Tag: community

Why open source companies dont dance?

I have been pondering on this seemingly logical paradox for some time now-

1) Why are open source solutions considered technically better but not customer friendly.

2) Why do startups and app creators in social media or mobile get much more press coverage than

profitable startups in enterprise software.

3) How does tech journalism differ in covering open source projects in enterprise versus retail software.

4) What are the hidden rules of the game of enterprise software.

Some observations-

1) Open source companies often focus much more on technical community management and crowd sourcing code. Traditional software companies focus much more on managing the marketing community of customers and influencers. Accordingly the balance of power is skewed in favor of techies and R and D in open source companies, and in favor of marketing and analyst relations in traditional software companies.

Traditional companies also spend much more on hiring top notch press release/public relationship agencies, while open source companies are both financially and sometimes ideologically opposed to older methods of marketing software. The reverse of this is you are much more likely to see Videos and Tutorials by an open source company than a traditional company. You can compare the websites of Cloudera, DataStax, Hadapt ,Appistry and Mapr and contrast that with Teradata or Oracle (which has a much bigger and much more different marketing strategy.

Social media for marketing is also more efficiently utilized by smaller companies (open source) while bigger companies continue to pay influential analysts for expensive white papers that help present the brand.

Lack of budgets is a major factor that limits access to influential marketing for open source companies particularly in enterprise software.

2 and 3) Retail software is priced at 2-100$ and sells by volume. Accordingly technology coverage of these software is based on volume.

Enterprise software is much more expensively priced and has much more discreet volume or sales points. Accordingly the technology coverage of enterprise software is more discreet, in terms of a white paper coming every quarter, a webinar every month and a press release every week. Retail software is covered non stop , but these journalists typically do not charge for “briefings”.

Journalists covering retail software generally earn money by ads or hosting conferences. So they have an interest in covering new stuff or interesting disruptive stuff. Journalists or analysts covering enterprise software generally earn money by white papers, webinars, attending than hosting conferences, writing books. They thus have a much stronger economic incentive to cover existing landscape and technologies than smaller startups.

4) What are the hidden rules of the game of enterprise software.

  • It is mostly a white man’s world. this can be proved by statistical demographic analysis
  • There is incestuous intermingling between influencers, marketers, and PR people. This can be proved by simple social network analysis of who talks to who and how much. A simple time series between sponsorship and analysts coverage also will prove this (I am working on quantifying this ).
  • There are much larger switching costs to enterprise software than retail software. This leads to legacy shoddy software getting much chances than would have been allowed in an efficient marketplace.
  • Enterprise software is a less efficient marketplace than retail software in all definitions of the term “efficient markets”
  • Cloud computing, and SaaS and Open source threatens to disrupt the jobs and careers of a large number of people. In the long term, they will create many more jobs, but in the short term, people used to comfortable living of enterprise software (making,selling,or writing) will actively and passively resist these changes to the  paradigms in the current software status quo.
  • Open source companies dont dance and dont play ball. They prefer to hire 4 more college grads than commission 2 more white papers.

and the following with slight changes from a comment I made on a fellow blog-

  • While the paradigm on how to create new software has evolved from primarily silo-driven R and D departments to a broader collaborative effort, the biggest drawback is software marketing has not evolved.
  • If you want your own version of the open source community editions to be more popular, some standardization is necessary for the corporate decision makers, and we need better marketing paradigms.
  • While code creation is crowdsourced, solution implementation cannot be crowdsourced. Customers want solutions to a problem not code.
  • Just as open source as a production and licensing paradigm threatens to disrupt enterprise software, it will lead to newer ways to marketing software given the hostility of existing status quo.

 

 

RapidMiner launches extensions marketplace

For some time now, I had been hoping for a place where new package or algorithm developers get at least a fraction of the money that iPad or iPhone application developers get. Rapid Miner has taken the lead in establishing a marketplace for extensions. Is there going to be paid extensions as well- I hope so!!

This probably makes it the first “app” marketplace in open source and the second app marketplace in analytics after salesforce.com

It is hard work to think of new algols, and some of them can really be usefull.

Can we hope for #rstats marketplace where people downloading say ggplot3.0 atleast get a prompt to donate 99 cents per download to Hadley Wickham’s Amazon wishlist. http://www.amazon.com/gp/registry/1Y65N3VFA613B

Do you think it is okay to pay 99 cents per iTunes song, but not pay a cent for open source software.

I dont know- but I am just a capitalist born in a country that was socialist for the first 13 years of my life. Congratulations once again to Rapid Miner for innovating and leading the way.

http://rapid-i.com/component/option,com_myblog/show,Rapid-I-Marketplace-Launched.html/Itemid,172

RapidMiner, Marketplace, Extensions 30 May 2011
Rapid-I Marketplace Launched by Simon Fischer

Over the years, many of you have been developing new RapidMiner Extensions dedicated to a broad set of topics. Whereas these extensions are easy to install in RapidMiner – just download and place them in the plugins folder – the hard part is to find them in the vastness that is the Internet. Extensions made by ourselves at Rapid-I, on the other hand,  are distributed by the update server making them searchable and installable directly inside RapidMiner.

We thought that this was a bit unfair, so we decieded to open up the update server to the public, and not only this, we even gave it a new look and name. The Rapid-I Marketplace is available in beta mode at http://rapidupdate.de:8180/ . You can use the Web interface to browse, comment, and rate the extensions, and you can use the update functionality in RapidMiner by going to the preferences and entering http://rapidupdate.de:8180/UpdateServer/ as the update server URL. (Once the beta test is complete, we will change the port back to 80 so we won’t have any firewall problems.)

As an Extension developer, just register with the Marketplace and drop me an email (fischer at rapid-i dot com) so I can give you permissions to upload your own extension. Upload is simple provided you use the standard RapidMiner Extension build process and will boost visibility of your extension.

Looking forward to see many new extensions there soon!

Disclaimer- Decisionstats is a partner of Rapid Miner. I have been liking the software for a long long time, and recently agreed to partner with them just like I did with KXEN some years back, and with Predictive AnalyticsConference, and Aster Data until last year.

I still think Rapid Miner is a very very good software,and a globally created software after SAP.

Here is the actual marketplace

http://rapidupdate.de:8180/UpdateServer/faces/index.xhtml

Welcome to the Rapid-I Marketplace Public Beta Test

The Rapid-I Marketplace will soon replace the RapidMiner update server. Using this marketplace, you can share your RapidMiner extensions and make them available for download by the community of RapidMiner users. Currently, we are beta testing this server. If you want to use this server in RapidMiner, you must go to the preferences and enter http://rapidupdate.de:8180/UpdateServer for the update url. After the beta test, we will change the port back to 80, which is currently occupied by the old update server. You can test the marketplace as a user (downloading extensions) and as an Extension developer. If you want to publish your extension here, please let us know via the contact form.

Hot Downloads
«« « 1 2 3 » »»
[Icon]The Image Processing Extension provides operators for handling image data. You can extract attributes describing colour and texture in the image, you can make several transformation of a image data which allows you to perform segmentation and detection of suspicious areas in image data.The extension provides many of image transformation and extraction operators ranging from Wavelet Decomposition, Hough Circle to Block Difference of Inverse probabilities.
[Icon]RapidMiner is unquestionably the world-leading open-source system for data mining. It is available as a stand-alone application for data analysis and as a data mining engine for the integration into own products. Thousands of applications of RapidMiner in more than 40 countries give their users a competitive edge.

  • Data Integration, Analytical ETL, Data Analysis, and Reporting in one single suite
  • Powerful but intuitive graphical user interface for the design of analysis processes
  • Repositories for process, data and meta data handling
  • Only solution with meta data transformation: forget trial and error and inspect results already during design time
  • Only solution which supports on-the-fly error recognition and quick fixes
  • Complete and flexible: Hundreds of data loading, data transformation, data modeling, and data visualization methods
[Icon]All modeling methods and attribute evaluation methods from the Weka machine learning library are available within RapidMiner. After installing this extension you will get access to about 100 additional modelling schemes including additional decision trees, rule learners and regression estimators.This extension combines two of the most widely used open source data mining solutions. By installing it, you can extend RapidMiner to everything what is possible with Weka while keeping the full analysis, preprocessing, and visualization power of RapidMiner.
[Icon]Finally, the two most widely used data analysis solutions – RapidMiner and R – are connected. Arbitrary R models and scripts can now be directly integrated into the RapidMiner analysis processes. The new R perspective offers the known R console together with the great plotting facilities of R. All variables and R scripts can be organized in the RapidMiner Repository.A directly included online help and multi-line editing makes the creation of R scripts much more comfortable.
Related articles

#Rstats for Business Intelligence

This is a short list of several known as well as lesser known R ( #rstats) language codes, packages and tricks to build a business intelligence application. It will be slightly Messy (and not Messi) but I hope to refine it someday when the cows come home.

It assumes that BI is basically-

a Database, a Document Database, a Report creation/Dashboard pulling software as well unique R packages for business intelligence.

What is business intelligence?

Seamless dissemination of data in the organization. In short let it flow- from raw transactional data to aggregate dashboards, to control and test experiments, to new and legacy data mining models- a business intelligence enabled organization allows information to flow easily AND capture insights and feedback for further action.

BI software has lately meant to be just reporting software- and Business Analytics has meant to be primarily predictive analytics. the terms are interchangeable in my opinion -as BI reports can also be called descriptive aggregated statistics or descriptive analytics, and predictive analytics is useless and incomplete unless you measure the effect in dashboards and summary reports.

Data Mining- is a bit more than predictive analytics- it includes pattern recognizability as well as black box machine learning algorithms. To further aggravate these divides, students mostly learn data mining in computer science, predictive analytics (if at all) in business departments and statistics, and no one teaches metrics , dashboards, reporting  in mainstream academia even though a large number of graduates will end up fiddling with spreadsheets or dashboards in real careers.

Using R with

1) Databases-

I created a short list of database connectivity with R here at https://rforanalytics.wordpress.com/odbc-databases-for-r/ but R has released 3 new versions since then.

The RODBC package remains the package of choice for connecting to SQL Databases.

http://cran.r-project.org/web/packages/RODBC/RODBC.pdf

Details on creating DSN and connecting to Databases are given at  https://rforanalytics.wordpress.com/odbc-databases-for-r/

For document databases like MongoDB and CouchDB

( what is the difference between traditional RDBMS and NoSQL if you ever need to explain it in a cocktail conversation http://dba.stackexchange.com/questions/5/what-are-the-differences-between-nosql-and-a-traditional-rdbms

Basically dispensing with the relational setup, with primary and foreign keys, and with the additional overhead involved in keeping transactional safety, often gives you extreme increases in performance

NoSQL is a kind of database that doesn’t have a fixed schema like a traditional RDBMS does. With the NoSQL databases the schema is defined by the developer at run time. They don’t write normal SQL statements against the database, but instead use an API to get the data that they need.

instead relating data in one table to another you store things as key value pairs and there is no database schema, it is handled instead in code.)

I believe any corporation with data driven decision making would need to both have atleast one RDBMS and one NoSQL for unstructured data-Ajay. This is a sweeping generic statement 😉 , and is an opinion on future technologies.

  • Use RMongo

From- http://tommy.chheng.com/2010/11/03/rmongo-accessing-mongodb-in-r/

http://plindenbaum.blogspot.com/2010/09/connecting-to-mongodb-database-from-r.html

Connecting to a MongoDB database from R using Java

http://nsaunders.wordpress.com/2010/09/24/connecting-to-a-mongodb-database-from-r-using-java/

Also see a nice basic analysis using R Mongo from

http://pseudofish.com/blog/2011/05/25/analysis-of-data-with-mongodb-and-r/

For CouchDB

please see https://github.com/wactbprot/R4CouchDB and

http://digitheadslabnotebook.blogspot.com/2010/10/couchdb-and-r.html

  • First install RCurl and RJSONIO. You’ll have to download the tar.gz’s if you’re on a Mac. For the second part, we’ll need to installR4CouchDB,

2) External Report Creating Software-

Jaspersoft- It has good integration with R and is a certified Revolution Analytics partner (who seem to be the only ones with a coherent #Rstats go to market strategy- which begs the question – why is the freest and finest stats software having only ONE vendor- if it was so great lots of companies would make exclusive products for it – (and some do -see https://rforanalytics.wordpress.com/r-business-solutions/ and https://rforanalytics.wordpress.com/using-r-from-other-software/)

From

http://www.jaspersoft.com/sites/default/files/downloads/events/Analytics%20-Jaspersoft-SEP2010.pdf

we see

http://jasperforge.org/projects/rrevodeployrbyrevolutionanalytics

RevoConnectR for JasperReports Server

RevoConnectR for JasperReports Server RevoConnectR for JasperReports Server is a Java library interface between JasperReports Server and Revolution R Enterprise’s RevoDeployR, a standardized collection of web services that integrates security, APIs, scripts and libraries for R into a single server. JasperReports Server dashboards can retrieve R charts and result sets from RevoDeployR.

http://jasperforge.org/plugins/esp_frs/optional_download.php?group_id=409

 

Using R and Pentaho
Extending Pentaho with R analytics”R” is a popular open source statistical and analytical language that academics and commercial organizations alike have used for years to get maximum insight out of information using advanced analytic techniques. In this twelve-minute video, David Reinke from Pentaho Certified Partner OpenBI provides an overview of R, as well as a demonstration of integration between R and Pentaho.
and from
R and BI – Integrating R with Open Source Business
Intelligence Platforms Pentaho and Jaspersoft
David Reinke, Steve Miller
Keywords: business intelligence
Increasingly, R is becoming the tool of choice for statistical analysis, optimization, machine learning and
visualization in the business world. This trend will only escalate as more R analysts transition to business
from academia. But whereas in academia R is often the central tool for analytics, in business R must coexist
with and enhance mainstream business intelligence (BI) technologies. A modern BI portfolio already includes
relational databeses, data integration (extract, transform, load – ETL), query and reporting, online analytical
processing (OLAP), dashboards, and advanced visualization. The opportunity to extend traditional BI with
R analytics revolves on the introduction of advanced statistical modeling and visualizations native to R. The
challenge is to seamlessly integrate R capabilities within the existing BI space. This presentation will explain
and demo an initial approach to integrating R with two comprehensive open source BI (OSBI) platforms –
Pentaho and Jaspersoft. Our efforts will be successful if we stimulate additional progress, transparency and
innovation by combining the R and BI worlds.
The demonstration will show how we integrated the OSBI platforms with R through use of RServe and
its Java API. The BI platforms provide an end user web application which include application security,
data provisioning and BI functionality. Our integration will demonstrate a process by which BI components
can be created that prompt the user for parameters, acquire data from a relational database and pass into
RServer, invoke R commands for processing, and display the resulting R generated statistics and/or graphs
within the BI platform. Discussion will include concepts related to creating a reusable java class library of
commonly used processes to speed additional development.

If you know Java- try http://ramanareddyg.blog.com/2010/07/03/integrating-r-and-pentaho-data-integration/

 

and I like this list by two venerable powerhouses of the BI Open Source Movement

http://www.openbi.com/demosarticles.html

Open Source BI as disruptive technology

http://www.openbi.biz/articles/osbi_disruption_openbi.pdf

Open Source Punditry

TITLE AUTHOR COMMENTS
Commercial Open Source BI Redux Dave Reinke & Steve Miller An review and update on the predictions made in our 2007 article focused on the current state of the commercial open source BI market. Also included is a brief analysis of potential options for commercial open source business models and our take on their applicability.
Open Source BI as Disruptive Technology Dave Reinke & Steve Miller Reprint of May 2007 DM Review article explaining how and why Commercial Open Source BI (COSBI) will disrupt the traditional proprietary market.

Spotlight on R

TITLE AUTHOR COMMENTS
R You Ready for Open Source Statistics? Steve Miller R has become the “lingua franca” for academic statistical analysis and modeling, and is now rapidly gaining exposure in the commercial world. Steve examines the R technology and community and its relevancy to mainstream BI.
R and BI (Part 1): Data Analysis with R Steve Miller An introduction to R and its myriad statistical graphing techniques.
R and BI (Part 2): A Statistical Look at Detail Data Steve Miller The usage of R’s graphical building blocks – dotplots, stripplots and xyplots – to create dashboards which require little ink yet tell a big story.
R and BI (Part 3): The Grooming of Box and Whiskers Steve Miller Boxplots and variants (e.g. Violin Plot) are explored as an essential graphical technique to summarize data distributions by categories and dimensions of other attributes.
R and BI (Part 4): Embellishing Graphs Steve Miller Lattices and logarithmic data transformations are used to illuminate data density and distribution and find patterns otherwise missed using classic charting techniques.
R and BI (Part 5): Predictive Modelling Steve Miller An introduction to basic predictive modelling terminology and techniques with graphical examples created using R.
R and BI (Part 6) :
Re-expressing Data		 Steve Miller How do you deal with highly skewed data distributions? Standard charting techniques on this “deviant” data often fail to illuminate relationships. This article explains techniques to re-express skewed data so that it is more understandable.
The Stock Market, 2007 Steve Miller R-based dashboards are presented to demonstrate the return performance of various asset classes during 2007.
Bootstrapping for Portfolio Returns: The Practice of Statistical Analysis Steve Miller Steve uses the R open source stats package and Monte Carlo simulations to examine alternative investment portfolio returns…a good example of applied statistics using R.
Statistical Graphs for Portfolio Returns Steve Miller Steve uses the R open source stats package to analyze market returns by asset class with some very provocative embedded trellis charts.
Frank Harrell, Iowa State and useR!2007 Steve Miller In August, Steve attended the 2007 Internation R User conference (useR!2007). This article details his experiences, including his meeting with long-time R community expert, Frank Harrell.
An Open Source Statistical “Dashboard” for Investment Performance Steve Miller The newly launched Dashboard Insight web site is focused on the most useful of BI tools: dashboards. With this article discussing the use of R and trellis graphics, OpenBI brings the realm of open source to this forum.
Unsexy Graphics for Business Intelligence Steve Miller Utilizing Tufte’s philosophy of maximizing the data to ink ratio of graphics, Steve demonstrates the value in dot plot diagramming. The R open source statistical/analytics software is showcased.
I think that the report generation package Brew would also qualify as a BI package, but large scale implementation remains to be seen in
a commercial business environment
  • brew: Creating Repetitive Reports
 brew: Templating Framework for Report Generation

brew implements a templating framework for mixing text and R code for report generation. brew template syntax is similar to PHP, Ruby's erb module, Java Server Pages, and Python's psp module. http://bit.ly/jINmaI
  • Yarr- creating reports in R
to be continued ( when I have more time and the temperature goes down from 110F in Delhi, India)
Related articles

AsterData still alive;/launches SQL-MapReduce Developer Portal

so apparantly ole client AsterData continues to thrive under gentle touch of Terrific Data

———————————————————————————————————————————————————

Aster Data today launched the SQL-MapReduce Developer Portal, a new online community for data scientists and analytic developers. For your convenience, I copied the release below and it can also be found here. Please let me know if you have any questions or if there is anything else I can help you with.

Sara Korolevich

Point Communications Group for Aster Data

sarak@pointcgroup.com

Office: 602.279.1137

Mobile: 623.326.0881

Teradata Accelerates Big Data Analytics with First Collaborative Community for SQL-MapReduce®

New online community for data scientists and analytic developers enables development and sharing of powerful MapReduce analytics


San Carlos, California – Teradata Corporation (NYSE:TDC) today announced the launch of the Aster Data SQL-MapReduce® Developer Portal. This portal is the first collaborative online developer community for SQL-MapReduce analytics, an emerging framework for processing non-relational data and ultra-fast analytics.

“Aster Data continues to deliver on its unique vision for powerful analytics with a rich set of tools to make development of those analytics quick and easy,” said Tasso Argyros, vice president of Aster Data Marketing and Product Management, Teradata Corporation. “This new developer portal builds on Aster Data’s continuing SQL-MapReduce innovation, leveraging the flexibility and power of SQL-MapReduce for analytics that were previously impossible or impractical.”

The developer portal showcases the power and flexibility of Aster Data’s SQL-MapReduce – which uniquely combines standard SQL with the popular MapReduce distributed computing technology for processing big data – by providing a collaborative community for sharing SQL-MapReduce expert insights in addition to sharing SQL-MapReduce analytic functions and sample code. Data scientists, quantitative analysts, and developers can now leverage the experience, knowledge, and best practices of a community of experts to easily harness the power of SQL-MapReduce for big data analytics.

A recent report from IDC Research, “Taking Care of Your Quants: Focusing Data Warehousing Resources on Quantitative Analysts Matters,” has shown that by enabling data scientists with the tools to harness emerging types and sources of data, companies create significant competitive advantage and become leaders in their respective industry.

“The biggest positive differences among leaders and the rest come from the introduction of new types of data,” says Dan Vesset, program vice president, Business Analytics Solutions, IDC Research. “This may include either new transactional data sources or new external data feeds of transactional or multi-structured interactional data — the latter may include click stream or other data that is a by-product of social networking.”

Vesset goes on to say, “Aster Data provides a comprehensive platform for analytics and their SQL-MapReduce Developer Portal provides a community for sharing best practices and functions which can have an even greater impact to an organization’s business.”

With this announcement Aster Data extends its industry leadership in delivering the most comprehensive analytic platform for big data analytics — not only capable of processing massive volumes of multi-structured data, but also providing an extensive set of tools and capabilities that make it simple to leverage the power of MapReduce analytics. The Aster Data

SQL-MapReduce Developer Portal brings the power of SQL-MapReduce accessible to data scientists, quantitative analysis, and analytic developers by making it easy to share and collaborate with experts in developing SQL-MapReduce analytics. This portal builds on Aster Data’s history of SQL-MapReduce innovations, including:

  • The first deep integration of SQL with MapReduce
  • The first MapReduce support for .NET
  • The first integrated development environment, Aster Data
    Developer Express
  • A comprehensive suite of analytic functions, Aster Data
    Analytic Foundation

Aster Data’s patent-pending SQL-MapReduce enables analytic applications and functions that can deliver faster, deeper insights on terabytes to petabytes of data. These applications are implemented using MapReduce but delivered through standard SQL and business intelligence (BI) tools.

SQL-MapReduce makes it possible for data scientists and developers to empower business analysts with the ability to make informed decisions, incorporating vast amounts of data, regardless of query complexity or data type. Aster Data customers are using SQL-MapReduce for rich analytics including analytic applications for social network analysis, digital marketing optimization, and on-the-fly fraud detection and prevention.

“Collaboration is at the core of our success as one of the leading providers, and pioneers of social software,” said Navdeep Alam, director of Data Architecture at Mzinga. “We are pleased to be one of the early members of The Aster Data SQL-MapReduce Developer Portal, which will allow us the ability to share and leverage insights with others in using big data analytics to attain a deeper understanding of customers’ behavior and create competitive advantage for our business.”

SQL-MapReduce is one of the core capabilities within Aster Data’s flagship product. Aster DatanCluster™ 4.6, the industry’s first massively parallel processing (MPP) analytic platform has an integrated analytics engine that stores and processes both relational and non-relational data at scale. With Aster Data’s unique analytics framework that supports both SQL and
SQL-MapReduce™, customers benefit from rich, new analytics on large data volumes with complex data types. Aster Data analytic functions are embedded within the analytic platform and processed locally with data, which allows for faster data exploration. The SQL-MapReduce framework provides scalable fault-tolerance for new analytics, providing users with superior reliability, regardless of number of users, query size, or data types.


About Aster Data
Aster Data is a market leader in big data analytics, enabling the powerful combination of cost-effective storage and ultra-fast analysis of new sources and types of data. The Aster Data nCluster analytic platform is a massively parallel software solution that embeds MapReduce analytic processing with data stores for deeper insights on new data sources and types to deliver new analytic capabilities with breakthrough performance and scalability. Aster Data’s solution utilizes Aster Data’s patent-pending SQL-MapReduce to parallelize processing of data and applications and deliver rich analytic insights at scale. Companies including Barnes & Noble, Intuit, LinkedIn, Akamai, and MySpace use Aster Data to deliver applications such as digital marketing optimization, social network and relationship analysis, and fraud detection and prevention.


About Teradata
Teradata is the world’s leader in data warehousing and integrated marketing management through itsdatabase software, data warehouse appliances, and enterprise analytics. For more information, visitteradata.com.

# # #

Teradata is a trademark or registered trademark of Teradata Corporation in the United States and other countries.

Free and Open Source cannot get basic economics correct

Nutch robots
Image via Wikipedia

Before you rev up those keyboards, and shoot off a snarky comment- consider this statement- there are many ways to run (and ruin economies). But they still have not found a replacement for money. Yes Happiness is important. Search Engine is good.

So unless they start a new branch of economics with lots more motivational theory and psychology and lot less quant especially for open source projects, money ,revenue, sales is the only true measure of success in enterprise software. Particularly if you have competitors who are making more money selling the same class of software.

Popularity contests are for high school quarterbacks —so even if your open source software is popular in downloads, email discussions, stack overflow or Continue reading “Free and Open Source cannot get basic economics correct”

Intel® Threading Challenge 2011 Software Contest

Logo of Intel, Jul 1968 - Dec 2005
Image via Wikipedia

One more software contests for you, but in the sub million dollar prize range

http://software.intel.com/en-us/contests/intel-threading-challenge-2011/contests.php

Intel® Threading Challenge 2011 – Win a Trip to Intel Developer Forum in San Francisco

Intel® Threading Challenge 2011 is going BIG this year! After three exciting threading competitions, our fourth Threading Challenge is stepping up the excitement with a BIG Grand Prize, a trip to the Intel Developer Forum (IDF) in San Francisco (September 13-15, 2011).

Since 2008, the Intel® Threading Challenge has attracted developers of varying experience from around the world. The active participation from the community has made the Threading Challenge not only a great programming competition, but a great way for community members to engage with each other, trade threading tips, and discover new parallel programming resources.

Last year’s format of two competition levels, Master and Apprentice, generated great excitement and opened the Threading Challenge to a new group of participants. So, we are going to continue the competition with a Master level and Apprentice level, each competing for the Grand Prize for their level, as well as individual problem awards. We know you love a great challenge and great prizes, so our Threading Challenge Team is putting together some exciting threading problems for you.

Monday, April 18, 2011 – Threading Challenge 2011 (Phase 1) Launches (both levels) at 12:00 PM (noon PDT)– The competition for 2011 is very similar to last year’s, but read on whether you’re a previous participant or new to the Threading Challenge, so you will be aware of all elements of the competition and how to compete. Then, you can start threading your way to prizes today!

Choose the right level for you!

 

Threading Challenge 2011:

• Two levels available for entry: Apprentice & Master
• Phase 1: 3 problems in each level
• Phase 2: Stay tuned for details, coming in Autumn 2011
• We will award 1st, 2nd & 3rd place prizes for each problem in each level
• No overlap of problems and each level’s problems will be offered consecutively
• Participants have the option to use the Intel® Manycore Testing Lab (MTL), consisting of 40 cores, 80 threads
• To enter the Threading Challenge 2011, please read the Official Rules and register for the competition with link in the “To Enter” Section.

The Threading Challenge will be implemented in two phases, with the 1st Phase consisting of 3 problems in each level. The details of the 2nd Phase will be announced in September 2011. For Phase 1, a new problem in each level will be launched on the days listed below at 12:00 noon (PDT) and will be open for entry for 22 days (inclusive of the problem starting day), until closing on the final problem day at 12:00 noon (PDT).

Problem Start and Closing Dates (both Master and Apprentice levels):

Problem 1:
Starts: Monday, April 18, 2011 at 12:00pm (PDT)
Ends. Monday, May 9, 2011 at 12:00pm (PDT)

Problem 2:
Starts: Monday, May 9, 2011 at 12:00pm (PDT)
Ends: Monday, May 30, 2011 at 12:00pm (PDT)

Problem 3: (Due to U.S. Memorial Day Holiday, Problem 2 will start on Tuesday, May 31, 2011)
Starts: Tuesday, May 31, 2011 at 12:00pm (PDT)
Ends: Tuesday, June 21, 2011 at 12:00pm (PDT)

*All problems start and end at 12:00 noon (Pacific Daylight Time)

Contestants will have 22 days to complete their entry submission (solution only for Apprentice OR solution and write-up for Master) for each problem. You may enter ONLY 1 problem at a time and will need to choose which level (Apprentice or Master) you wish to participate in during each problem cycle. You will be awarded points based on your solution submitted. Be sure to take advantage of our threading resources and tools, and you may validate your solution (optional) using the Intel® Manycore Testing Lab to solve your problems and get involved in the dedicated forums to earn extra points.

Each problems winners will be announced on the site after the problem is closed, and Prizes will be awarded to those problem winners (see official rules for prize distribution information). The Grand Prize, a Trip to Intel® Developer Forum (IDF) in San Francisco, will be awarded for each level to the participant that has the highest total points earned for the three problems in each level (i.e., highest total points for Master level problems and Apprentice level problems).

The Intel® Threading Challenge attracts some of the most talented developers in the world to solve parallelism code challenges. Now is your chance to take multithreading to the next level and possibly win great prizes. Demonstrate your threading expertise today!

More Details:

Intel® Threading Challenge 2011 is organized so any level of developer can have the opportunity to participate. Two levels of participation are available. The Apprentice level gives those just getting started in multithreading development a chance to try out and improve their threading skills. The Master level will be executed similarly to previous threading challenges, providing those with more experience a chance to test their skills and compete against other experienced developers.

Intel® Manycore Testing Lab – Available as Option for Threading Challenge 2011 Participants

This year competitors will have the optional opportunity to develop and validate their code using the Intel® Manycore Testing Lab. This 40-core, 80-thread development environment has the latest hardware and software available and will be used by this year’s judges to test the winning entries in Threading Challenge 2011 Phase 1.

The Intel® Manycore Testing Lab (MTL) will be made available to Threading Challenge 2011 contestants. Use of the MTL will give participants the opportunity to write and test their code on systems exactly configured to what the judges will be using to score submitted entries. No more guessing about if your code will build or how it will run. (There is no requirement to use the MTL for any part of the contest. It is strictly an optional alternative being made available to those that wish to use it.)

Related Articles