools, like Rogue Wave’s <a href="http://www.roguewave.com/products/totalview/replayengine.aspx?utm_source=HPCwire&utm_medium=Spotlight&utm_campaign=ITS-20130325" target="_blank">Replay Engine</a>, their debugging time decreased by an average of 26%. Developers, like you, can leverage these time savings to develop additional products, features, and capabilities. Read more…
Python Wraps Around Big, Fast Data
Python is finding its way into an ever-expanding set of use cases that fall into both the high performance computing and big data buckets. Read more…
How Ford is Putting Hadoop Pedal to the Metal
Ford Motor, like any other company at its scale, has been contending with a slew of big data problems--a matter that is being complicated by ever-growing additions to the data feed, from its own internal feeds to the terabytes of vehicle-fed machine data. We talked in depth with Ford's data science lead about the company's tough vendor and technology decisions around Hadoop and where the real value of such.... Read more…
Juneja: HPC, Cloud, and Open Source the Nexus of Big Data Innovation
It should come as no surprise that Intel is converging HPC, cloud and open source, said Intel's big data chief at the Strata 2013 conference this week. Read more…
SGI Plants Big Data Seeds in HPC
Mannel and Conway talked this week about SGI and their various big data functions. Their focus was specifically data-intensive high performance computing, otherwise known as high performance data analytics (HPDA). The talk touched on both the rise of big data within HPC and how SGI has molded to that. Read more…
How In-Memory Data Grids Can Analyze Fast-Changing Data in Real-Time
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Continuous analysis of fast-changing operational data unlocks the potential to extract important patterns. Big data systems such as Hadoop are not well suited for this challenge, however, in-memory data grids (IMDGs) offer breakthroughs that enable real-time analysis of fast-changing data. Recent measurements demonstrate that an IMDG can deliver a complete map/reduce analysis every four seconds across a terabyte data set which is being updated continuously.<br /> Read more…
Marking Spikes for the Enterprise Graph
In some ways, the story of Sun Microsystems closely parallels what’s happening with the present merge between high performance computing and the more enterprise-geared momentum behind big data. According to a former Sun lead on the R&D side and current research and development exec at Cray's big data arm, this story can be.... Read more…
BioInformatics: A Data Deluge with Hadoop to the Rescue
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Apache Hadoop-based massively parallel processing is well suited to address many challenges in the growing field of BioInformatics. BioInformatics is not a “spectator sport”; this article explains how to get started via hands-on experience with the FDA Adverse Event Reporting System (FAERS). Read more…
Using In-Memory Data Grids for Global Data Integration
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By enabling extremely fast and scalable data access even under large and growing workloads, in-memory data grids (IMDGs) have proven their value in storing fast-changing application data, such as financial trading data, shopping data, and much more. As organizations work to efficiently access their critical business data across multiple sites or scale their processing into the cloud, the need rapidly has grown to quickly and seamlessly migrate data where it is needed. The use of IMDGs creates an exciting opportunity for organizations to employ powerful global strategies for data sharing. Federating IMDGs across multiple sites enables seamless, transparent access to data from any site and provides an ideal solution to the challenge of global data integration. Read more…
TIBCO CTO Flashes R&D Future for Fast Data
This week we spent quality time with software giant TIBCO's CTO, Matt Quinn to discuss what the future of big data research and development looks like--and what trends are on the horizon in the post-Hadoop ecosystem. From network and switch tweaks to getting a handle on... Read more…
The GPU “Sweet Spot” for Big Data
GPUs have stirred some vicious waves in the supercomputing community, and these same performance boosts are being explored for large-scale data mining by a number of enterprise users. During our conversation with NVIDIA's Tesla senior manager for high performance computing, Sumit Gupta, we explored how traditional data... Read more…
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