In this video, Jeff Baxter from NetApp presents: Solving I/O Challenges.
NetApp now has a customer with a full Exabyte on the floor.”
The presentation was recorded at the HPC Advisory Council Stanford Conference 2013. Download the slides (PDF).
Video: NetApp – Solving I/O Challenges
Video: High Performance NAS for Hadoop
In this video, Dr. Brent Welch from Panasas presents: High Performance NAS for Hadoop.
The presentation was recorded at the HPC Advisory Council Stanford Conference 2013. Download the slides (PDF).
ISC Introduces Big Data Conference
ISC events, the organizers of the ISC’13 International Supercomputing Conference and ISC Cloud have announced a new conference series – the ISC Big Data Conference. The inaugural event will be held September 25-26 in the Marriott Hotel, Heidelberg, Germany. Chaired by Sverre Jarp, the CTO of CERN openlab in Geneva, two-day the forum will scrutinize all facets of big data in order to empower practitioners and vendors who want to learn more about this rapidly evolving set of technologies.
Commodity-based servers and fast interconnects allow companies and service providers to build infrastructure to transform data into meaningful results, significant trends and predictions. Big Data Analytics has become synonymous with ‘power’ and ‘competitive advantage’ through the extraction of valuable knowledge by transforming the data,” said Sverre. “The challenge when implementing a ‘Big Data’ strategy is to select all the right building blocks allowing enterprise analysts or scientists to sift through huge amounts of data in the most nimble way and acquire genuine knowledge from it.”
The ISC Big Data Conference will be preceded by the annual ISC Cloud event, which will take place at the same venue on September 22-23. Read the Full Story.
Podcast: Ironstone VC Fund Using Data Science to Pick Disruptive Startups
Can Big Data analytics be used to predict which Startup companies will succeed? In this video, Thomas Thurston from Growth Science discusses the new Ironstone Venture Capital Fund, which is using Business Model Simulation to choose disruptive Startups.
The human mind is good at some things but bad at others. So we use data science and technology to help our brains with the things they weren’t designed for. This marriage between technology and the brain has allowed us to predict business behavior in ways that weren’t possible even a decade ago. It’s the future of venture capital,” said Thomas Thurston from Growth Science. “This fund is unique. First, instead of mostly using intuition, like most VCs do, we’re using powerful, proven data science to identify disruptive companies. That’s revolutionary. Second, we’re interested in seed- and early-stage companies, which is much needed as our economy rebuilds itself. Finally, unlike a lot of VCs focused on exits and quickly ‘flipping’ startups, we have a long-term view and really want to partner with people growing strong, disruptive, meaningful businesses to make the world a better place.”
Read the Full Story * Download the MP3 * Subscribe on iTunes * If Dropbox is blocked, download audio from Google Drive.
Video: Accelerating Big Data with Hadoop and Memcached
In this video, D.K. Panda from Ohio State University presents: Accelerating Big Data with Hadoop and Memcached. The presentation was recorded at the HPC Advisory Council Stanford Conference 2013. Download the slides (PDF).
Xyratex and Pentaho Partner to Unlock Big Value From Big Data
This week Xyratex announced a partnership with analytics leader Pentaho Corporation to develop the industry’s first fully integrated Big Data analytics and scalable storage solutions. The combined offerings, which will be released later this year, will help organizations decrease the amount of hardware and software required to complete major data analysis projects – and unlock the limitless potential of Big Data while delivering lower total cost of ownership (TCO) to end users.
This tight integration of the analytics engine and the data storage into the same solution will remove performance bottlenecks, reduce deployment complexity, simplify management and ease the scaling of an organization’s big data infrastructure, enabling our customers to garner valuable insights into their business sooner,” said Ken Claffey, senior vice president of the ClusterStor business at Xyratex. “Today, in collaboration with our partners, we’re helping end users achieve best-in-class performance, reliability and scalability – including implementing the fastest data storage system in the world. We’re confident that the combined power of our ClusterStor data storage with Pentaho’s leading analytics will re-define what’s possible with Big Data.”
Read the Full Story.
Video: Hadoop Acceleration with RDMA
In this video, Eyal Gutkind from Mellanox presents: Hadoop Acceleration with RDMA. The presentation was recorded at the HPC Advisory Council Stanford Conference 2013. Download the slides (PDF).
DARPA Boosts Python with $3 Million Award to Continuum Analytics
Over at IT World, Joab Jackson writes that Python just got a big data boost from DARPA with a $3 million award to software provider Continuum Analytics. The funding will help foster the development of Python’s data processing and visualization capabilities for big data jobs.
The money will go toward developing new techniques for data analysis and for visually portraying large, multi-dimensional data sets. The work aims to extend beyond the capabilities offered by the NumPy and SciPy Python libraries, which are widely used by programmers for mathematical and scientific calculations, respectively. More mathematically centered languages such as the R Statistical language might seem better suited for big-data number crunching, but Python offers an advantage of being easy to learn.
The work is part of DARPA’s XData research program, a four-year, $100 million effort to give the Defense Department and other U.S. government agencies tools to work with large amounts of sensor data and other forms of big data. Read the Full Story.
In this video from PyData NYC 2012, Stephen Diehl from Continuum Analytics presents on Blaze, a next-generation NumPy designed as a foundational set of abstractions on which to build out-of-core and distributed algorithms. Blaze generalizes many of the ideas found in popular PyData projects such as Numpy, Pandas, and Theano into one generalized data-structure. Together with a powerful array-oriented virtual machine and run-time, Blaze will be capable of performing efficient linear algebra and indexing operations on top of a wide variety of data backends.
Podcast: More than Big Data – Scott Gnau on the Teradata Unified Data Architecture
In this podcast, Scott Gnau from Teradata Labs discusses various aspects of Big Data and how the company’s Unified Data Architecture can position the enterprise to succeed.
Download the MP3 * Subscribe on iTunes * If Dropbox is blocked, download audio from Google Drive.
Slidecast: SGI Infinite Storage & Scality Ring
In this slidecast, Floyd Christofferson from SGI describes how the combination of the company’s Infinite Storage platform and Scality Ring technology provide a new, unified scale-out storage system. The solution is designed to provide both extreme scale and high performance, allowing customers to manage storage of massive stores of unstructured data.
Scale-out object-based solutions are designed to address this particular set of problems by minimizing manual intervention for storage expansions, migrations, and recoveries from storage system failure,” said Ashish Nadkarni, research director, Storage Systems at IDC. “Such a dispersed, fault-tolerant architecture enables IT organizations to more efficiently absorb data growth in a manner that is predicable for the long term.”
Read the Full Story * Download the MP3 * Download the Slides (PDF) * Subscribe on iTunes * If Dropbox is blocked, download audio from Google Drive.
Live Video: PSC Sherlock Supercomputer Launch Event
Ed. Note: The launch event starts at the 28:22 minute mark.
The Pittsburg Supercomputer Center is streaming live video from their launch event for their new Sherlock supercomputer. A uRiKA graph-analytics appliance from YarcData, Sherlock is designed to discover unknown relationships or patterns hidden in extremely large and complex bodies of information.
Sherlock gives PSC the first system available to researchers that is optimized for a particularly difficult family of questions regarding, for example, security, medicine, public health, and social dynamics,” says Nick Nystrom, Director of Strategic Applications, PSC. “These problems cost individuals and society in time, money, and human suffering. Sherlock also helps keep Pittsburgh — and Pennsylvania — at the forefront of high performance computing.”
IBM Uses Big Data to Predict Rise of Steampunk Fashion Trend
Can supercomputers predict fashion trends? Based on an analysis of more than a half million public posts on message boards, blogs, social media sites and news sources, IBM predicts that steampunk, a sub-genre inspired by the clothing, technology and social mores of Victorian society, will be a major trend to bubble up, and take hold, of the retail industry. Major fashion labels, accessories providers and jewelry makers are expected to integrate a steampunk aesthetic into their designs in the coming year.
Smart retailers are using social analytics to better understand, predict and shape consumer demand for “must-have” products before a particular trend gets saturated in the marketplace,” said Trevor Davis, Consumer Products Expert with IBM’s Global Business Services. “By staying ahead of a trend as it develops, a retailer can more effectively control critical merchandizing, inventory and planning decisions. Technology can provide tremendous foresight to help businesses differentiate what is a fleeting fad, versus what is an enduring trend.”
The IBM Social Sentiment Index uses advanced analytics and natural language processing technologies to analyze large volumes of social media data in order to assess public opinions. The Index can identify and measure positive, negative and neutral sentiments shared in public forums such as Twitter, blogs, message boards and other social media, and provide quick insights into consumer conversations about issues, products and services. Representing a new form of market research, social sentiment analyses offer organizations new insights that can help them better understand and respond to consumer trends.
Check out the Steampunk Infographic or Read the Full Story.
Joint Computing Institute to Tackle Big Data in the Northwest
This week PNNL announced that the lab is launching the new Northwest Institute for Advanced Computing in cooperation with the University of Washington. Researchers associated with the institute will work to ensure the next generation of computers and the methods used to run them can address challenges ranging from climate change to energy management.
Computing has transformed science, engineering and society in remarkable ways,” said Doug Ray, associate director of PNNL’s Fundamental & Computational Sciences Directorate. “But as huge amounts of new data are generated daily by scientific instruments and household electronics, new technologies and approaches are needed to give that information more meaning. Researchers at the Northwest Institute for Advanced Computing will tackle ‘big data’ and help improve the quality of life for many U.S. citizens.”
Located on UW’s campus, the institute will be a center of collaboration where UW and PNNL researchers jointly explore advanced computer system designs, accelerate data-driven scientific discovery and improve computational modeling and simulation. Scientists and engineers at the institute will also train future researchers in modern computational approaches. Read the Full Story.
Book Review: The Human Face of Big Data
Big data is more than hadoop, map reduce, SAS or other programmatic and analytical focused tool, solution or platform, yet those all have been and will be significant focus areas in the future. This also means big data is more than data warehouse, data mart, data mining, social media and event or activity log processing which also are main parts have continued roles going forward. Just as there are large MByte, GByte or TByte sized files or objects, there are also millions and billions of smaller files, objects or pieces of information that are part of the big data universe.
Read the Full Story or check out this interview with author Rick Smolan.
Georgia Tech wins DARPA ADATA Research Funding
A team at the Georgia Institute of Technology has received a $2.7 million award from the Defense Advanced Research Projects Agency (DARPA) to develop technology to help address the challenges of Big Data – data sets that are both massive and complex.
The contract is part of DARPA’s XDATA program, a four-year research effort to develop computational techniques and open-source software tools for processing and analysing data, motivated by defence needs. Georgia Tech was selected to perform research in the area of scalable analytics and data-processing technology.
The team will focus on producing new machine-learning approaches capable of analyzing very large-scale data. Team members will also pursue development of distributed computing methods that can process data-analytics algorithms very rapidly with a variety of systems, including supercomputers, parallel-processing environments and networked, distributed computing systems.
‘This award allows us to build on the foundations we’ve already established in large-scale data analytics and visualisation,’ said Richard Fujimoto, leader of the Georgia Tech team. ‘The algorithms, tools and other technologies that we develop will all be open source, to allow them to be customised to address new problems arising in defence and other applications.’
The award is part of a $200 million multi-agency federal initiative for big-data research and development. It aims to improve the ability to extract knowledge and insights from the nation’s fast-growing volumes of digital data.
This story appears here as part of a cross-publishing agreement with Scientific Computing World.
