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  • Cloud computing?

    - by Suraj
    I'm writing a report advising on future technologies that a manufacturing company could use. I've highlighted a number of advanced manufacturing technologies such as CAD etc. However, I want to bring cloud computing into the report just to score some extra points. I am not sure how one would bring together cloud computing with the advanced technologies though. Basically what would be the process of integrating these technologies into a cloud computing "environment"? Say the organisation buys a CAD package, how could they make use of cloud computing here?

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  • Open source Distributed computing tool

    - by Prasenjit Chatterjee
    I want to set up distributed computing on my Local Area Network consisting a bunch of PCs. Say for the time being each one has the same OS - Windows 7. Is there any opensource tool available so that I can share the resources of these PCs over the LAN and increase the speed of my applications and the memory space. I know that if its a graphics intensive application then, it is not very practical, because the speed of LAN is much slower than Graphics processors. But I only want to share general applications, some basic softwares, Programming language IDEs etc. Can anyone shed some light on it? Thanks in Advance..

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  • Cloud Computing - Multiple Physical Computers, One Logical Computer

    - by Koobz
    I know that you can set up multiple virtual machines per physical computer. I'm wondering if it's possible to make multiple physical computers behave as one logical unit? Fundamentally the way I imagine it working is that you can throw 10 computers into a facility one day. You've got one client that requires the equivalent of two computers worth, and 100 others that eat up the remaining 8. As demands change you're just reallocating logical resources, maybe the 2 computer client now requires a third physical system. You just add it to the cloud, and don't worry about sharding the database, or migrating data over to a new server. Can it work this way? If yes, why would anyone ever do things like partition their database servers anymore? Just add more computing resources. You scale horizontally with the hardware, but your server appears to scale vertically. There's no need to modify your application's infrastructure to support multiple databases etc.

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  • Cloud Computing - Multiple Physical Computers, One Logical Computer

    - by bundini
    I know that you can set up multiple virtual machines per physical computer. I'm wondering if it's possible to make multiple physical computers behave as one logical unit? Fundamentally the way I imagine it working is that you can throw 10 computers into a facility one day. You've got one client that requires the equivalent of two computers worth, and 100 others that eat up the remaining 8. As demands change you're just reallocating logical resources, maybe the 2 computer client now requires a third physical system. You just add it to the cloud, and don't worry about sharding the database, or migrating data over to a new server. Can it work this way? If yes, why would anyone ever do things like hand partition their database servers anymore? Just add more computing resources. You scale horizontally with the hardware, but your server appears to scale vertically. There's no need to modify your application's supporting infrastructure to support multiple databases etc.

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  • cloud computing ? Eucalyptus

    - by neolix
    Hi Greeting!! I want to setup small cloud computing using our old 2 core server system? we are new to cloud system we have google for the same. We are looking host VM's on top any one has done pls share me doc or how to ? we have 50 plus server which we are not using. 2 core each 4GB RAM, 1TB HDD centos is my base os we looking host windows. Right now we can use this server only paravirtualization ignore my english Thanks

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  • Configuration management in support of scientific computing

    - by Sharpie
    For the past few years I have been involved with developing and maintaining a system for forecasting near-shore waves. Our team has just received a significant grant for further development and as a result we are taking the opportunity to refactor many components of the old system. We will also be receiving a new server to run the model and so I am taking this opportunity to consider how we set up the system. Basically, the steps that need to happen are: Some standard packages and libraries such as compilers and databases need to be downloaded and installed. Some custom scientific models need to be downloaded and compiled from source as they are not commonly provided as packages. New users need to be created to manage the databases and run the models. A suite of scripts that manage model-database interaction needs to be checked out from source code control and installed. Crontabs need to be set up to run the scripts at regular intervals in order to generate forecasts. I have been pondering applying tools such as Puppet, Capistrano or Fabric to automate the above steps. It seems perfectly possible to implement most of the above functionality except there are a couple usage cases that I am wondering about: During my preliminary research, I have found few examples and little discussion on how to use these systems to abstract and automate the process of building custom components from source. We may have to deploy on machines that are isolated from the Internet- i.e. all configuration and set up files will have to come in on a USB key that can be inserted into a terminal that can connect to the server that will run the models. I see this as an opportunity to learn a new tool that will help me automate my workflow, but I am unsure which tool I should start with. If any member of the community could suggest a tool that would support the above workflow and the issues specific to scientific computing, I would be very grateful. Our production server will be running Linux, but support for OS X would be a bonus as it would allow the development team to setup test installations outside of VirtualBox.

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  • Configuration management in support of scientific computing

    - by Sharpie
    For the past few years I have been involved with developing and maintaining a system for forecasting near-shore waves. Our team has just received a significant grant for further development and as a result we are taking the opportunity to refactor many components of the old system. We will also be receiving a new server to run the model and so I am taking this opportunity to consider how we set up the system. Basically, the steps that need to happen are: Some standard packages and libraries such as compilers and databases need to be downloaded and installed. Some custom scientific models need to be downloaded and compiled from source as they are not commonly provided as packages. New users need to be created to manage the databases and run the models. A suite of scripts that manage model-database interaction needs to be checked out from source code control and installed. Crontabs need to be set up to run the scripts at regular intervals in order to generate forecasts. I have been pondering applying tools such as Puppet, Capistrano or Fabric to automate the above steps. It seems perfectly possible to implement most of the above functionality except there are a couple usage cases that I am wondering about: During my preliminary research, I have found few examples and little discussion on how to use these systems to abstract and automate the process of building custom components from source. We may have to deploy on machines that are isolated from the Internet- i.e. all configuration and set up files will have to come in on a USB key that can be inserted into a terminal that can connect to the server that will run the models. I see this as an opportunity to learn a new tool that will help me automate my workflow, but I am unsure which tool I should start with. If any member of the community could suggest a tool that would support the above workflow and the issues specific to scientific computing, I would be very grateful. Our production server will be running Linux, but support for OS X would be a bonus as it would allow the development team to setup test installations outside of VirtualBox.

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  • Distributed storage and computing

    - by Tim van Elteren
    Dear Serverfault community, After researching a number of distributed file systems for deployment in a production environment with the main purpose of performing both batch and real-time distributed computing I've identified the following list as potential candidates, mainly on maturity, license and support: Ceph Lustre GlusterFS HDFS FhGFS MooseFS XtreemFS The key properties that our system should exhibit: an open source, liberally licensed, yet production ready, e.g. a mature, reliable, community and commercially supported solution; ability to run on commodity hardware, preferably be designed for it; provide high availability of the data with the most focus on reads; high scalability, so operation over multiple data centres, possibly on a global scale; removal of single points of failure with the use of replication and distribution of (meta-)data, e.g. provide fault-tolerance. The sensitivity points that were identified, and resulted in the following questions, are: transparency to the processing layer / application with respect to data locality, e.g. know where data is physically located on a server level, mainly for resource allocation and fast processing, high performance, how can this be accomplished? Do you from experience know what solutions provide this transparency and to what extent? posix compliance, or conformance, is mentioned on the wiki pages of most of the above listed solutions. The question here mainly is, how relevant is support for the posix standard? Hadoop for example isn't posix compliant by design, what are the pro's and con's? what about the difference between synchronous and asynchronous opeartion of a distributed file system. Though a synchronous distributed file system has the preference because of reliability it also imposes certain limitations with respect to scalability. What would be, from your expertise, the way to go on this? I'm looking forward to your replies. Thanks in advance! :) With kind regards, Tim van Elteren

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  • Big Data – Role of Cloud Computing in Big Data – Day 11 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the NewSQL. In this article we will understand the role of Cloud in Big Data Story What is Cloud? Cloud is the biggest buzzword around from last few years. Everyone knows about the Cloud and it is extremely well defined online. In this article we will discuss cloud in the context of the Big Data. Cloud computing is a method of providing a shared computing resources to the application which requires dynamic resources. These resources include applications, computing, storage, networking, development and various deployment platforms. The fundamentals of the cloud computing are that it shares pretty much share all the resources and deliver to end users as a service.  Examples of the Cloud Computing and Big Data are Google and Amazon.com. Both have fantastic Big Data offering with the help of the cloud. We will discuss this later in this blog post. There are two different Cloud Deployment Models: 1) The Public Cloud and 2) The Private Cloud Public Cloud Public Cloud is the cloud infrastructure build by commercial providers (Amazon, Rackspace etc.) creates a highly scalable data center that hides the complex infrastructure from the consumer and provides various services. Private Cloud Private Cloud is the cloud infrastructure build by a single organization where they are managing highly scalable data center internally. Here is the quick comparison between Public Cloud and Private Cloud from Wikipedia:   Public Cloud Private Cloud Initial cost Typically zero Typically high Running cost Unpredictable Unpredictable Customization Impossible Possible Privacy No (Host has access to the data Yes Single sign-on Impossible Possible Scaling up Easy while within defined limits Laborious but no limits Hybrid Cloud Hybrid Cloud is the cloud infrastructure build with the composition of two or more clouds like public and private cloud. Hybrid cloud gives best of the both the world as it combines multiple cloud deployment models together. Cloud and Big Data – Common Characteristics There are many characteristics of the Cloud Architecture and Cloud Computing which are also essentially important for Big Data as well. They highly overlap and at many places it just makes sense to use the power of both the architecture and build a highly scalable framework. Here is the list of all the characteristics of cloud computing important in Big Data Scalability Elasticity Ad-hoc Resource Pooling Low Cost to Setup Infastructure Pay on Use or Pay as you Go Highly Available Leading Big Data Cloud Providers There are many players in Big Data Cloud but we will list a few of the known players in this list. Amazon Amazon is arguably the most popular Infrastructure as a Service (IaaS) provider. The history of how Amazon started in this business is very interesting. They started out with a massive infrastructure to support their own business. Gradually they figured out that their own resources are underutilized most of the time. They decided to get the maximum out of the resources they have and hence  they launched their Amazon Elastic Compute Cloud (Amazon EC2) service in 2006. Their products have evolved a lot recently and now it is one of their primary business besides their retail selling. Amazon also offers Big Data services understand Amazon Web Services. Here is the list of the included services: Amazon Elastic MapReduce – It processes very high volumes of data Amazon DynammoDB – It is fully managed NoSQL (Not Only SQL) database service Amazon Simple Storage Services (S3) – A web-scale service designed to store and accommodate any amount of data Amazon High Performance Computing – It provides low-tenancy tuned high performance computing cluster Amazon RedShift – It is petabyte scale data warehousing service Google Though Google is known for Search Engine, we all know that it is much more than that. Google Compute Engine – It offers secure, flexible computing from energy efficient data centers Google Big Query – It allows SQL-like queries to run against large datasets Google Prediction API – It is a cloud based machine learning tool Other Players Besides Amazon and Google we also have other players in the Big Data market as well. Microsoft is also attempting Big Data with the Cloud with Microsoft Azure. Additionally Rackspace and NASA together have initiated OpenStack. The goal of Openstack is to provide a massively scaled, multitenant cloud that can run on any hardware. Thing to Watch The cloud based solutions provides a great integration with the Big Data’s story as well it is very economical to implement as well. However, there are few things one should be very careful when deploying Big Data on cloud solutions. Here is a list of a few things to watch: Data Integrity Initial Cost Recurring Cost Performance Data Access Security Location Compliance Every company have different approaches to Big Data and have different rules and regulations. Based on various factors, one can implement their own custom Big Data solution on a cloud. Tomorrow In tomorrow’s blog post we will discuss about various Operational Databases supporting Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Cloud Computing Forces Better Design Practices

    - by Herve Roggero
    Is cloud computing simply different than on premise development, or is cloud computing actually forcing you to create better applications than you normally would? In other words, is cloud computing merely imposing different design principles, or forcing better design principles?  A little while back I got into a discussion with a developer in which I was arguing that cloud computing, and specifically Windows Azure in his case, was forcing developers to adopt better design principles. His opinion was that cloud computing was not yielding better systems; just different systems. In this blog, I will argue that cloud computing does force developers to use better design practices, and hence better applications. So the first thing to define, of course, is the word “better”, in the context of application development. Looking at a few definitions online, better means “superior quality”. As it relates to this discussion then, I stipulate that cloud computing can yield higher quality applications in terms of scalability, everything else being equal. Before going further I need to also outline the difference between performance and scalability. Performance and scalability are two related concepts, but they don’t mean the same thing. Scalability is the measure of system performance given various loads. So when developers design for performance, they usually give higher priority to a given load and tend to optimize for the given load. When developers design for scalability, the actual performance at a given load is not as important; the ability to ensure reasonable performance regardless of the load becomes the objective. This can lead to very different design choices. For example, if your objective is to obtains the fastest response time possible for a service you are building, you may choose the implement a TCP connection that never closes until the client chooses to close the connection (in other words, a tightly coupled service from a connectivity standpoint), and on which a connection session is established for faster processing on the next request (like SQL Server or other database systems for example). If you objective is to scale, you may implement a service that answers to requests without keeping session state, so that server resources are released as quickly as possible, like a REST service for example. This alternate design would likely have a slower response time than the TCP service for any given load, but would continue to function at very large loads because of its inherently loosely coupled design. An example of a REST service is the NO-SQL implementation in the Microsoft cloud called Azure Tables. Now, back to cloud computing… Cloud computing is designed to help you scale your applications, specifically when you use Platform as a Service (PaaS) offerings. However it’s not automatic. You can design a tightly-coupled TCP service as discussed above, and as you can imagine, it probably won’t scale even if you place the service in the cloud because it isn’t using a connection pattern that will allow it to scale [note: I am not implying that all TCP systems do not scale; I am just illustrating the scalability concepts with an imaginary TCP service that isn’t designed to scale for the purpose of this discussion]. The other service, using REST, will have a better chance to scale because, by design, it minimizes resource consumption for individual requests and doesn’t tie a client connection to a specific endpoint (which means you can easily deploy this service to hundreds of machines without much trouble, as long as your pockets are deep enough). The TCP and REST services discussed above are both valid designs; the TCP service is faster and the REST service scales better. So is it fair to say that one service is fundamentally better than the other? No; not unless you need to scale. And if you don’t need to scale, then you don’t need the cloud in the first place. However, it is interesting to note that if you do need to scale, then a loosely coupled system becomes a better design because it can almost always scale better than a tightly-coupled system. And because most applications grow overtime, with an increasing user base, new functional requirements, increased data and so forth, most applications eventually do need to scale. So in my humble opinion, I conclude that a loosely coupled system is not just different than a tightly coupled system; it is a better design, because it will stand the test of time. And in my book, if a system stands the test of time better than another, it is of superior quality. Because cloud computing demands loosely coupled systems so that its underlying service architecture can be leveraged, developers ultimately have no choice but to design loosely coupled systems for the cloud. And because loosely coupled systems are better… … the cloud forces better design practices. My 2 cents.

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  • Cloud Computing = Elasticity * Availability

    - by Herve Roggero
    What is cloud computing? Is hosting the same thing as cloud computing? Are you running a cloud if you already use virtual machines? What is the difference between Infrastructure as a Service (IaaS) and a cloud provider? And the list goes on… these questions keep coming up and all try to fundamentally explain what “cloud” means relative to other concepts. At the risk of over simplification, answering these questions becomes simpler once you understand the primary foundations of cloud computing: Elasticity and Availability.   Elasticity The basic value proposition of cloud computing is to pay as you go, and to pay for what you use. This implies that an application can expand and contract on demand, across all its tiers (presentation layer, services, database, security…).  This also implies that application components can grow independently from each other. So if you need more storage for your database, you should be able to grow that tier without affecting, reconfiguring or changing the other tiers. Basically, cloud applications behave like a sponge; when you add water to a sponge, it grows in size; in the application world, the more customers you add, the more it grows. Pure IaaS providers will provide certain benefits, specifically in terms of operating costs, but an IaaS provider will not help you in making your applications elastic; neither will Virtual Machines. The smallest elasticity unit of an IaaS provider and a Virtual Machine environment is a server (physical or virtual). While adding servers in a datacenter helps in achieving scale, it is hardly enough. The application has yet to use this hardware.  If the process of adding computing resources is not transparent to the application, the application is not elastic.   As you can see from the above description, designing for the cloud is not about more servers; it is about designing an application for elasticity regardless of the underlying server farm.   Availability The fact of the matter is that making applications highly available is hard. It requires highly specialized tools and trained staff. On top of it, it's expensive. Many companies are required to run multiple data centers due to high availability requirements. In some organizations, some data centers are simply on standby, waiting to be used in a case of a failover. Other organizations are able to achieve a certain level of success with active/active data centers, in which all available data centers serve incoming user requests. While achieving high availability for services is relatively simple, establishing a highly available database farm is far more complex. In fact it is so complex that many companies establish yearly tests to validate failover procedures.   To a certain degree certain IaaS provides can assist with complex disaster recovery planning and setting up data centers that can achieve successful failover. However the burden is still on the corporation to manage and maintain such an environment, including regular hardware and software upgrades. Cloud computing on the other hand removes most of the disaster recovery requirements by hiding many of the underlying complexities.   Cloud Providers A cloud provider is an infrastructure provider offering additional tools to achieve application elasticity and availability that are not usually available on-premise. For example Microsoft Azure provides a simple configuration screen that makes it possible to run 1 or 100 web sites by clicking a button or two on a screen (simplifying provisioning), and soon SQL Azure will offer Data Federation to allow database sharding (which allows you to scale the database tier seamlessly and automatically). Other cloud providers offer certain features that are not available on-premise as well, such as the Amazon SC3 (Simple Storage Service) which gives you virtually unlimited storage capabilities for simple data stores, which is somewhat equivalent to the Microsoft Azure Table offering (offering a server-independent data storage model). Unlike IaaS providers, cloud providers give you the necessary tools to adopt elasticity as part of your application architecture.    Some cloud providers offer built-in high availability that get you out of the business of configuring clustered solutions, or running multiple data centers. Some cloud providers will give you more control (which puts some of that burden back on the customers' shoulder) and others will tend to make high availability totally transparent. For example, SQL Azure provides high availability automatically which would be very difficult to achieve (and very costly) on premise.   Keep in mind that each cloud provider has its strengths and weaknesses; some are better at achieving transparent scalability and server independence than others.    Not for Everyone Note however that it is up to you to leverage the elasticity capabilities of a cloud provider, as discussed previously; if you build a website that does not need to scale, for which elasticity is not important, then you can use a traditional host provider unless you also need high availability. Leveraging the technologies of cloud providers can be difficult and can become a journey for companies that build their solutions in a scale up fashion. Cloud computing promises to address cost containment and scalability of applications with built-in high availability. If your application does not need to scale or you do not need high availability, then cloud computing may not be for you. In fact, you may pay a premium to run your applications with cloud providers due to the underlying technologies built specifically for scalability and availability requirements. And as such, the cloud is not for everyone.   Consistent Customer Experience, Predictable Cost With all its complexities, buzz and foggy definition, cloud computing boils down to a simple objective: consistent customer experience at a predictable cost.  The objective of a cloud solution is to provide the same user experience to your last customer than the first, while keeping your operating costs directly proportional to the number of customers you have. Making your applications elastic and highly available across all its tiers, with as much automation as possible, achieves the first objective of a consistent customer experience. And the ability to expand and contract the infrastructure footprint of your application dynamically achieves the cost containment objectives.     Herve Roggero is a SQL Azure MVP and co-author of Pro SQL Azure (APress).  He is the co-founder of Blue Syntax Consulting (www.bluesyntax.net), a company focusing on cloud computing technologies helping customers understand and adopt cloud computing technologies. For more information contact herve at hroggero @ bluesyntax.net .

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  • Grid computing projects similar to NGrid (thread based)

    - by DivdeAndConquer
    Hello there, first time poster. This is a great place for reading about programming problems. I've been looking at some grid computing projects for .Net/Mono and stumbled upon NGrid. NGrid seems really appealing for grid computing because you simply pass threads to it and there is very little modification you have to make to your code. However, I see that NGrid (http://ngrid.sourceforge.net/?page=overview) is still at version 0.7 and hasn't been updated since May 2008. So, I'm wondering if there are any other grid computing projects that use a similar thread-passing architecture and if anyone has had success using NGrid.

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  • Understanding: cloud-server, cloud-hosting, cloud-computing, the cloud

    - by Abel
    There's a lot of buzz about these subjects and there seems little consensus on the terms. Is that just me not understanding the subject, or is there a clear meaning for each of these terms? Are there more elaborate terms or descriptions that describe what a cloud provider has, is or offers? EDIT: rewritten question, apparently it was unclear, partially due to the bloat I added.

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  • Web Site Serving, Cloud-Computing, oh, my

    - by Frank
    I'm planning a software based service. To give it a bit of context (type of traffic), assume it similar to facebook in nature (with a little GitHub thrown in). I've been trying to understand my different hosting options. I've been using a shared host with GoDaddy for years just fine. I currently host a Wordpress web site there and I've not had any problems. Quite frankly, they've taken good care of me. However, the nature of a shared hosting environment is limited in nature. For example, I can't do anything but host a web site there. For example, I can not run a Mercurial server. Last time I attempted to build a web application with the intention of eventually launching it via GoDaddy, I ran in to all sorts of troubles because it was shared-hosted. Assembly issues, etc. At the time, the cost and time sank my project. (The lack of direct access was also frustrating.) (to be fair to godaddy, this was over 3 years ago) I've been looking at Rackspace or Amazon as a possible cloud solution but it seems to be just processing power and bandwidth (and an OS). From what I understand, I'd need to get Apache and MySQL Working on my own. The way cloud hosting is priced, however, seems appealing. I figure my final option might be to use a virtual private host. I think this would be more flexible than a shared-host site but less scalable than a cloud based server. So, I guess my question is what is an appropriate solution for someone who intends to build a web application service? I figure that I need to establish a hosting environment now rather than later so I can plan to effectively use the environment. I'd prefer to be fairly economical to start out with. I really can't afford to pay $999 (or even $99) while I build up the site and get the core functionality online but at the same time, I'd like to have the selected environment grow as needed. Thank you.

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  • How secure is cloud computing?

    - by Rhubarb
    By secure, I don't mean the machines itself and access to it from the network. I mean, and I suppose this could be applied to any kind of hosting service, when you put all your intellectual property onto a hosted provider, what happens to the hard disks as they cycle through them? Say I've invested million into my software, and the information and data that I have is valuable, how can I be sure it isn't read off old disks as they're recycled? Is there some kind of standard to look for that ensures a provider is going to use the strictest form of intellectual property protection? Is SAS70 applicable here?

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  • Cloud computing?

    - by Shawn H
    I'm an analyst and intermediate programmer working for a consulting company. Sometimes we are doing some intensive computing in Excel which can be frustrating because we have slow computers. My company does not have enough money to buy everyone new computers right now. Is there a cloud computing service that allows me to login to a high performance virtual computer from remote desktop? We are not that technical so preferrably the computer is running Windows and I can run Excel and other applications from this computer. Thanks

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  • cloud computing in .net 4.0

    - by HotTester
    Since the launch of .net 4.0 the buzz word has been cloud computing. But very little is said and discussed about it in perspective of .net technologies. Further is it really the worth to invest or do we have sufficient current technologies that can handle what cloud computing offers ? Can you please describe it and an example would be quite helpful ! Thanks in advance.

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  • Retro Video Game Collection

    - by Matt Christian
    Recently I've decided, in true nerd fashion, to collect either comic books or video games.  Considering I'm much more versed in the technological arts and not in ACTUAL art, I thought collecting old video games would be an interesting venture.  After all, I am a self-described compulsive shopper (my bank statement at the end of the month has a purchase every few days).  (Don't worry, I'm not in debt and still pay my bills on time!) I went to a local video game store in Stevens Point called Gaming Generations which is a neat little shop with loads of old games for great prices.  For example, any NES cartridge on the shelf (not behind glass) is, at most, $4.99 with the cheaper ones around $1.99.  During my first round at GG, I picked up the following: NES: - Fester's Quest - Adventures of Link (Zelda 2, grey cart) - Little Nemo - Total Recall - The Goonies 2 PSX: - Galerians N64: - Mission: Impossible - Hybrid Heaven I was a little cautious, would I even like collecting old games?  As soon as I popped a few of those games in I knew right away the answer was an astounding YES!  Not only is it fun to bring back memories of all these old games, but searching for them in stores is also a blast and saying 'I have that one, I need the second one.' After finding such joy in buying these games, I decided to go search through 4-5 stores in Wausau for old games as well.  While the prices were a bit higher and selection smaller, the search was still fun.  I found the following: NES: - Maniac Mansion - T&C Surf - Chip N Dale: Rescue Rangers - TMNT (the first one) - Mission: Impossible N64: - Turok - Turok 2 Genesis: - Sonic the Hedgehog Dreamcast: - Shenmue And I found a Gamegear for $5!  Now I just need to find games for it... Tonight I will go on one more small expedition into the used, once again stopping at GG and another second hand store to see if I can find any items for my collection.

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  • Cloud Computing : publication du volet 3 du Syntec Numérique

    - by Eric Bezille
    Une vision client/fournisseur réunie autour d'une ébauche de cadre contractuel Lors de la Cloud Computing World Expo qui se tenait au CNIT la semaine dernière, j'ai assisté à la présentation du nouveau volet du Syntec numérique sur le Cloud Computing et les "nouveaux modèles" induits : modèles économiques, contrats, relations clients-fournisseurs, organisation de la DSI. L'originalité de ce livre blanc vis à vis de ceux déjà existants dans le domaine est de s'être attaché à regrouper l'ensemble des acteurs clients (au travers du CRIP) et fournisseurs, autour d'un cadre de formalisation contractuel, en s'appuyant sur le modèle e-SCM. Accélération du passage en fournisseur de Services et fin d'une IT en silos ? Si le Cloud Computing permet d'accélérer le passage de l'IT en fournisseur de services (dans la suite d'ITIL v3), il met également en exergue le challenge pour les DSI d'un modèle en rupture nécessitant des compétences transverses permettant de garantir les qualités attendues d'un service de Cloud Computing : déploiement en mode "self-service" à la demande, accès standardisé au travers du réseau,  gestion de groupes de ressources partagées,  service "élastique" : que l'on peut faire croitre ou diminuer rapidement en fonction de la demande mesurable On comprendra bien ici, que le Cloud Computing va bien au delà de la simple virtualisation de serveurs. Comme le décrit fort justement Constantin Gonzales dans son blog ("Three Enterprise Principles for Building Clouds"), l'important réside dans le respect du standard de l'interface d'accès au service. Ensuite, la façon dont il est réalisé (dans le nuage), est de la charge et de la responsabilité du fournisseur. A lui d'optimiser au mieux pour être compétitif, tout en garantissant les niveaux de services attendus. Pour le fournisseur de service, bien entendu, il faut maîtriser cette implémentation qui repose essentiellement sur l'intégration et l'automatisation des couches et composants nécessaires... dans la durée... avec la prise en charge des évolutions de chacun des éléments. Pour le client, il faut toujours s'assurer de la réversibilité de la solution au travers du respect des standards... Point également abordé dans le livre blanc du Syntec, qui rappelle les points d'attention et fait un état des lieux de l'avancement des standards autour du Cloud Computing. En vous souhaitant une bonne lecture...

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  • CISDI Cloud - Industrial Cloud Computing Platform based on Oracle Products

    - by Wenyu Duan
    In today's era, Cloud Computing is becoming integral to the vision and corporate strategy of leading organizations and is often seen as a key business driver to achieve growth and innovation. Headquartered in Chongqing, China, CISDI Engineering Co., Ltd. is a large state-owned engineering company, offering consulting, engineering design, EPC contracting, and equipment integration services to steel producers all over the world. With over 50 years of experience, CISDI offers quality services for every aspect of production for projects in the metal industry and the company has evolved into a leading international engineering service group with 18 subsidiaries providing complete lifecycle for E&C projects. CISDI group delegation led by Mr. Zhaohui Yu, CEO of CISDI Group, Mr. Zhiyou Li, CEO of CISDI Info, Mr. Qing Peng, CTO of CISDI Info and Mr. Xin Xiao, Head of CISDI Info's R&D joined Oracle OpenWorld 2012 and presented a very impressive cloud initiative case in their session titled “E&C Industry Solution in CISDI Cloud - An Industrial Cloud Computing Platform Based on Oracle Products”. CISDI group plans to expand through three phases in the construction of its cloud computing platform: first, it will relocate its existing technologies to Oracle systems, along with establishing private cloud for CISDI; secondly, it will gradually provide mixed cloud services for its subsidiaries and partners; and finally it plans to launch an industrial cloud with a highly mature, secure and scalable environment providing cloud services for customers in the engineering construction and steel industries, among others. “CISDI Cloud” will become the growth engine for the organization to expand its global reach through online services and achieving the strategic objective of being the preferred choice of E&C companies worldwide. The new cloud computing platform is designed to provide access to the shared computing resources pool in a self-service, dynamic, elastic and measurable way. It’s flexible and scalable grid structure can support elastic expansion and sustainable growth, and can bring significant benefits in speed, agility and efficiency. Further, the platform can greatly cut down deployment and maintenance costs. CISDI delegation highlighted these points as the key reasons why the group decided to have a strategic collaboration with Oracle for building this world class industrial cloud - - Oracle’s strategy: Open, Complete and Integrated - Oracle as the only company who can provide engineered system, with complete product chain of hardware and software - Exadata, Exalogic, EM 12c to provide solid foundation for "CISDI Cloud" The cloud blueprint and advanced architecture for industrial cloud computing platform presented in the session shows how Oracle products and technologies together with industrial applications from CISDI can provide end-end portfolio of E&C industry services in cloud. CISDI group was recognized for business leadership and innovative solutions and was presented with Engineering and Construction Industry Excellence Award during Oracle OpenWorld.

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  • DIY Coffee Table Arcade Hides Retro Gaming Inside

    - by Jason Fitzpatrick
    Last week we showed you a nifty man-cave arcade-in-coffee-table build that was a bit, shall we say, exposed. If you’re looking for a sleek build that conceals its arcade-heart until it’s game time, this clean and concealed build is for you. Courtesy of IKEAHacker reader Sam Wang, the beauty of this build is that other than the rectangle of black glass in the center of the table–which could just as well be a design accent–there is no indication that the coffee table is a gaming machine when not in use. Slide out the drawers and boot it up, however, and you’re in business–full MAME arcade emulation at your finger tips. Hit up the link below to check out his full photo build guide. My DIY Arcade Machine Coffee Table [via IKEAHacker] How To Switch Webmail Providers Without Losing All Your Email How To Force Windows Applications to Use a Specific CPU HTG Explains: Is UPnP a Security Risk?

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  • Title of a specific retro game with color absorption

    - by Rene B
    I am looking for the title a free multiplayer (on one machine) DOS game i can't remember Players are steering (with cursors/WASD keys) kind of ufos which looks like donuts from top-down view. These 'ufos' attract colored particles. When your particles collide with particles from other players (in a different color), the colors will mix. If the particles are more your color than the other players color, they will start following you. The only remaining player (with the most color particles) wins the game. Can you please give me the game title? THANK YOU!

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  • Creating a retro-style palette swapping effect in OpenGL

    - by Zack The Human
    I'm working on a Megaman-like game where I need to change the color of certain pixels at runtime. For reference: in Megaman when you change your selected weapon then main character's palette changes to reflect the selected weapon. Not all of the sprite's colors change, only certain ones do. This kind of effect was common and quite easy to do on the NES since the programmer had access to the palette and the logical mapping between pixels and palette indices. On modern hardware, though, this is a bit more challenging because the concept of palettes is not the same. All of my textures are 32-bit and do not use palettes. There are two ways I know of to achieve the effect I want, but I'm curious if there are better ways to achieve this effect easily. The two options I know of are: Use a shader and write some GLSL to perform the "palette swapping" behavior. If shaders are not available (say, because the graphics card doesn't support them) then it is possible to clone the "original" textures and generate different versions with the color changes pre-applied. Ideally I would like to use a shader since it seems straightforward and requires little additional work opposed to the duplicated-texture method. I worry that duplicating textures just to change a color in them is wasting VRAM -- should I not worry about that?

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