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  • What is wrong with the JavaScript event handling in this example? (Using click() and hover() jQuery

    - by Bungle
    I'm working on a sort of proof-of-concept for a project that approximates Firebug's inspector tool. For more details, please see this related question. Here is the example page. I've only tested it in Firefox: http://troy.onespot.com/static/highlight.html The idea is that, when you're mousing over any element that can contain text, it should "highlight" with a light gray background to indicate the boundaries of that element. When you then click on the element, it should alert() a CSS selector that matches it. This is somewhat working in the example linked above. However, there's one fundamental problem. When mousing over from the top of the page to the bottom, it will pick up the paragraphs, <h1> element, etc. But, it doesn't get the <div>s that encompass those paragraphs. However, for example, if you "sneak up" on the <div> that contains the two paragraphs "The area was settled..." and "Austin was selected..." from the left - tracing down the left edge of the page and entering the <div> just between the two paragraphs (see this screenshot) - then it is picked up. I assume this has something to do with the fact that I haven't attached an event handler to the <body> element (where you're entering the <div> from if you enter from the left), but I have attached handlers to the <p>s (where you're entering from if you come from the top or bottom). There are also other issues with mousing in and out elements - background colors that "stick" and the like - that I think are also related. As indicated in the related question posted above, I suspect there is something about event bubbling that I don't understand that is causing unexpected behavior. Can anyone spot what's wrong with my code? Thanks in advance for any help!

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  • Copying Columns from Grid to Clipboard in SQL Developer

    - by thatjeffsmith
    There are several ways to get data from a query or a table|view to the clipboard. You know the tried and true, copy and paste. But what if you only want one or more columns, not every column? There are several ways to do this, let’s see if we can’t identify all of them. Write your query to only include the data you want Obvious? Yes. Needed to be said? Definitely. The best tuning tip is to only ask for the data you need, only when you absolutely need it. But let’s look at a few more practical ways to do this. Hide the unwanted columns Mouse right click on an column header. In the context menu, select ‘Columns.’ Hide the columns you don’t want. Copy and paste. WYSIWYG Grids, Hide Columns and Filter Rows Mouse select the columns Obvious, but a bit painful. For a very large dataset, you’ll be holding down the Shift and PageDown buttons – but it works. Remember to use Ctrl+Shift+C to get the column headers with the data. Use the Export Wizard This used to be called ‘Unload’ – agreed, not a great name. So, we changed it. In a grid, right mouse click on the data, and on the context menu, select ‘Export…’ Select your format – I suggest ‘delimited’ or ‘fixed’ for copying data to the clipboard. You can export to the clipboard, yes you can! Click ‘Next.’ Click in the Columns dialog, and choose the columns you want copied. Trim the columns you don't want copied Click ‘Finish.’ Alt or Ctrl tab to your window or application of choice. And Paste! "FIRST_NAME" "LAST_NAME" "Donald" "OConnell" "Douglas" "Grant" "Jennifer" "Whalen" "Pat" "Fay" "Susan" "Mavris" "William" "Gietz" "Alexander" "Hunold" "Bruce" "Ernst" "David" "Austin" "Valli" "Pataballa" "Diana" "Lorentz" "Daniel" "Faviet" "John" "Chen" "Ismael" "Sciarra" "Jose Manuel" "Urman" "Luis" "Popp" "Alexander" "Khoo" "Shelli" "Baida" "Sigal" "Tobias" "Guy" "Himuro" "Karen" "Colmenares" "Matthew" "Weiss" "Adam" "Fripp" "Payam" "Kaufling" "Shanta" "Vollman" "Kevin" "Mourgos" "Julia" "Nayer" "Irene" "Mikkilineni" ... There’s probably at least 2 or 3 more ways, but… But, try these and let me know how we can improve things. I’ve already gotten a request to be able to include the SQL text used to populate the dataset on the the copy to clipboard, and it’s now on our to-do list

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  • Upcoming EMEA, APAC & US Events with MySQL in 2014

    - by Lenka Kasparova
    As an update to the previous announcement from Mar 25, 2014 please find below the updated list of events where MySQL Community team is attending and/or supporting. This time you can find not only EMEA & APAC ones but also conferences & events we are covering in the US & Canada. You are invited to meet our engineers at the events below.   EMEA  NEW!! BGOUG, Sandanski, Bulgaria, June 13, 2014  Georgi Kodinov will attend and speak at this local Oracle User Group event. Feel free to come. PHP Tour Lyon, Lyon, France, June 23-24, 2014 MySQL team is going to be part of this show as well, we are not going to have a booth here but very active networking by our french MySQL team around the event. Come to meet us and talk to us! NEW!! Converge Conference, Glasgow, Scotland, August 15-16, 2014  MySQL Community Manager, David Stokes attends with MySQL talk. NEW!! CakeFest, Madrid, Spain, August 21-24, 2014  A talk on "Scaling Your MySQL instances AND keeping your Sanity" will be given by the MySQL Community Manager, David Stokes. Froscon 2014, St.Augustin, Germany, August 23-24, 2014 Please visit our booth as well as watch the Froscon website for the schedule updates. NEW!! SymfonyLive, UK, London, September 25-26, 2014 MySQL Community Magers, David Stokes & Morgan Tocker submitted MySQL talks for this show. Schedule will be announced later on. DrupalCon Amsterdam, The Netherlands, September 29-Oct 3, 2014 Meet us at our booth at DrupalCon Amsterdam. For the schedule please watch the DrupalCon website. All Your Base, Oxford UK, October 17, 2014  Come to visit our MySQL booth and talk to our MySQL experts. NEW!! WebTechCon / IPC, Munich Germany, October 26-29, 2014 NEW!! DOAG, Nuremberg, Germany, November 18-20, 2014 There will be a full day of MySQL talks and one full day of MySQL workshop & sessions with live demo. This event is simply hard to miss! NEW!! Forum PHP Paris, France, November 21-22, 2014 More details: TBD NEW!! UK OUG, Liverpool, UK, December 8-10, 2014 MySQL will be part of the Oracle booth and we hope to get more space for MySQL talks.  USA NEW!! Texas Linux Fest, Austin, Texas, US, June 13-14, 2014 NEW!! SouthEast Linux Fest, Charlotte, US, June 20-22, 2014 NEW!! Debian Conference 2014, Portland, OR, US, August 23-31, 2014 NEW!! FossetCon, Orlando, US, September 11-13, 2014 NEW!! Oracle Open World, San Francisco, US, September 29-October 3, 2014 NEW!! MySQL Central @ Open/World, San Francisco, US, September 29-October 3, 2014 NEW!! PyTexas 2014, Dallas, TX, US, October 3-5, 2014 NEW!! All Things Open (replacing POSSCON), Raleigh, NC, October 23-24, 2014 NEW!! Ohio LinuxFest 2014, Columbus, Ohio, US, October 24-25, 2014 NEW!! ZendCon PHP, Santa Clara, US, October 27-30, 2014 NEW!! Kuali Days 2014, Indianapolis, US, November 10-13, 2014 NEW!! Live 360, Orlando, FL, US, November 17-20, 2014 APAC OpenSourceConference Japan, Hokkaido, June 13-14, 2014 MySQL is represented by Ryusuke Kajiyama with the talk on "MySQL Technology Updates". NEW!! db tech showcase, Osaka Japan, June 18-20, 2014 Three MySQL talks are scheduled for this show, "MySQL for Oracle DBA" & "MySQL Technology Updates" by Ryusuke Kajiyama. The last talk will be on MySQL Fabric by Yoshiaki Yamasaki. NEW!! PyCon Singapore, Singapore, June 18-20, 2014 Ryusuke Kajiyama will be talking about "Sharding and scale-out using Python-based MySQL Fabric". NEW!! COSCUP, Taipei, Taiwan, July 19-20, 2014 We are going to run a technical session on MySQL Workbench & one talk on how to make MySQL better MySQL. NEW!! PyCon New Zealand, Wellington, New Zealand, September 13-14, 2014 MySQL talks were submitted as well as one talk by Solaris Modernization team on Python & Solaris, watch the website for schedule updates. NEW!! PyCon Japan, Tokyo Japan, September 13-15, 2014 MySQL will be a MySQL session speaker, no schedule is announced yet. Ruby Kaigi, Tokyo, Japan, September 18-20, 2014 Another event MySQL supports and attends in APAC region. Ruby Kaigi is the international Ruby Conference in Japan, Tokyo. Ruby started in Japan, so Ruby Kaigi has excellent speakers and developers! MySQL team is going to be present at this conference with MySQL talks and active networking around the venue. NEW!! PyCon India, Bangalore, India, September 26-28, 2014 A MySQL talk on "MySQL Utilities scaling MySQL with Python" has been submitted, please watch the PyCon website for the schedule updates. NEW!! OpenSourceConference Japan, Tokyo, October 18-19, 2014 NEW!! OpenSource India, Bengaluru, India, November 7-8, 2014 NEW!! OpenSourceConference Japan, Fukuoka, November 14-15, 2014 You can check the MySQL wikis for updates on the conferences we are attending. Next time I hope to have more details for each event above (especially for the US ones).

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  • OTN Architect Day Headed to Reston, VA - May 16

    - by Bob Rhubart
    In 2011 OTN Architect Day made stops in Chicago, Denver, Phoenix, Redwood Shores, and Toronto. The 2012 series begins with OTN Architect Day in Reston, VA on Wednesday May 16. Registration is now open for this free event, but don't get caught napping -- seating is limited, and the event is just 5 weeks away. The information below reflects the most recent updates to the event agenda, including the addition of Oracle ACE Director Kai Yu as the guest keynote speaker. Kai is Senior System Engineer / Architect at Dell, Inc., and has been very busy of late as a speaker at various industry and Oracle User Group events. I'm very happy Kai has agreed to make the trek from his hometown in Austin, TX to share his insight at the Architect Day event in Reston.  If you're in the area, put this one on your calendar. You won't be sorry.   Venue Sheraton Reston Hotel 11810 Sunrise Valley Drive Reston, VA 20191 Event Agenda 8:30 am - 9:00 am Registration and Continental Breakfast 9:00 am - 9:15 am Welcome and Opening Comments 9:15 am - 10:00 am Engineered Systems: Oracle's Vision for the Future | Ralf Dossman Oracle's Exadata and Exalogic are impressive products in their own right. But working in combination they deliver unparalleled transaction processing performance with up to a 30x increase over existing legacy systems, with the lowest cost of ownership over a 3 or 5 year basis than any other hardware. In this session you'll learn how to leverage Oracle's Engineered Systems within your enterprise to deliver record-breaking performance at the lowest TCO. 10:00 am - 10:30 am High Availability Infrastructure for Cloud Computing | Kai Yu Infrastructure high availability is extremely critical to Cloud Computing. In a Cloud system that hosts a large number of databases and applications with different SLAs, any unplanned outage can be devastating, and even a small planned downtime may be unacceptable. This presentation will discuss various technology solutions and the related best practices that system architects should consider in cloud infrastructure design to ensure high availability. 10:30 am - 10:45 am Break 10:45 am - 11:30 am Breakout Sessions: (pick one) Innovations in Grid Computing with Oracle Coherence | Bjorn Boe Learn how Coherence can increase the availability, scalability and performance of your existing applications with its advanced low-latency data-grid technologies. Also hear some interesting industry-specific use cases that customers had implemented and how Oracle is integrating Coherence into its Enterprise Java stack. Cloud Computing - Making IT Simple | Scott Mattoon The road to Cloud Computing is not without a few bumps. This session will help to smooth out your journey by tackling some of the potential complications. We'll examine whether standardization is a prerequisite for the Cloud. We'll look at why refactoring isn't just for application code. We'll check out deployable entities and their simplification via higher levels of abstraction. And we'll close out the session with a look at engineered systems and modular clouds. 11:30 pm - 12:15 pm Breakout Sessions: (pick one) Oracle Enterprise Manager | Joe Diemer Oracle Enterprise Manager (EM) provides complete lifecycle management for the cloud - from automated cloud setup to self-service delivery to cloud operations. In this session you'll learn how to take control of your cloud infrastructure with EM features including Consolidation Planning and Self-Service provisioning with Metering and Chargeback. Come hear how Oracle is expanding its management capabilities into the cloud! Rationalization and Defense in Depth - Two Steps Closer to the Clouds | Dave Chappelle Security represents one of the biggest concerns about cloud computing. In this session we'll get past the FUD with a real-world look at some key issues. We'll discuss the infrastructure necessary to support rationalization and security services, explore architecture for defense -in-depth, and deal frankly with the good, the bad, and the ugly in Cloud security. 12:15 pm - 1:15 pm Lunch 1:40 pm - 2:00 pm Panel Discussion - Q&A 2:00 pm - 2:45 pm Breakout Sessions: (pick one) 21st Century SOA | Peter Belknap Service Oriented Architecture has evolved from concept to reality in the last decade. The right methodology coupled with mature SOA technologies has helped customers demonstrate success in both innovation and ROI. In this session you will learn how Oracle SOA Suite's orchestration, virtualization, and governance capabilities provide the infrastructure to run mission critical business and system applications. And we'll take a special look at the convergence of SOA & BPM using Oracle's Unified technology stack. Track B: Oracle Cloud Reference Architecture | Anbu Krishnaswamy Cloud initiatives are beginning to dominate enterprise IT roadmaps. Successful adoption of Cloud and the subsequent governance challenges warrant a Cloud reference architecture that is applied consistently across the enterprise. This presentation gives an overview of Oracle's Cloud Reference Architecture, which is part of the Cloud Enterprise Technology Strategy (ETS). Concepts covered include common management layer capabilities, service models, resource pools, and use cases. 2:45 pm - 3:00 pm Break 3:00 pm - 4:00 pm Roundtable Discussions 4:00 pm - 4:15 pm Closing Comments & Readouts from Roundtable 4:15 pm - 5:00 pm Cocktail Reception / Networking Session schedule and content subject to change.

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  • IE9, LightSwitch Beta 2 and Zune HD: A Study in Risk Management?

    - by andrewbrust
    Photo by parl, 'Risk.’ Under Creative Commons Attribution-NonCommercial-NoDerivs License This has been a busy week for Microsoft, and for me as well.  On Monday, Microsoft launched Internet Explorer 9 at South by Southwest (SXSW) in Austin, TX.  That evening I flew from New York to Seattle.  On Tuesday morning, Microsoft launched Visual Studio LightSwitch, Beta 2 with a Go-Live license, in Redmond, and I had the privilege of speaking at the keynote presentation where the announcement was made.  Readers of this blog know I‘m a fan of LightSwitch, so I was happy to tell the app dev tools partners in the audience that I thought the LightSwitch extensions ecosystem represented a big opportunity – comparable to the opportunity when Visual Basic 1.0 was entering its final beta roughly 20 years ago.  On Tuesday evening, I flew back to New York (and wrote most of this post in-flight). Two busy, productive days.  But there was a caveat that impacts the accomplishments, because Monday was also the day reports surfaced from credible news agencies that Microsoft was discontinuing its dedicated Zune hardware efforts.  While the Zune brand, technology and service will continue to be a component of Windows Phone and a piece of the Xbox puzzle as well, speculation is that Microsoft will no longer be going toe-to-toe with iPod touch in the portable music player market. If we take all three of these developments together (even if one of them is based on speculation), two interesting conclusions can reasonably be drawn, one good and one less so. Microsoft is doubling down on technologies it finds strategic and de-emphasizing those that it does not.  HTML 5 and the Web are strategic, so here comes IE9, and it’s a very good browser.  Try it and see.  Silverlight is strategic too, as is SQL Server, Windows Azure and SQL Azure, so here comes Visual Studio LightSwitch Beta 2 and a license to deploy its apps to production.  Downloads of that product have exceeded Microsoft’s projections by more than 50%, and the company is even citing analyst firms’ figures covering the number of power-user developers that might use it. (I happen to think the product will be used by full-fledged developers as well, but that’s a separate discussion.) Windows Phone is strategic too…I wasn’t 100% positive of that before, but the Nokia agreement has made me confident.  Xbox as an entertainment appliance is also strategic.  Standalone music players are not strategic – and even if they were, selling them has been a losing battle for Microsoft.  So if Microsoft has consolidated the Zune content story and the ZunePass subscription into Xbox and Windows Phone, it would make sense, and would be a smart allocation of resources.  Essentially, it would be for the greater good. But it’s not all good.  In this scenario, Zune player customers would lose out.  Unless they wanted to switch to Windows Phone, and then use their phone’s battery for the portable media needs, they’re going to need a new platform.  They’re going to feel abandoned.  Even if Zune lives, there have been other such cul de sacs for customers.  Remember SPOT watches?  Live Spaces?  The original Live Mesh?  Microsoft discontinued each of these products.  The company is to be commended for cutting its losses, as admitting a loss isn’t easy.  But Redmond won’t be well-regarded by the victims of those decisions.  Instead, it gets black marks. What’s the answer?  I think it’s a bit like the 1980’s New York City “don’t block the box” gridlock rules: don’t enter an intersection unless you see a clear path through it.  If the light turns red and you’re blocking the perpendicular traffic, that’s your fault in judgment.  You get fined and get points on your license and you don’t get to shrug it off as beyond your control.  Accountability is key.  The same goes for Microsoft.  If it decides to enter a market, it should see a reasonable path through success in that market. Switching analogies, Microsoft shouldn’t make investments haphazardly, and it certainly shouldn’t ask investors to buy into a high-risk fund that is sold as safe and which offers only moderate returns.  People won’t continue to invest with a fund manager with a track record of over-zealous, imprudent, sub-prime investments.  The same is true on the product side for Microsoft, and not just with music players and geeky wrist watches.  It’s true of Web browsers, and line-of-business app dev tools, and smartphones, and cloud platforms and operating systems too.  When Microsoft is casual about its own risk, it raises risk for its customers, and weakens its reputation, market share and credibility.  That doesn’t mean all risk is bad, but it does mean no product team’s risk should be taken lightly. For mutual fund companies, it’s the CEO’s job to give his fund managers autonomy, but to make sure they’re conforming to a standard of rational risk management.  Because all those funds carry the same brand, and many of them serve the same investors. The same goes for Microsoft, its product portfolio, its executive ranks and its product managers.

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  • Your Day-by-Day Guide to Agile PLM at Oracle OpenWorld 2012

    - by Kerrie Foy
    This year’s Oracle OpenWorld conference is nearly here, and we’re all excited about what we have planned! With five days of activities and customer presenters from market leaders and top innovators like The Coca-Cola Company, Starbucks, JDSU, Facebook, GlobalFoundries, and more, this is an event you don't want to miss. I've compiled this day-by-day guide to help anyone keep track of all the “Product Lifecycle Management and Product Value Chain” sessions and activities at OpenWorld 2012, September 30 – October 4 in San Francisco, California.  Monday, October 1 There are great networking activities on Sunday September 30, but PLM specific sessions start after general conference keynotes on Monday, October 1 at 10:45 a.m. at the InterContinental Hotel in room Telegraph Hill. In fact, most of our sessions this year will be held in this room, which is still close to the conference keynotes in Moscone, but just far enough away to allow some focused networking and discussions.   This first session, 10:45 – 11:45 a.m. is a joint session with the Agile and AutoVue teams, entitled “Streamline PLM Design-to-Manufacturing Processes with AutoVue Visualization Soltuions” featuring presenters from Oracle as well as joint AutoVue and Agile PLM customer GlobalFoundries. In the following 12:15 – 1:15 p.m. slot, there are two sessions to choose from, so if you have a team of representatives attending OpenWorld, you may consider splitting up to catch both of these: a) Our General Session will be held in the InterContinental Hotel Ballroom C, which will cover our complete enterprise PLM strategy, product updates, and roadmaps. It’s our pleasure to feature a customer keynote presentation from Chris Bedi, CIO, and Rajeev Sethi, Director IT Business Engagement, of JDSU. b) A focused session on integrating PLM with Engineering and Supply Chain Systems will be held on the second floor of Moscone West (next to the InterContinental) in room 2022. Join to discover how these types of integrations help companies manage common and integrated design information across all MCAD, ECAD, and software components. After a lunch break and perhaps a visit to the Demogrounds in Moscone West, select from two product roadmap sessions in the next time slot (3:15 – 4:15 p.m.): an Agile 9.3.x session located in the InterContinental’s Ballroom C, and an Agile PLM for Process session located back in the InterContinental’s Telegraph Room. Both sessions will have strong content around each product line’s latest releases, vision, and customer examples. We are very pleased to feature Daniel Soosai of Facebook in the A9 session and Vinnie D’Agostino of The Coca-Cola Company in the PLM for Process session. Afterwards, hang in there for one last session of the day from 4:45 – 5:45 p.m.; it’s an insightful discussion on leveraging Agile PLM as the Foundation for Enterprise Quality Management, and it’s sure to be one of the best. In the Telegraph Room, this session will feature Oracle experts, partner co-presenter David Bartlett from CPG Solutions, and customer co-presenter Thomas Crowe, CIO of PL Developments. Hear their experience around implementing collaborative, integrated solutions to ensure effective knowledge transfer throughout an organization, and how to perform analysis in real time to resolve product quality issues swiftly and efficiently. On Monday evening there will be plenty of industry, product, and partner dinners, so take advantage of all the networking opportunities and catch some great tunes at the 5 day Oracle OpenWorld Music Festival! Tuesday, October 2 Tuesday starts early with a special PLM Networking Brunch, sponsored by several partners, from 8:30 a.m. – 10:30 a.m. at the B Restaurant that sits atop Yerba Buena Gardens. You’ll have the unique opportunity to meet with like-minded industry peers and a PLM partner to discuss a topic of your choosing while enjoying a delicious meal. Registration is required, so to inquire about attending this brunch, please email Terri.Hiskey-AT-oracle.com. After wrapping up your conversations over brunch, head over to the Marriott Marquis in the Nob Hill CD room for a chance to experience the Oracle Product Lifecycle Analytics solution in a Hands-On Lab, open from 10:15 a.m. – 12:45 p.m. Experts will be there to answer your questions. Back in the InterContinental Hotel’s Telegraph room, the session on “Ideation and Requirements Management: Capturing the Voice of the Customer” begins at 11:45 a.m. – 12:45 p.m. This may be the session for you if you’re struggling with challenges like too many repositories of customer needs, requests, and ideas; limited visibility into which ideas are being advanced by customers and field resources; or if you’re unable to leverage internal expertise to expose effort and potential risks. This session will discuss how Agile PLM can help you overcome ideation challenges to deliver the right products to their targeted markets and fulfill customer desires. Next, from 1:15 – 2:15 p.m. join us for a session on Managing Profitable Innovation with Oracle Product Lifecycle Analytics. If you missed the Hands-on Lab, have more questions, or simply want to be inspired by the product’s forward-thinking vision and capabilities, this is a great opportunity to meet the progressive-minded executives behind the application. After this session, it may be a good opportunity to swing by the Demogrounds in Moscone West and visit the Agile PLM demos at exhibit booths #81 for Agile PLM for Discrete Manufacturing, #70 for Agile PLM for Process, and #82 for AutoVue and Agile PLM Enterprise Visualization. Check out the related Supply Chain Management booths close by if you’re interested - here's the map. There’s always lots to see and do around the exhibit area. But don’t forget the last session of the day from 5:00 p.m. – 6:00 p.m. in Telegraph Hill on Managing Product Innovation and Compliance in Life Science Companies, a “must-see” if you’re in this industry. Launching innovative products quickly is already a high-stakes challenge, but companies in the life sciences industry face uniquely severe consequences when new products don’t perform or comply as required. In recent years, more and more regulations have become mandatory, and new ones, such as REACH, are currently going into effect for several companies. Customer presenters from pharmaceutical leader Eli Lilly will share how they’ve leveraged Agile PLM to deliver high-quality, innovative products in a fast-paced, heavily regulated market environment. Tuesday evening unwind at the Supply Chain Management Reception from 6:00 – 8:00 p.m. at the premier boutique Roe Nightclub and Lounge, which is located about three blocks down on Howard Street (on the other side of Moscone from the InterContinental Hotel). Registration is required. Click here for the details.   Wednesday, October 3 We have another full line-up on Wednesday, so be ready for an action-packed day. We start with a session at 10:15 – 11:15 a.m. in the Telegraph Room where we have a session on “PLM for Consumer Products: Building an Engine for Quality and Innovation” with featured presenters from Starbucks and partner Kalypso. This is a rare opportunity to learn directly from Starbucks how they instill quality and innovation throughout their organization, products, and processes, leveraging PLM disciplines with strong support from their partner.  If you’re not in the consumer products industry, we recommend attending another session at 10:15 – 11:15 a.m. in Moscone West room 3005: “Eco-Enterprise Innovation Awards and the Business Case for Sustainability” featuring Jeff Henley, Oracle’s Chairman of the Board and Jon Chorley, Chief Sustainability Officer. Oracle will honor select customers with Oracle’s Eco-Enterprise Innovation award, which recognizes customers and their respective partners who rely on Oracle products to support their green business practices to reduce their environmental impact while improving business efficiencies and reducing costs. The awards presentation is followed by a panel discussion with customers and Oracle executives, who describe how these award-winning organizations are embracing environmental initiatives as a central part of their business strategy and how information technology plays a pivotal role. Next at 11:45 a.m. – 12:45 p.m. in Telegraph Hill attend our session devoted to exploring Product Lifecycle Management’s role in Software Lifecycle Management. This is a thought leadership session with Oracle experts in the field on the importance of change management, and we’ll discuss how Oracle has for years leveraged Agile PLM to develop Agile PLM. If software lifecycle management doesn’t apply to your business or you’d rather engage in some lively one-on-one discussions, we also have a “Supply Chain Meet the Experts” session in Moscone West Room 2001A. Product experts, thought leaders and executives will be on hand to discuss your questions/topics, so come prepared. This session tends to fill up fast so try to get in early. At 1:15 – 2:15 p.m. join us back in Telegraph Hill for a session focused on leveraging the Agile Product Portfolio Management application as the Product Development Master Schedule to improve efficiencies, optimize resources, and gain visibility across projects enterprise-wide to improve portfolio profitability. Customer presenters from Broadcom will explain how they’ve leveraged the product to enable a master schedule with enterprise-level, phase-gate program and project collaboration and resource optimization. Again in Telegraph Hill from 3:30 – 4:30 p.m. we have an interesting session with leading semiconductor customer LSI and partner Kalypso on how LSI leveraged Agile PLM to advance from homegrown applications to complete Product Value Chain Management. That type of transition can be challenging, and LSI details how they were able to achieve their goals and the value they gained along the journey – a fascinating account for any company interested in leveraging best practices to innovate their business processes and even end products. Lastly, we’ll wrap up in Telegraph Hill from 5:00 – 6:00 p.m. with a session on “Ensuring New Product Success by Achieving Excellence in New Product Introduction.” This is a cross-industry session, guaranteed to deliver insight in the often elusive practice of creating winning products, and we’re very excited about. According to IDC Manufacturing Insights analyst Joe Barkai, “Product Failures are not necessarily a result of bad ideas…they are a result of suboptimal decisions.” We’ll show you how to wire your business processes to enhance decision-making and maximize product potential. Now, quickly hit your hotel room to freshen up and then catch one of the many complimentary shuttles to the much-anticipated Oracle Customer Appreciation Event on Treasure Island. We have a very exciting show planned – check out what’s in store here. Thursday, October 4 PLM has a light schedule on Thursday this year with just one session, but this again is one of our best sessions on managing the Product Value Chain: at 11:15 a.m – 12:15 p.m.in Telegraph Hill, it’s a customer and partner driven session with Sonoco Products and Deloitte telling their story about how to achieve integrated change control by interfacing Agile PLM with Oracle E-Business Suite. Sonoco Products, a global manufacturer of consumer and industrial packaging materials, with its systems integrator, Deloitte, is doing this by implementing prebuilt integration (Oracle Design-to-Release Integration Pack for Agile Product Lifecycle Management for Process and Oracle Process) to integrate Agile with Oracle Product Hub/Oracle Product Information Management and Oracle E-Business Suite. This session presents a case study of how Sonoco is leveraging this solution to improve data quality and build a framework for stronger master data governance. Even though that ends our PLM line-up at OpenWorld, there will still be many sessions and activities at the conference, so visit the Oracle OpenWorld website to review agendas and build your schedule. And of course, download and bring this guide and the latest version of the Agile PLM Focus-On Document (available soon!). San Francisco is a wonderful city to explore, and we’re glad you’re considering joining the Agile PLM team at Oracle OpenWorld!  I hope to see you there! Follow me before the conference and on site for real-time updates about #OOW12 on Twitter @Kerrie_Foy or @AgilePLM.

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  • CodePlex Daily Summary for Sunday, May 23, 2010

    CodePlex Daily Summary for Sunday, May 23, 2010New ProjectsA2Command: Apple 2 port of CBM-Command (http://cbmcommand.codeplex.com)AgUnit: AgUnit is a plugin for Jetbrains ReSharper (R#) that allows you to run and debug Silverlight unit tests from within Visual Studio.BSonPosh Powershell Module: A collection of useful Powershell functions I have written and collected over the years. It is a Powershell v2 Module composed of mostly scripts.DB Restriker: Simple tool for lookup, parsing, searching some standard databases using wildcards and pattern recognition.Entity Framework Repository & Unit of Work Template: T4 Template for Entity Framework 4 for creating a data access layer using the repository and unit of work patterns. Designed to work well with dep...Fiction Catalog: A catalog project designed to store information about fictional literature.Giving a Presentation: Useful for people doing presentations, this application hides desktop icons, disables screensaver, closes chosen programs when presentation starts,...glueless: Glueless is a local message bus which allows architect to design highly decoupled systems and applications. Glueless is a step beyond dependency i...HtmlCodeIt: Take any code and format it so that it can be viewed properly on a web browser, blog post or website.just testproject :): just have a test!KanbanTaskboard: The aim of the project is to design and implement a functional prototype for visualizing and operating a multi-platform virtual "Kanban Taskboard”Life System: Life SystemOaSys Project: Project Oasys is a project that aims to help solve desertification. Scoring of pingPong Game: Scoring of pingPong GameSilverlight Web Comic: The Silverlight Web Comic makes easier for the people create your own comic with your own pictures o drawings, and add the globes of text like the ...TickSharp: C# Wrapper for http://TickSpot.com RESTful API.Traductor: El Traductor es una aplicación de escritorio para traducción de frases entre distintos idiomas basada en la plataforma Silverlight Out Of Browser y...WatchersNET.SkinObjects.ModulActionsMenu: Displays the Module Actions Menu as a Unsorted CSS Menu.xxfd1r4w96: testingNew ReleasesAgUnit: AgUnit 0.1: Initial release of AgUnit. 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  • Fluent NHibernate Many to one mapping

    - by Jit
    I am new to Hibernate world. It may be a silly question, but I am not able to solve it. I am testing many to One relationship of tables and trying to insert record. I have a Department table and Employee table. Employee and Dept has many to One relationship here. I am using Fluent NHibernate to add records. All codes below. Pls help - SQL Code create table Dept ( Id int primary key identity, DeptName varchar(20), DeptLocation varchar(20)) create table Employee ( Id int primary key identity, EmpName varchar(20),EmpAge int, DeptId int references Dept(Id)) Class Files public partial class Dept { public virtual System.String DeptLocation { get; set; } public virtual System.String DeptName { get; set; } public virtual System.Int32 Id { get; private set; } public virtual IList<Employee> Employees { get; set; } } public partial class Employee { public virtual System.Int32 DeptId { get; set; } public virtual System.Int32 EmpAge { get; set; } public virtual System.String EmpName { get; set; } public virtual System.Int32 Id { get; private set; } public virtual Project.Model.Dept Dept { get; set; } } Mapping Files public class DeptMapping : ClassMap { public DeptMapping() { Id(x = x.Id); Map(x = x.DeptName); Map(x = x.DeptLocation); HasMany(x = x.Employees) .Inverse() .Cascade.All(); } } public class EmployeeMapping : ClassMap { public EmployeeMapping() { Id(x = x.Id); Map(x = x.EmpName); Map(x = x.EmpAge); Map(x = x.DeptId); References(x = x.Dept) .Cascade.None(); } } My Code to add try { Dept dept = new Dept(); dept.DeptLocation = "Austin"; dept.DeptName = "Store"; Employee emp = new Employee(); emp.EmpName = "Ron"; emp.EmpAge = 30; IList<Employee> empList = new List<Employee>(); empList.Add(emp); dept.Employees = empList; emp.Dept = dept; IRepository<Dept> rDept = new Repository<Dept>(); rDept.SaveOrUpdate(dept); } catch (Exception ex) { Console.WriteLine(ex.Message); } Here i am getting error as InnerException = {"Invalid column name 'Dept_id'."} Message = "could not insert: [Project.Model.Employee][SQL: INSERT INTO [Employee] (EmpName, EmpAge, DeptId, Dept_id) VALUES (?, ?, ?, ?); select SCOPE_IDENTITY()]"

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  • How to use Koala Facebook Graph API?

    - by reko
    I am a Rails newbie. I want to use Koala's Graph API. In my controller @graph = Koala::Facebook::API.new('myFacebookAccessToken') @hello = @graph.get_object("my.Name") When I do this, I get something like this { "id"=>"123456", "name"=>"First Middle Last", "first_name"=>"First", "middle_name"=>"Middle", "last_name"=>"Last", "link"=>"http://www.facebook.com/MyName", "username"=>"my.name", "birthday"=>"12/12/1212", "hometown"=>{"id"=>"115200305133358163", "name"=>"City, State"}, "location"=>{"id"=>"1054648928202133335", "name"=>"City, State"}, "bio"=>"This is my awesome Bio.", "quotes"=>"I am the master of my fate; I am the captain of my soul. - William Ernest Henley\r\n\r\n"Don't go around saying the world owes you a living. The world owes you nothing. It was here first.\" - Mark Twain", "work"=>[{"employer"=>{"id"=>"100751133333", "name"=>"Company1"}, "position"=>{"id"=>"105763693332790962", "name"=>"Position1"}, "start_date"=>"2010-08", "end_date"=>"2011-07"}], "sports"=>[{"id"=>"104019549633137", "name"=>"Sport1"}, {"id"=>"103992339636529", "name"=>"Sport2"}], "favorite_teams"=>[{"id"=>"105467226133353743", "name"=>"Fav1"}, {"id"=>"19031343444432369133", "name"=>"Fav2"}, {"id"=>"98027790139333", "name"=>"Fav3"}, {"id"=>"104055132963393331", "name"=>"Fav4"}, {"id"=>"191744431437533310", "name"=>"Fav5"}], "favorite_athletes"=>[{"id"=>"10836600585799922", "name"=>"Fava1"}, {"id"=>"18995689436787722", "name"=>"Fava2"}, {"id"=>"11156342219404022", "name"=>"Fava4"}, {"id"=>"11169998212279347", "name"=>"Fava5"}, {"id"=>"122326564475039", "name"=>"Fava6"}], "inspirational_people"=>[{"id"=>"16383141733798", "name"=>"Fava7"}, {"id"=>"113529011990793335", "name"=>"fava8"}, {"id"=>"112032333138809855566", "name"=>"Fava9"}, {"id"=>"10810367588423324", "name"=>"Fava10"}], "education"=>[{"school"=>{"id"=>"13478880321332322233663", "name"=>"School1"}, "type"=>"High School", "with"=>[{"id"=>"1401052755", "name"=>"Friend1"}]}, {"school"=>{"id"=>"11482777188037224", "name"=>"School2"}, "year"=>{"id"=>"138383069535219", "name"=>"2005"}, "type"=>"High School"}, {"school"=>{"id"=>"10604484633093514", "name"=>"School3"}, "year"=>{"id"=>"142963519060927", "name"=>"2010"}, "concentration"=>[{"id"=>"10407695629335773", "name"=>"c1"}], "type"=>"College"}, {"school"=>{"id"=>"22030497466330708", "name"=>"School4"}, "degree"=>{"id"=>"19233130157477979", "name"=>"c3"}, "year"=>{"id"=>"201638419856163", "name"=>"2011"}, "type"=>"Graduate School"}], "gender"=>"male", "interested_in"=>["female"], "relationship_status"=>"Single", "religion"=>"Religion1", "political"=>"Political1", "email"=>"[email protected]", "timezone"=>-8, "locale"=>"en_US", "languages"=>[{"id"=>"10605952233759137", "name"=>"English"}, {"id"=>"10337617475934611", "name"=>"L2"}, {"id"=>"11296944428713061", "name"=>"L3"}], "verified"=>true, "updated_time"=>"2012-02-24T04:18:05+0000" } How do I show this entire hash in the view in a good format? This is what I did from what ever I learnt.. In my view <% @hello.each do |key, value| %> <li><%=h "#{key.to_s} : #{value.to_s}" %></li> <% end %> This will get the entire thing converted to a list... It works awesome if its just one key.. but how to work with multiple keys and show only the information... something like when it outputs hometown : City, State rather than something like hometown : {"id"=>"115200305133358163", "name"=>"City, State"} Also for education if I just say education[school][name] to display list of schools attended? The error i get is can't convert String into Integer I also tried to do this in my controller, but I get the same error.. @fav_teams = @hello["favorite_teams"]["name"] Also, how can I save all these to the database.. something like just the list of all schools.. not their id no's? Update: The way I plan to save to my database is.. lets say for a user model, i want to save to database as :facebook_id, :facebook_name, :facebook_firstname, ...., :facebook_hometown .. here I only want to save name... when it comes to education.. I want to save.. school, concentration and type.. I have no idea on how to achieve this.. Looking forward for help! thanks!

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  • How John Got 15x Improvement Without Really Trying

    - by rchrd
    The following article was published on a Sun Microsystems website a number of years ago by John Feo. It is still useful and worth preserving. So I'm republishing it here.  How I Got 15x Improvement Without Really Trying John Feo, Sun Microsystems Taking ten "personal" program codes used in scientific and engineering research, the author was able to get from 2 to 15 times performance improvement easily by applying some simple general optimization techniques. Introduction Scientific research based on computer simulation depends on the simulation for advancement. The research can advance only as fast as the computational codes can execute. The codes' efficiency determines both the rate and quality of results. In the same amount of time, a faster program can generate more results and can carry out a more detailed simulation of physical phenomena than a slower program. Highly optimized programs help science advance quickly and insure that monies supporting scientific research are used as effectively as possible. Scientific computer codes divide into three broad categories: ISV, community, and personal. ISV codes are large, mature production codes developed and sold commercially. The codes improve slowly over time both in methods and capabilities, and they are well tuned for most vendor platforms. Since the codes are mature and complex, there are few opportunities to improve their performance solely through code optimization. Improvements of 10% to 15% are typical. Examples of ISV codes are DYNA3D, Gaussian, and Nastran. Community codes are non-commercial production codes used by a particular research field. Generally, they are developed and distributed by a single academic or research institution with assistance from the community. Most users just run the codes, but some develop new methods and extensions that feed back into the general release. The codes are available on most vendor platforms. Since these codes are younger than ISV codes, there are more opportunities to optimize the source code. Improvements of 50% are not unusual. Examples of community codes are AMBER, CHARM, BLAST, and FASTA. Personal codes are those written by single users or small research groups for their own use. These codes are not distributed, but may be passed from professor-to-student or student-to-student over several years. They form the primordial ocean of applications from which community and ISV codes emerge. Government research grants pay for the development of most personal codes. This paper reports on the nature and performance of this class of codes. Over the last year, I have looked at over two dozen personal codes from more than a dozen research institutions. The codes cover a variety of scientific fields, including astronomy, atmospheric sciences, bioinformatics, biology, chemistry, geology, and physics. The sources range from a few hundred lines to more than ten thousand lines, and are written in Fortran, Fortran 90, C, and C++. For the most part, the codes are modular, documented, and written in a clear, straightforward manner. They do not use complex language features, advanced data structures, programming tricks, or libraries. I had little trouble understanding what the codes did or how data structures were used. Most came with a makefile. Surprisingly, only one of the applications is parallel. All developers have access to parallel machines, so availability is not an issue. Several tried to parallelize their applications, but stopped after encountering difficulties. Lack of education and a perception that parallelism is difficult prevented most from trying. I parallelized several of the codes using OpenMP, and did not judge any of the codes as difficult to parallelize. Even more surprising than the lack of parallelism is the inefficiency of the codes. I was able to get large improvements in performance in a matter of a few days applying simple optimization techniques. Table 1 lists ten representative codes [names and affiliation are omitted to preserve anonymity]. Improvements on one processor range from 2x to 15.5x with a simple average of 4.75x. I did not use sophisticated performance tools or drill deep into the program's execution character as one would do when tuning ISV or community codes. Using only a profiler and source line timers, I identified inefficient sections of code and improved their performance by inspection. The changes were at a high level. I am sure there is another factor of 2 or 3 in each code, and more if the codes are parallelized. The study’s results show that personal scientific codes are running many times slower than they should and that the problem is pervasive. Computational scientists are not sloppy programmers; however, few are trained in the art of computer programming or code optimization. I found that most have a working knowledge of some programming language and standard software engineering practices; but they do not know, or think about, how to make their programs run faster. They simply do not know the standard techniques used to make codes run faster. In fact, they do not even perceive that such techniques exist. The case studies described in this paper show that applying simple, well known techniques can significantly increase the performance of personal codes. It is important that the scientific community and the Government agencies that support scientific research find ways to better educate academic scientific programmers. The inefficiency of their codes is so bad that it is retarding both the quality and progress of scientific research. # cacheperformance redundantoperations loopstructures performanceimprovement 1 x x 15.5 2 x 2.8 3 x x 2.5 4 x 2.1 5 x x 2.0 6 x 5.0 7 x 5.8 8 x 6.3 9 2.2 10 x x 3.3 Table 1 — Area of improvement and performance gains of 10 codes The remainder of the paper is organized as follows: sections 2, 3, and 4 discuss the three most common sources of inefficiencies in the codes studied. These are cache performance, redundant operations, and loop structures. Each section includes several examples. The last section summaries the work and suggests a possible solution to the issues raised. Optimizing cache performance Commodity microprocessor systems use caches to increase memory bandwidth and reduce memory latencies. Typical latencies from processor to L1, L2, local, and remote memory are 3, 10, 50, and 200 cycles, respectively. Moreover, bandwidth falls off dramatically as memory distances increase. Programs that do not use cache effectively run many times slower than programs that do. When optimizing for cache, the biggest performance gains are achieved by accessing data in cache order and reusing data to amortize the overhead of cache misses. Secondary considerations are prefetching, associativity, and replacement; however, the understanding and analysis required to optimize for the latter are probably beyond the capabilities of the non-expert. Much can be gained simply by accessing data in the correct order and maximizing data reuse. 6 out of the 10 codes studied here benefited from such high level optimizations. Array Accesses The most important cache optimization is the most basic: accessing Fortran array elements in column order and C array elements in row order. Four of the ten codes—1, 2, 4, and 10—got it wrong. Compilers will restructure nested loops to optimize cache performance, but may not do so if the loop structure is too complex, or the loop body includes conditionals, complex addressing, or function calls. In code 1, the compiler failed to invert a key loop because of complex addressing do I = 0, 1010, delta_x IM = I - delta_x IP = I + delta_x do J = 5, 995, delta_x JM = J - delta_x JP = J + delta_x T1 = CA1(IP, J) + CA1(I, JP) T2 = CA1(IM, J) + CA1(I, JM) S1 = T1 + T2 - 4 * CA1(I, J) CA(I, J) = CA1(I, J) + D * S1 end do end do In code 2, the culprit is conditionals do I = 1, N do J = 1, N If (IFLAG(I,J) .EQ. 0) then T1 = Value(I, J-1) T2 = Value(I-1, J) T3 = Value(I, J) T4 = Value(I+1, J) T5 = Value(I, J+1) Value(I,J) = 0.25 * (T1 + T2 + T5 + T4) Delta = ABS(T3 - Value(I,J)) If (Delta .GT. MaxDelta) MaxDelta = Delta endif enddo enddo I fixed both programs by inverting the loops by hand. Code 10 has three-dimensional arrays and triply nested loops. The structure of the most computationally intensive loops is too complex to invert automatically or by hand. The only practical solution is to transpose the arrays so that the dimension accessed by the innermost loop is in cache order. The arrays can be transposed at construction or prior to entering a computationally intensive section of code. The former requires all array references to be modified, while the latter is cost effective only if the cost of the transpose is amortized over many accesses. I used the second approach to optimize code 10. Code 5 has four-dimensional arrays and loops are nested four deep. For all of the reasons cited above the compiler is not able to restructure three key loops. Assume C arrays and let the four dimensions of the arrays be i, j, k, and l. In the original code, the index structure of the three loops is L1: for i L2: for i L3: for i for l for l for j for k for j for k for j for k for l So only L3 accesses array elements in cache order. L1 is a very complex loop—much too complex to invert. I brought the loop into cache alignment by transposing the second and fourth dimensions of the arrays. Since the code uses a macro to compute all array indexes, I effected the transpose at construction and changed the macro appropriately. The dimensions of the new arrays are now: i, l, k, and j. L3 is a simple loop and easily inverted. L2 has a loop-carried scalar dependence in k. By promoting the scalar name that carries the dependence to an array, I was able to invert the third and fourth subloops aligning the loop with cache. Code 5 is by far the most difficult of the four codes to optimize for array accesses; but the knowledge required to fix the problems is no more than that required for the other codes. I would judge this code at the limits of, but not beyond, the capabilities of appropriately trained computational scientists. Array Strides When a cache miss occurs, a line (64 bytes) rather than just one word is loaded into the cache. If data is accessed stride 1, than the cost of the miss is amortized over 8 words. Any stride other than one reduces the cost savings. Two of the ten codes studied suffered from non-unit strides. The codes represent two important classes of "strided" codes. Code 1 employs a multi-grid algorithm to reduce time to convergence. The grids are every tenth, fifth, second, and unit element. Since time to convergence is inversely proportional to the distance between elements, coarse grids converge quickly providing good starting values for finer grids. The better starting values further reduce the time to convergence. The downside is that grids of every nth element, n > 1, introduce non-unit strides into the computation. In the original code, much of the savings of the multi-grid algorithm were lost due to this problem. I eliminated the problem by compressing (copying) coarse grids into continuous memory, and rewriting the computation as a function of the compressed grid. On convergence, I copied the final values of the compressed grid back to the original grid. The savings gained from unit stride access of the compressed grid more than paid for the cost of copying. Using compressed grids, the loop from code 1 included in the previous section becomes do j = 1, GZ do i = 1, GZ T1 = CA(i+0, j-1) + CA(i-1, j+0) T4 = CA1(i+1, j+0) + CA1(i+0, j+1) S1 = T1 + T4 - 4 * CA1(i+0, j+0) CA(i+0, j+0) = CA1(i+0, j+0) + DD * S1 enddo enddo where CA and CA1 are compressed arrays of size GZ. Code 7 traverses a list of objects selecting objects for later processing. The labels of the selected objects are stored in an array. The selection step has unit stride, but the processing steps have irregular stride. A fix is to save the parameters of the selected objects in temporary arrays as they are selected, and pass the temporary arrays to the processing functions. The fix is practical if the same parameters are used in selection as in processing, or if processing comprises a series of distinct steps which use overlapping subsets of the parameters. Both conditions are true for code 7, so I achieved significant improvement by copying parameters to temporary arrays during selection. Data reuse In the previous sections, we optimized for spatial locality. It is also important to optimize for temporal locality. Once read, a datum should be used as much as possible before it is forced from cache. Loop fusion and loop unrolling are two techniques that increase temporal locality. Unfortunately, both techniques increase register pressure—as loop bodies become larger, the number of registers required to hold temporary values grows. Once register spilling occurs, any gains evaporate quickly. For multiprocessors with small register sets or small caches, the sweet spot can be very small. In the ten codes presented here, I found no opportunities for loop fusion and only two opportunities for loop unrolling (codes 1 and 3). In code 1, unrolling the outer and inner loop one iteration increases the number of result values computed by the loop body from 1 to 4, do J = 1, GZ-2, 2 do I = 1, GZ-2, 2 T1 = CA1(i+0, j-1) + CA1(i-1, j+0) T2 = CA1(i+1, j-1) + CA1(i+0, j+0) T3 = CA1(i+0, j+0) + CA1(i-1, j+1) T4 = CA1(i+1, j+0) + CA1(i+0, j+1) T5 = CA1(i+2, j+0) + CA1(i+1, j+1) T6 = CA1(i+1, j+1) + CA1(i+0, j+2) T7 = CA1(i+2, j+1) + CA1(i+1, j+2) S1 = T1 + T4 - 4 * CA1(i+0, j+0) S2 = T2 + T5 - 4 * CA1(i+1, j+0) S3 = T3 + T6 - 4 * CA1(i+0, j+1) S4 = T4 + T7 - 4 * CA1(i+1, j+1) CA(i+0, j+0) = CA1(i+0, j+0) + DD * S1 CA(i+1, j+0) = CA1(i+1, j+0) + DD * S2 CA(i+0, j+1) = CA1(i+0, j+1) + DD * S3 CA(i+1, j+1) = CA1(i+1, j+1) + DD * S4 enddo enddo The loop body executes 12 reads, whereas as the rolled loop shown in the previous section executes 20 reads to compute the same four values. In code 3, two loops are unrolled 8 times and one loop is unrolled 4 times. Here is the before for (k = 0; k < NK[u]; k++) { sum = 0.0; for (y = 0; y < NY; y++) { sum += W[y][u][k] * delta[y]; } backprop[i++]=sum; } and after code for (k = 0; k < KK - 8; k+=8) { sum0 = 0.0; sum1 = 0.0; sum2 = 0.0; sum3 = 0.0; sum4 = 0.0; sum5 = 0.0; sum6 = 0.0; sum7 = 0.0; for (y = 0; y < NY; y++) { sum0 += W[y][0][k+0] * delta[y]; sum1 += W[y][0][k+1] * delta[y]; sum2 += W[y][0][k+2] * delta[y]; sum3 += W[y][0][k+3] * delta[y]; sum4 += W[y][0][k+4] * delta[y]; sum5 += W[y][0][k+5] * delta[y]; sum6 += W[y][0][k+6] * delta[y]; sum7 += W[y][0][k+7] * delta[y]; } backprop[k+0] = sum0; backprop[k+1] = sum1; backprop[k+2] = sum2; backprop[k+3] = sum3; backprop[k+4] = sum4; backprop[k+5] = sum5; backprop[k+6] = sum6; backprop[k+7] = sum7; } for one of the loops unrolled 8 times. Optimizing for temporal locality is the most difficult optimization considered in this paper. The concepts are not difficult, but the sweet spot is small. Identifying where the program can benefit from loop unrolling or loop fusion is not trivial. Moreover, it takes some effort to get it right. Still, educating scientific programmers about temporal locality and teaching them how to optimize for it will pay dividends. Reducing instruction count Execution time is a function of instruction count. Reduce the count and you usually reduce the time. The best solution is to use a more efficient algorithm; that is, an algorithm whose order of complexity is smaller, that converges quicker, or is more accurate. Optimizing source code without changing the algorithm yields smaller, but still significant, gains. This paper considers only the latter because the intent is to study how much better codes can run if written by programmers schooled in basic code optimization techniques. The ten codes studied benefited from three types of "instruction reducing" optimizations. The two most prevalent were hoisting invariant memory and data operations out of inner loops. The third was eliminating unnecessary data copying. The nature of these inefficiencies is language dependent. Memory operations The semantics of C make it difficult for the compiler to determine all the invariant memory operations in a loop. The problem is particularly acute for loops in functions since the compiler may not know the values of the function's parameters at every call site when compiling the function. Most compilers support pragmas to help resolve ambiguities; however, these pragmas are not comprehensive and there is no standard syntax. To guarantee that invariant memory operations are not executed repetitively, the user has little choice but to hoist the operations by hand. The problem is not as severe in Fortran programs because in the absence of equivalence statements, it is a violation of the language's semantics for two names to share memory. Codes 3 and 5 are C programs. In both cases, the compiler did not hoist all invariant memory operations from inner loops. Consider the following loop from code 3 for (y = 0; y < NY; y++) { i = 0; for (u = 0; u < NU; u++) { for (k = 0; k < NK[u]; k++) { dW[y][u][k] += delta[y] * I1[i++]; } } } Since dW[y][u] can point to the same memory space as delta for one or more values of y and u, assignment to dW[y][u][k] may change the value of delta[y]. In reality, dW and delta do not overlap in memory, so I rewrote the loop as for (y = 0; y < NY; y++) { i = 0; Dy = delta[y]; for (u = 0; u < NU; u++) { for (k = 0; k < NK[u]; k++) { dW[y][u][k] += Dy * I1[i++]; } } } Failure to hoist invariant memory operations may be due to complex address calculations. If the compiler can not determine that the address calculation is invariant, then it can hoist neither the calculation nor the associated memory operations. As noted above, code 5 uses a macro to address four-dimensional arrays #define MAT4D(a,q,i,j,k) (double *)((a)->data + (q)*(a)->strides[0] + (i)*(a)->strides[3] + (j)*(a)->strides[2] + (k)*(a)->strides[1]) The macro is too complex for the compiler to understand and so, it does not identify any subexpressions as loop invariant. The simplest way to eliminate the address calculation from the innermost loop (over i) is to define a0 = MAT4D(a,q,0,j,k) before the loop and then replace all instances of *MAT4D(a,q,i,j,k) in the loop with a0[i] A similar problem appears in code 6, a Fortran program. The key loop in this program is do n1 = 1, nh nx1 = (n1 - 1) / nz + 1 nz1 = n1 - nz * (nx1 - 1) do n2 = 1, nh nx2 = (n2 - 1) / nz + 1 nz2 = n2 - nz * (nx2 - 1) ndx = nx2 - nx1 ndy = nz2 - nz1 gxx = grn(1,ndx,ndy) gyy = grn(2,ndx,ndy) gxy = grn(3,ndx,ndy) balance(n1,1) = balance(n1,1) + (force(n2,1) * gxx + force(n2,2) * gxy) * h1 balance(n1,2) = balance(n1,2) + (force(n2,1) * gxy + force(n2,2) * gyy)*h1 end do end do The programmer has written this loop well—there are no loop invariant operations with respect to n1 and n2. However, the loop resides within an iterative loop over time and the index calculations are independent with respect to time. Trading space for time, I precomputed the index values prior to the entering the time loop and stored the values in two arrays. I then replaced the index calculations with reads of the arrays. Data operations Ways to reduce data operations can appear in many forms. Implementing a more efficient algorithm produces the biggest gains. The closest I came to an algorithm change was in code 4. This code computes the inner product of K-vectors A(i) and B(j), 0 = i < N, 0 = j < M, for most values of i and j. Since the program computes most of the NM possible inner products, it is more efficient to compute all the inner products in one triply-nested loop rather than one at a time when needed. The savings accrue from reading A(i) once for all B(j) vectors and from loop unrolling. for (i = 0; i < N; i+=8) { for (j = 0; j < M; j++) { sum0 = 0.0; sum1 = 0.0; sum2 = 0.0; sum3 = 0.0; sum4 = 0.0; sum5 = 0.0; sum6 = 0.0; sum7 = 0.0; for (k = 0; k < K; k++) { sum0 += A[i+0][k] * B[j][k]; sum1 += A[i+1][k] * B[j][k]; sum2 += A[i+2][k] * B[j][k]; sum3 += A[i+3][k] * B[j][k]; sum4 += A[i+4][k] * B[j][k]; sum5 += A[i+5][k] * B[j][k]; sum6 += A[i+6][k] * B[j][k]; sum7 += A[i+7][k] * B[j][k]; } C[i+0][j] = sum0; C[i+1][j] = sum1; C[i+2][j] = sum2; C[i+3][j] = sum3; C[i+4][j] = sum4; C[i+5][j] = sum5; C[i+6][j] = sum6; C[i+7][j] = sum7; }} This change requires knowledge of a typical run; i.e., that most inner products are computed. The reasons for the change, however, derive from basic optimization concepts. It is the type of change easily made at development time by a knowledgeable programmer. In code 5, we have the data version of the index optimization in code 6. Here a very expensive computation is a function of the loop indices and so cannot be hoisted out of the loop; however, the computation is invariant with respect to an outer iterative loop over time. We can compute its value for each iteration of the computation loop prior to entering the time loop and save the values in an array. The increase in memory required to store the values is small in comparison to the large savings in time. The main loop in Code 8 is doubly nested. The inner loop includes a series of guarded computations; some are a function of the inner loop index but not the outer loop index while others are a function of the outer loop index but not the inner loop index for (j = 0; j < N; j++) { for (i = 0; i < M; i++) { r = i * hrmax; R = A[j]; temp = (PRM[3] == 0.0) ? 1.0 : pow(r, PRM[3]); high = temp * kcoeff * B[j] * PRM[2] * PRM[4]; low = high * PRM[6] * PRM[6] / (1.0 + pow(PRM[4] * PRM[6], 2.0)); kap = (R > PRM[6]) ? high * R * R / (1.0 + pow(PRM[4]*r, 2.0) : low * pow(R/PRM[6], PRM[5]); < rest of loop omitted > }} Note that the value of temp is invariant to j. Thus, we can hoist the computation for temp out of the loop and save its values in an array. for (i = 0; i < M; i++) { r = i * hrmax; TEMP[i] = pow(r, PRM[3]); } [N.B. – the case for PRM[3] = 0 is omitted and will be reintroduced later.] We now hoist out of the inner loop the computations invariant to i. Since the conditional guarding the value of kap is invariant to i, it behooves us to hoist the computation out of the inner loop, thereby executing the guard once rather than M times. The final version of the code is for (j = 0; j < N; j++) { R = rig[j] / 1000.; tmp1 = kcoeff * par[2] * beta[j] * par[4]; tmp2 = 1.0 + (par[4] * par[4] * par[6] * par[6]); tmp3 = 1.0 + (par[4] * par[4] * R * R); tmp4 = par[6] * par[6] / tmp2; tmp5 = R * R / tmp3; tmp6 = pow(R / par[6], par[5]); if ((par[3] == 0.0) && (R > par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * tmp5; } else if ((par[3] == 0.0) && (R <= par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * tmp4 * tmp6; } else if ((par[3] != 0.0) && (R > par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * TEMP[i] * tmp5; } else if ((par[3] != 0.0) && (R <= par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * TEMP[i] * tmp4 * tmp6; } for (i = 0; i < M; i++) { kap = KAP[i]; r = i * hrmax; < rest of loop omitted > } } Maybe not the prettiest piece of code, but certainly much more efficient than the original loop, Copy operations Several programs unnecessarily copy data from one data structure to another. This problem occurs in both Fortran and C programs, although it manifests itself differently in the two languages. Code 1 declares two arrays—one for old values and one for new values. At the end of each iteration, the array of new values is copied to the array of old values to reset the data structures for the next iteration. This problem occurs in Fortran programs not included in this study and in both Fortran 77 and Fortran 90 code. Introducing pointers to the arrays and swapping pointer values is an obvious way to eliminate the copying; but pointers is not a feature that many Fortran programmers know well or are comfortable using. An easy solution not involving pointers is to extend the dimension of the value array by 1 and use the last dimension to differentiate between arrays at different times. For example, if the data space is N x N, declare the array (N, N, 2). Then store the problem’s initial values in (_, _, 2) and define the scalar names new = 2 and old = 1. At the start of each iteration, swap old and new to reset the arrays. The old–new copy problem did not appear in any C program. In programs that had new and old values, the code swapped pointers to reset data structures. Where unnecessary coping did occur is in structure assignment and parameter passing. Structures in C are handled much like scalars. Assignment causes the data space of the right-hand name to be copied to the data space of the left-hand name. Similarly, when a structure is passed to a function, the data space of the actual parameter is copied to the data space of the formal parameter. If the structure is large and the assignment or function call is in an inner loop, then copying costs can grow quite large. While none of the ten programs considered here manifested this problem, it did occur in programs not included in the study. A simple fix is always to refer to structures via pointers. Optimizing loop structures Since scientific programs spend almost all their time in loops, efficient loops are the key to good performance. Conditionals, function calls, little instruction level parallelism, and large numbers of temporary values make it difficult for the compiler to generate tightly packed, highly efficient code. Conditionals and function calls introduce jumps that disrupt code flow. Users should eliminate or isolate conditionls to their own loops as much as possible. Often logical expressions can be substituted for if-then-else statements. For example, code 2 includes the following snippet MaxDelta = 0.0 do J = 1, N do I = 1, M < code omitted > Delta = abs(OldValue ? NewValue) if (Delta > MaxDelta) MaxDelta = Delta enddo enddo if (MaxDelta .gt. 0.001) goto 200 Since the only use of MaxDelta is to control the jump to 200 and all that matters is whether or not it is greater than 0.001, I made MaxDelta a boolean and rewrote the snippet as MaxDelta = .false. do J = 1, N do I = 1, M < code omitted > Delta = abs(OldValue ? NewValue) MaxDelta = MaxDelta .or. (Delta .gt. 0.001) enddo enddo if (MaxDelta) goto 200 thereby, eliminating the conditional expression from the inner loop. A microprocessor can execute many instructions per instruction cycle. Typically, it can execute one or more memory, floating point, integer, and jump operations. To be executed simultaneously, the operations must be independent. Thick loops tend to have more instruction level parallelism than thin loops. Moreover, they reduce memory traffice by maximizing data reuse. Loop unrolling and loop fusion are two techniques to increase the size of loop bodies. Several of the codes studied benefitted from loop unrolling, but none benefitted from loop fusion. This observation is not too surpising since it is the general tendency of programmers to write thick loops. As loops become thicker, the number of temporary values grows, increasing register pressure. If registers spill, then memory traffic increases and code flow is disrupted. A thick loop with many temporary values may execute slower than an equivalent series of thin loops. The biggest gain will be achieved if the thick loop can be split into a series of independent loops eliminating the need to write and read temporary arrays. I found such an occasion in code 10 where I split the loop do i = 1, n do j = 1, m A24(j,i)= S24(j,i) * T24(j,i) + S25(j,i) * U25(j,i) B24(j,i)= S24(j,i) * T25(j,i) + S25(j,i) * U24(j,i) A25(j,i)= S24(j,i) * C24(j,i) + S25(j,i) * V24(j,i) B25(j,i)= S24(j,i) * U25(j,i) + S25(j,i) * V25(j,i) C24(j,i)= S26(j,i) * T26(j,i) + S27(j,i) * U26(j,i) D24(j,i)= S26(j,i) * T27(j,i) + S27(j,i) * V26(j,i) C25(j,i)= S27(j,i) * S28(j,i) + S26(j,i) * U28(j,i) D25(j,i)= S27(j,i) * T28(j,i) + S26(j,i) * V28(j,i) end do end do into two disjoint loops do i = 1, n do j = 1, m A24(j,i)= S24(j,i) * T24(j,i) + S25(j,i) * U25(j,i) B24(j,i)= S24(j,i) * T25(j,i) + S25(j,i) * U24(j,i) A25(j,i)= S24(j,i) * C24(j,i) + S25(j,i) * V24(j,i) B25(j,i)= S24(j,i) * U25(j,i) + S25(j,i) * V25(j,i) end do end do do i = 1, n do j = 1, m C24(j,i)= S26(j,i) * T26(j,i) + S27(j,i) * U26(j,i) D24(j,i)= S26(j,i) * T27(j,i) + S27(j,i) * V26(j,i) C25(j,i)= S27(j,i) * S28(j,i) + S26(j,i) * U28(j,i) D25(j,i)= S27(j,i) * T28(j,i) + S26(j,i) * V28(j,i) end do end do Conclusions Over the course of the last year, I have had the opportunity to work with over two dozen academic scientific programmers at leading research universities. Their research interests span a broad range of scientific fields. Except for two programs that relied almost exclusively on library routines (matrix multiply and fast Fourier transform), I was able to improve significantly the single processor performance of all codes. Improvements range from 2x to 15.5x with a simple average of 4.75x. Changes to the source code were at a very high level. I did not use sophisticated techniques or programming tools to discover inefficiencies or effect the changes. Only one code was parallel despite the availability of parallel systems to all developers. Clearly, we have a problem—personal scientific research codes are highly inefficient and not running parallel. The developers are unaware of simple optimization techniques to make programs run faster. They lack education in the art of code optimization and parallel programming. I do not believe we can fix the problem by publishing additional books or training manuals. To date, the developers in questions have not studied the books or manual available, and are unlikely to do so in the future. Short courses are a possible solution, but I believe they are too concentrated to be much use. The general concepts can be taught in a three or four day course, but that is not enough time for students to practice what they learn and acquire the experience to apply and extend the concepts to their codes. Practice is the key to becoming proficient at optimization. I recommend that graduate students be required to take a semester length course in optimization and parallel programming. We would never give someone access to state-of-the-art scientific equipment costing hundreds of thousands of dollars without first requiring them to demonstrate that they know how to use the equipment. Yet the criterion for time on state-of-the-art supercomputers is at most an interesting project. Requestors are never asked to demonstrate that they know how to use the system, or can use the system effectively. A semester course would teach them the required skills. Government agencies that fund academic scientific research pay for most of the computer systems supporting scientific research as well as the development of most personal scientific codes. These agencies should require graduate schools to offer a course in optimization and parallel programming as a requirement for funding. About the Author John Feo received his Ph.D. in Computer Science from The University of Texas at Austin in 1986. After graduate school, Dr. Feo worked at Lawrence Livermore National Laboratory where he was the Group Leader of the Computer Research Group and principal investigator of the Sisal Language Project. In 1997, Dr. Feo joined Tera Computer Company where he was project manager for the MTA, and oversaw the programming and evaluation of the MTA at the San Diego Supercomputer Center. In 2000, Dr. Feo joined Sun Microsystems as an HPC application specialist. He works with university research groups to optimize and parallelize scientific codes. Dr. Feo has published over two dozen research articles in the areas of parallel parallel programming, parallel programming languages, and application performance.

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