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  • Why is it always "what language should I learn next" instead of "what project should I tackle next"?

    - by MikeRand
    Hi all, Why do beginning programmers (like me) always ask about the next language they should learn instead of asking about the next project to tackle? Why did Eric Raymond, in the "Learn How To Program" section of his "How To Become A Hacker" essay, talk about the order in which you should learn languages (vs. the order in which you should tackle projects). Do beginning carpenters ask "I know how to use a hammer ... should I learn how to use a saw or a level next?" I ask because I'm finding that almost any meaningful project I'm interested in tackling (e.g. a web app, a set of poker analysis tools) requires that I learn just enough of a multitude of languages (Python, C, HTML, CSS, Javascript, SQL) and frameworks/libraries (wxPython, tkinter, Django) to implement them. Thanks, Mike

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  • Google I/O 2012 - YouTube API + Cloud Rendering = Happy Mobile Gamers

    Google I/O 2012 - YouTube API + Cloud Rendering = Happy Mobile Gamers Jarek Wilkiewicz, Danny Hermes YouTube is one of the top destinations for gamers. Many console developers already incorporate video recording and uploading directly into their titles, but uploading to YouTube from a mobile game presents a unique set of challenges. Come and learn how the YouTube API combined with cloud computing can help enable video uploads in your mobile game. For all I/O 2012 sessions, go to developers.google.com From: GoogleDevelopers Views: 100 0 ratings Time: 57:05 More in Science & Technology

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  • SQLAuthority News Interesting Whitepaper We Loaded 1TB in 30 Minutes with SSIS, and So Can You

    In February 2008, Microsoft announced a record-breaking data load using Microsoft SQL Server Integration Services (SSIS): 1 TB of data in less than 30 minutes. That data load, using SQL Server Integration Services, was 30% faster than the previous best time using a commercial ETL tool. This paper outlines what it took: the software, hardware, [...]...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • Azure Futures - Distributed Computing and Number Crunching

    - by JoshReuben
    "the biggest Azure customers today are the ones using HPC on-premises at the current time" - http://www.zdnet.com/blog/microsoft/windows-azure-futures-turning-the-cloud-into-a-supercomputer/8592?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+zdnet%2Fmicrosoft+%28ZDNet+All+About+Microsoft%29&utm_content=Google+Reader   Orleans Framework for cloud computing - http://research.microsoft.com/en-us/projects/orleans     HPC on Azure - http://www.zdnet.com/blog/microsoft/microsoft-finalizes-its-latest-supercomputing-operating-system-release/7414   Dryad is Microsoft’s competitor to Google MapReduce and Apache Hadoop  - http://www.zdnet.com/blog/microsoft/microsoft-takes-a-step-toward-commercializing-its-dryad-distributed-computing-technologies/8255?tag=mantle_skin;content   SQL Server Analysis Services DataMining in the cloud - http://www.sqlmag.com/article/reporting2/azure-data-mining-in-the-cloud.aspx

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  • Is it okay for programmers to be given the task of outlining database requirements?

    - by L'Ingenu
    In my current job, dba's and programmers are divided in tasks. Any code that needs to be written in procedures dba's write, and programmers do only application code. The strange thing is that whenever a task needs to be defined/specced, programmers get the task, and we have to define all the procedures needed and what they should return. Is this a common practice in software development? Are programmers generally the ones tasked with building requirements for the database side?

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  • GDD-BR 2010 [1H] VC Panel: Entrepreneurship, Incubation and Venture Capital

    GDD-BR 2010 [1H] VC Panel: Entrepreneurship, Incubation and Venture Capital Speakers: Don Dodge, Eric Acher, Humberto Matsuda, Alex Tabor Track: Panels Time slot: H [17:20 - 18:05] Room: 1 Startups can be built and funded anywhere in the world, not just Silicon Valley. Venture Capital investors are investing in startups globally, and funding incubators to hatch their future investments. Find out how you can get into an incubator, or funded by a Venture Capitalist or Angel Investors. Learn from examples in the USA and hear from local VC investors in this panel discussion. Get your questions answered by real investors. From: GoogleDevelopers Views: 6 0 ratings Time: 37:39 More in Science & Technology

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  • Automated Website Testing/Sanity/Quality

    - by Jeff
    I am thinking about building a tool that starts from the root of a webpage and traverses the entire website gathering a list of resources such as CSS/HTML/Javascript files and then runs CSS/Javascript Lint + HTML Validator + Broken Link Finder. Before I start building something like this, I was wondering if this exists already? Thanks. I already searched Google quite a bit and couldn't find much.

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  • Load Balance and Parallel Performance

    Load balancing an application workload among threads is critical to performance. However, achieving perfect load balance is non-trivial, and it depends on the parallelism within the application, workload, the number of threads, load balancing policy, and the threading implementation.

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  • Detecting Installed .NET Framework Versions

    - by João Angelo
    A new year is upon us and it’s also time for me to end my blogging vacations and get back to the blogosphere. However, let’s start simple… and short. More specifically with a quick way to detect the installed .NET Framework versions on a machine. You just need to fire up Internet Explorer, write the following in the address bar and press enter: javascript:alert(navigator.userAgent) If for any reason you need to copy/paste the resulting information then use the next command instead: javascript:document.write(navigator.userAgent)

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  • Syncing client and server CRUD operations using json and php

    - by Justin
    I'm working on some code to sync the state of models between client (being a javascript application) and server. Often I end up writing redundant code to track the client and server objects so I can map the client supplied data to the server models. Below is some code I am thinking about implementing to help. What I don't like about the below code is that this method won't handle nested relationships very well, I would have to create multiple object trackers. One work around is for each server model after creating or loading, simply do $model->clientId = $clientId; IMO this is a nasty hack and I want to avoid it. Adding a setCientId method to all my model object would be another way to make it less hacky, but this seems like overkill to me. Really clientIds are only good for inserting/updating data in some scenarios. I could go with a decorator pattern but auto generating a proxy class seems a bit involved. I could use a generic proxy class that uses a __call function to allow for original object data to be accessed, but this seems wrong too. Any thoughts or comments? $clientData = '[{name: "Bob", action: "update", id: 1, clientId: 200}, {name:"Susan", action:"create", clientId: 131} ]'; $jsonObjs = json_decode($clientData); $objectTracker = new ObjectTracker(); $objectTracker->trackClientObjs($jsonObjs); $query = $this->em->createQuery("SELECT x FROM Application_Model_User x WHERE x.id IN (:ids)"); $query->setParameters("ids",$objectTracker->getClientSpecifiedServerIds()); $models = $query->getResults(); //Apply client data to server model foreach ($models as $model) { $clientModel = $objectTracker->getClientJsonObj($model->getId()); ... } //Create new models and persist foreach($objectTracker->getNewClientObjs() as $newClientObj) { $model = new Application_Model_User(); .... $em->persist($model); $objectTracker->trackServerObj($model); } $em->flush(); $resourceResponse = $objectTracker->createResourceResponse(); //Id mappings will be an associtave array representing server id resources with client side // id. //This method Dosen't seem to flexible if we want to return additional data with each resource... //Would have to modify the returned data structure, seems like tight coupling... //Ex return value: //[{clientId: 200, id:1} , {clientId: 131, id: 33}];

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  • Google Maps API Round-up

    Google Maps API Round-up This week, Mano Marks and Paul Saxman go over recent launches and things you might have missed with the Google Maps APIs, including the new Google Time Zone API, traffic estimates with the Directions API (for enterprise customers), and the Places Autocomplete API query results and data service enhancements. From: GoogleDevelopers Views: 0 0 ratings Time: 00:00 More in Education

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  • How to troubleshoot ethernet port on laptop

    - by Psallas Vassilios
    I have a problem with my wired connection. To be more specific, my laptop doesn't seems to recognize that I have plugged in an ethernet cable. I tried to download new drivers for my ethernet card, but I couldn't find any solutions. Maybe because I am new to Linux, so I'm not familiar with running commands in the terminal. OK I have typed the command and here are the results: 00:04.0 Ethernet controller [0200]: Silicon Integrated Systems [SiS] 191 Gigabit Ethernet Adapter [1039:0191] (rev 02) For the second reply I don't know if the following is what you asked me: ?Memory: 3.9 GiB ?Processor: Intel Core 2 Duo CPU P8800 @ 2.66GHz × 2 ?OS type: 32-bit My Ethernet connection had some problem on Windows too. I have changed recently my internet provider, and since then my ethernet cable is not recognized by the laptop. At that time I was still on Windows. I thought that with Ubuntu the problem would be solved, but unfortunately the problem still persists. If someone can help me to solve my problem I'll be thankful. Here are the results of the three first commands you told me to run: lsmod | grep sis190 sis190 22570 0 sudo modprobe sis190 ifconfig eth0 Link encap:Ethernet HWaddr 00:90:f5:90:81:7e UP BROADCAST MULTICAST MTU:1500 Metric:1 RX packets:0 errors:0 dropped:0 overruns:0 frame:0 TX packets:0 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:1000 RX bytes:0 (0.0 B) TX bytes:0 (0.0 B) lo Link encap:Local Loopback inet addr:127.0.0.1 Mask:255.0.0.0 inet6 addr: ::1/128 Scope:Host UP LOOPBACK RUNNING MTU:16436 Metric:1 RX packets:185 errors:0 dropped:0 overruns:0 frame:0 TX packets:185 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:0 RX bytes:22672 (22.6 KB) TX bytes:22672 (22.6 KB) wlan0 Link encap:Ethernet HWaddr 00:25:d3:2c:3a:ae inet addr:192.168.1.72 Bcast:192.168.1.255 Mask:255.255.255.0 inet6 addr: fe80::225:d3ff:fe2c:3aae/64 Scope:Link UP BROADCAST RUNNING MULTICAST MTU:1500 Metric:1 RX packets:260 errors:0 dropped:0 overruns:0 frame:0 TX packets:363 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:1000 RX bytes:71992 (71.9 KB) TX bytes:52000 (52.0 KB) and the results of running the last two commands: dmesg | grep -e eth -e sis190 [ 0.816667] sis190: sis190 Gigabit Ethernet driver 1.4 loaded [ 0.816728] sis190 0000:00:04.0: setting latency timer to 64 [ 0.816751] sis190: 0000:00:04.0: Read MAC address from EEPROM [ 0.904032] sis190: 0000:00:04.0: Realtek PHY RTL8201 transceiver at address [ 1.416030] sis190: 0000:00:04.0: Using transceiver at address 1 as default [ 1.448235] sis190 0000:00:04.0: eth0: 0000:00:04.0: SiS 191 PCI Gigabit Ethernet adapter at f8410000 (IRQ: 19), 00:90:f5:90:81:7e [ 1.448238] sis190 0000:00:04.0: eth0: GMII mode. [ 1.448243] sis190 0000:00:04.0: eth0: Enabling Auto-negotiation [ 11.560907] IPv6: ADDRCONF(NETDEV_UP): eth0: link is not ready [ 16.372019] IPv6: ADDRCONF(NETDEV_UP): eth0: link is not ready [ 16.372265] IPv6: ADDRCONF(NETDEV_UP): eth0: link is not ready [ 26.424038] sis190 0000:00:04.0: eth0: auto-negotiating... nm-tool NetworkManager Tool State: connected (global) - Device: eth0 ----------------------------------------------------------------- Type: Wired Driver: sis190 State: unavailable Default: no HW Address: 00:90:F5:90:81:7E Capabilities: Carrier Detect: yes Wired Properties Carrier: off

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  • Running C++ AMP kernels on the CPU

    - by Daniel Moth
    One of the FAQs we receive is whether C++ AMP can be used to target the CPU. For targeting multi-core we have a technology we released with VS2010 called PPL, which has had enhancements for VS 11 – that is what you should be using! FYI, it also has a Linux implementation via Intel's TBB which conforms to the same interface. When you choose to use C++ AMP, you choose to take advantage of massively parallel hardware, through accelerators like the GPU. Having said that, you can always use the accelerator class to check if you are running on a system where the is no hardware with a DirectX 11 driver, and decide what alternative code path you wish to follow.  In fact, if you do nothing in code, if the runtime does not find DX11 hardware to run your code on, it will choose the WARP accelerator which will run your code on the CPU, taking advantage of multi-core and SSE2 (depending on the CPU capabilities WARP also uses SSE3 and SSE 4.1 – it does not currently use AVX and on such systems you hopefully have a DX 11 GPU anyway). A few things to know about WARP It is our fallback CPU solution, not intended as a primary target of C++ AMP. WARP stands for Windows Advanced Rasterization Platform and you can read old info on this MSDN page on WARP. What is new in Windows 8 Developer Preview is that WARP now supports DirectCompute, which is what C++ AMP builds on. It is not currently clear if we will have a CPU fallback solution for non-Windows 8 platforms when we ship. When you create a WARP accelerator, its is_emulated property returns true. WARP does not currently support double precision.   BTW, when we refer to WARP, we refer to this accelerator described above. If we use lower case "warp", that refers to a bunch of threads that run concurrently in lock step and share the same instruction. In the VS 11 Developer Preview, the size of warp in our Ref emulator is 4 – Ref is another emulator that runs on the CPU, but it is extremely slow not intended for production, just for debugging. Comments about this post by Daniel Moth welcome at the original blog.

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  • parallel_for_each from amp.h – part 1

    - by Daniel Moth
    This posts assumes that you've read my other C++ AMP posts on index<N> and extent<N>, as well as about the restrict modifier. It also assumes you are familiar with C++ lambdas (if not, follow my links to C++ documentation). Basic structure and parameters Now we are ready for part 1 of the description of the new overload for the concurrency::parallel_for_each function. The basic new parallel_for_each method signature returns void and accepts two parameters: a grid<N> (think of it as an alias to extent) a restrict(direct3d) lambda, whose signature is such that it returns void and accepts an index of the same rank as the grid So it looks something like this (with generous returns for more palatable formatting) assuming we are dealing with a 2-dimensional space: // some_code_A parallel_for_each( g, // g is of type grid<2> [ ](index<2> idx) restrict(direct3d) { // kernel code } ); // some_code_B The parallel_for_each will execute the body of the lambda (which must have the restrict modifier), on the GPU. We also call the lambda body the "kernel". The kernel will be executed multiple times, once per scheduled GPU thread. The only difference in each execution is the value of the index object (aka as the GPU thread ID in this context) that gets passed to your kernel code. The number of GPU threads (and the values of each index) is determined by the grid object you pass, as described next. You know that grid is simply a wrapper on extent. In this context, one way to think about it is that the extent generates a number of index objects. So for the example above, if your grid was setup by some_code_A as follows: extent<2> e(2,3); grid<2> g(e); ...then given that: e.size()==6, e[0]==2, and e[1]=3 ...the six index<2> objects it generates (and hence the values that your lambda would receive) are:    (0,0) (1,0) (0,1) (1,1) (0,2) (1,2) So what the above means is that the lambda body with the algorithm that you wrote will get executed 6 times and the index<2> object you receive each time will have one of the values just listed above (of course, each one will only appear once, the order is indeterminate, and they are likely to call your code at the same exact time). Obviously, in real GPU programming, you'd typically be scheduling thousands if not millions of threads, not just 6. If you've been following along you should be thinking: "that is all fine and makes sense, but what can I do in the kernel since I passed nothing else meaningful to it, and it is not returning any values out to me?" Passing data in and out It is a good question, and in data parallel algorithms indeed you typically want to pass some data in, perform some operation, and then typically return some results out. The way you pass data into the kernel, is by capturing variables in the lambda (again, if you are not familiar with them, follow the links about C++ lambdas), and the way you use data after the kernel is done executing is simply by using those same variables. In the example above, the lambda was written in a fairly useless way with an empty capture list: [ ](index<2> idx) restrict(direct3d), where the empty square brackets means that no variables were captured. If instead I write it like this [&](index<2> idx) restrict(direct3d), then all variables in the some_code_A region are made available to the lambda by reference, but as soon as I try to use any of those variables in the lambda, I will receive a compiler error. This has to do with one of the direct3d restrictions, where only one type can be capture by reference: objects of the new concurrency::array class that I'll introduce in the next post (suffice for now to think of it as a container of data). If I write the lambda line like this [=](index<2> idx) restrict(direct3d), all variables in the some_code_A region are made available to the lambda by value. This works for some types (e.g. an integer), but not for all, as per the restrictions for direct3d. In particular, no useful data classes work except for one new type we introduce with C++ AMP: objects of the new concurrency::array_view class, that I'll introduce in the post after next. Also note that if you capture some variable by value, you could use it as input to your algorithm, but you wouldn’t be able to observe changes to it after the parallel_for_each call (e.g. in some_code_B region since it was passed by value) – the exception to this rule is the array_view since (as we'll see in a future post) it is a wrapper for data, not a container. Finally, for completeness, you can write your lambda, e.g. like this [av, &ar](index<2> idx) restrict(direct3d) where av is a variable of type array_view and ar is a variable of type array - the point being you can be very specific about what variables you capture and how. So it looks like from a large data perspective you can only capture array and array_view objects in the lambda (that is how you pass data to your kernel) and then use the many threads that call your code (each with a unique index) to perform some operation. You can also capture some limited types by value, as input only. When the last thread completes execution of your lambda, the data in the array_view or array are ready to be used in the some_code_B region. We'll talk more about all this in future posts… (a)synchronous Please note that the parallel_for_each executes as if synchronous to the calling code, but in reality, it is asynchronous. I.e. once the parallel_for_each call is made and the kernel has been passed to the runtime, the some_code_B region continues to execute immediately by the CPU thread, while in parallel the kernel is executed by the GPU threads. However, if you try to access the (array or array_view) data that you captured in the lambda in the some_code_B region, your code will block until the results become available. Hence the correct statement: the parallel_for_each is as-if synchronous in terms of visible side-effects, but asynchronous in reality.   That's all for now, we'll revisit the parallel_for_each description, once we introduce properly array and array_view – coming next. Comments about this post by Daniel Moth welcome at the original blog.

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  • best add-ons for Firefox 4

    - by anirudha
    Firefox is a great tool for web development and have many great feature like addons , plugin or many other customization to make development easier and best. here is the list of plugin for Firefox 4 [upcoming] Firebug : 1.7x [in development] Web Developer [stable] Firequery [stable but not reviewed] Firecookie [stable] Colorzilla[direct from developer site] Adblock[stable] measureit[direct from developer site]

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