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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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  • The speed of .NET in numerical computing

    - by Yin Zhu
    In my experience, .net is 2 to 3 times slower than native code. (I implemented L-BFGS for multivariate optimization). I have traced the ads on stackoverflow to http://www.centerspace.net/products/ the speed is really amazing, the speed is close to native code. How can they do that? They said that: Q. Is NMath "pure" .NET? A. The answer depends somewhat on your definition of "pure .NET". NMath is written in C#, plus a small Managed C++ layer. For better performance of basic linear algebra operations, however, NMath does rely on the native Intel Math Kernel Library (included with NMath). But there are no COM components, no DLLs--just .NET assemblies. Also, all memory allocated in the Managed C++ layer and used by native code is allocated from the managed heap. Can someone explain more to me? Thanks!

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  • curious ill conditioned numerical problem

    - by aaa
    hello. somebody today showed me this curious ill conditioned problem (apparently pretty famous), which looks relatively simple ƒ = (333.75 - a^2)b^6 + a^2 (11a^2 b^2 - 121b^4 - 2) + 5.5b^8 + a/(2^b) where a = 77617 and b = 33096 can you determine correct answer?

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  • C++ Numerical truncation error

    - by Andrew
    Hello everyone, sorry if dumb but could not find an answer. #include <iostream> using namespace std; int main() { double a(0); double b(0.001); cout << a - 0.0 << endl; for (;a<1.0;a+=b); cout << a - 1.0 << endl; for (;a<10.0;a+=b); cout << a - 10.0 << endl; cout << a - 10.0-b << endl; return 0; } Output: 0 6.66134e-16 0.001 -1.03583e-13 Tried compiling it with MSVC9, MSVC10, Borland C++ 2010. All of them arrive in the end to the error of about 1e-13. Is it normal to have such a significant error accumulation over only a 1000, 10000 increments?

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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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  • Numerical stability in continuous physics simulation

    - by Panda Pajama
    Pretty much all of the game development I have been involved with runs afoul of simulating a physical world in discrete time steps. This is of course very simple, but hardly elegant (not to mention mathematically inaccurate). It also has severe disadvantages when large values are involved (either very large speeds, or very large time intervals). I'm trying to make a continuous physics simulation, just for learning, which goes like this: time = get_time() while true do new_time = get_time() update_world(new_time - time) render() time = new_time end And update_world() is a continuous physical simulation. Meaning that for example, for an accelerated object, instead of doing object.x = object.x + object.vx * timestep object.vx = object.vx + object.ax * timestep -- timestep is fixed I'm doing something like object.x = object.x + object.vx * deltatime + object.ax * ((deltatime ^ 2) / 2) object.vx = object.vx + object.ax * deltatime However, I'm having a hard time with the numerical stability of my solutions, especially for very large time intervals (think of simulating a physical world for hundreds of thousands of virtual years). Depending on the framerate, I get wildly different solutions. How can I improve the numerical stability of my continuous physical simulations?

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  • What modern alternatives to Numerical Recipes exist?

    - by Stewart
    In the past, the Numerical Recipes book was considered the gold standard reference for numerical algorithms. The earliest Fortran Edition was followed by editions in C and C++ and others, bringing it then more up-to-date. Through these, it provided reference code for the state-of-the-art algorithms of the day. Older editions are available online for free nowadays. Unfortunately, I think it is now mostly useful only as a historic tome. The "software engineering" practises seem to me to be outdated, and the actual content hasn't kept pace with the literature. What comprehensive yet approachable references should the modern programmer look at instead?

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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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  • Extreme Optimization Numerical Libraries for .NET – Part 1 of n

    - by JoshReuben
    While many of my colleagues are fascinated in constructing the ultimate ViewModel or ServiceBus, I feel that this kind of plumbing code is re-invented far too many times – at some point in the near future, it will be out of the box standard infra. How many times have you been to a customer site and built a different variation of the same kind of code frameworks? How many times can you abstract Prism or reliable and discoverable WCF communication? As the bar is raised for whats bundled with the framework and more tasks become declarative, automated and configurable, Information Systems will expose a higher level of abstraction, forcing software engineers to focus on more advanced computer science and algorithmic tasks. I've spent the better half of the past decade building skills in .NET and expanding my mathematical horizons by working through the Schaums guides. In this series I am going to examine how these skillsets come together in the implementation provided by ExtremeOptimization. Download the trial version here: http://www.extremeoptimization.com/downloads.aspx Overview The library implements a set of algorithms for: linear algebra, complex numbers, numerical integration and differentiation, solving equations, optimization, random numbers, regression, ANOVA, statistical distributions, hypothesis tests. EONumLib combines three libraries in one - organized in a consistent namespace hierarchy. Mathematics Library - Extreme.Mathematics namespace Vector and Matrix Library - Extreme.Mathematics.LinearAlgebra namespace Statistics Library - Extreme.Statistics namespace System Requirements -.NET framework 4.0  Mathematics Library The classes are organized into the following namespace hierarchy: Extreme.Mathematics – common data types, exception types, and delegates. Extreme.Mathematics.Calculus - numerical integration and differentiation of functions. Extreme.Mathematics.Curves - points, lines and curves, including polynomials and Chebyshev approximations. curve fitting and interpolation. Extreme.Mathematics.Generic - generic arithmetic & linear algebra. Extreme.Mathematics.EquationSolvers - root finding algorithms. Extreme.Mathematics.LinearAlgebra - vectors , matrices , matrix decompositions, solvers for simultaneous linear equations and least squares. Extreme.Mathematics.Optimization – multi-d function optimization + linear programming. Extreme.Mathematics.SignalProcessing - one and two-dimensional discrete Fourier transforms. Extreme.Mathematics.SpecialFunctions

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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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  • Getting Started with Cloud Computing

    - by juanlarios
    You’ve likely heard about how Office 365 and Windows Intune are great applications to get you started with Cloud Computing. Many of you emailed me asking for more info on what Cloud Computing is, including the distinction between "Public Cloud" and "Private Cloud". I want to address these questions and help you get started. Let's begin with a brief set of definitions and some places to find more info; however, an excellent place where you can always learn more about Cloud Computing is the Microsoft Virtual Academy. Public Cloud computing means that the infrastructure to run and manage the applications users are taking advantage of is run by someone else and not you. In other words, you do not buy the hardware or software to run your email or other services being used in your organization – that is done by someone else. Users simply connect to these services from their computers and you pay a monthly subscription fee for each user that is taking advantage of the service. Examples of Public Cloud services include Office 365, Windows Intune, Microsoft Dynamics CRM Online, Hotmail, and others. Private Cloud computing generally means that the hardware and software to run services used by your organization is run on your premises, with the ability for business groups to self-provision the services they need based on rules established by the IT department. Generally, Private Cloud implementations today are found in larger organizations but they are also viable for small and medium-sized businesses since they generally allow an automation of services and reduction in IT workloads when properly implemented. Having the right management tools, like System Center 2012, to implement and operate Private Cloud is important in order to be successful. So – how do you get started? The first step is to determine what makes the most sense to your organization. The nice thing is that you do not need to pick Public or Private Cloud – you can use elements of both where it makes sense for your business – the choice is yours. When you are ready to try and purchase Public Cloud technologies, the Microsoft Volume Licensing web site is a good place to find links to each of the online services. In particular, if you are interested in a trial for each service, you can visit the following pages: Office 365, CRM Online, Windows Intune, and Windows Azure. For Private Cloud technologies, start with some of the courses on Microsoft Virtual Academy and then download and install the Microsoft Private Cloud technologies including Windows Server 2008 R2 Hyper-V and System Center 2012 in your own environment and take it for a spin. Also, keep up to date with the Canadian IT Pro blog to learn about events Microsoft is delivering such as the IT Virtualization Boot Camps and more to get you started with these technologies hands on. Finally, I want to ask for your help to allow the team at Microsoft to continue to provide you what you need. Twice a year through something we call "The Global Relationship Study" – they reach out and contact you to see how they're doing and what Microsoft could do better. If you get an email from "Microsoft Feedback" with the subject line "Help Microsoft Focus on Customers and Partners" between March 5th and April 13th, please take a little time to tell them what you think. Cloud Computing Resources: Microsoft Server and Cloud Computing site – information on Microsoft's overall cloud strategy and products. Microsoft Virtual Academy – for free online training to help improve your IT skillset. Office 365 Trial/Info page – get more information or try it out for yourself. Office 365 Videos – see how businesses like yours have used Office 365 to transition to the cloud. Windows Intune Trial/Info – get more information or try it out for yourself. Microsoft Dynamics CRM Online page – information on trying and licensing Microsoft Dynamics CRM Online. Additional Resources You May Find Useful: Springboard Series Your destination for technical resources, free tools and expert guidance to ease the deployment and management of your Windows-based client infrastructure. TechNet Evaluation Center Try some of our latest Microsoft products for free, Like System Center 2012 Pre-Release Products, and evaluate them before you buy. AlignIT Manager Tech Talk Series A monthly streamed video series with a range of topics for both infrastructure and development managers. Ask questions and participate real-time or watch the on-demand recording. Tech·Days Online Discover what's next in technology and innovation with Tech·Days session recordings, hands-on labs and Tech·Days TV.

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  • Cloud Computing Business Benefits

    - by workflowman
    If you have been living under a rock for the past year, you wouldn't have heard about cloud computing. Cloud computing is a loose term that describes anything that is hosted in data centers and accessed via the internet. It is normally associated with developers who draw clouds in diagrams indicating where services or how systems communicate with each other. Cloud computing also incorporates such well-known trends as Web 2.0 and Software as a Service (SaaS) and more recently Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). Its aim is to change the way we compute, moving from traditional desktop and on-premises servers to services and resources that are hosted in the cloud.  Benefits of Cloud Computing  There are clearly benefits in building applications using cloud computing, some of which are listed here:  Zero up- front investment:  Delivering a large-scale system costs a fortune in both time and money. Often IT departments are split into hardware/network and software services. The hardware team provisions servers and so forth under the requirements of the software team. Often the hardware team has a different budget that requires approval. Although hardware and software management are two separate disciplines, sometimes what happens is developers are given the task to estimate CPU cycles, disk space, and so forth, which ends up in underutilized servers.  Usage-based costing:  You pay for what you use, no more, no less, because you never actually own the server. This is similar to car leasing, where in the long run you get a new car every three years and maintenance is never a worry.  Potential for shrinking the processing time:  If processes are split over multiple machines, parallel processing is performed, which decreases processing time.  More office space:  Walk into most offices, and guaranteed you will find a medium- sized room dedicated to servers.  Efficient resource utilization:  The resource utilization is handed by a centralized cloud administrator who is in charge of deciding exactly the right amount of resources for a system. This takes the task away from local administrators, who have to regularly monitor these servers.  Just-in-time infrastructure:  If your system is a success and needs to scale to meet demand, this can cause further time delays or a slow- performing service. Cloud computing solves this because you can add more resources at any time.  Lower environmental impact:  If servers are centralized, potentially an environment initiative is more likely to succeed. As an example, if servers are placed in sunny or windy parts of the world, then why not use these resources to power those servers?  Lower costs:  Unfortunately, this is one point that administrators will not like. If you have people administrating your e-mail server and network along with support staff doing other cloud-based tasks, this workforce can be reduced. This saves costs, though it also reduces jobs.

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