Data Analysis & Simulation

Archive for November, 2010

EasyFit Used to Improve the Forecasting of Software Project Status

Monday, November 29th, 2010

The software development community struggles with a way to identify if their projects are on-schedule given the inherent risks of constant invention that inevitably has elements of uncertainty and risk. Current practice is for developers to estimate a software project, and attempt to consider (up-front) all variations to get a viable estimate of time and cost. This process is laborious, and even with due rigor, project slip when the realization that estimates versus actual times fail to match. This leads to costly project overruns and lack of trust in future estimates.

As part of the Agile movement for software development, we think there is a better way and are championing the use of Monte-Carlo simulation as a ways of assessing likely progress and dealing with delays as early as possible… read the full case study

Will Cloud Computing Make Risk Analysis More Economically Efficient?

Monday, November 1st, 2010

What is Cloud Computing?

For some time now, there has been a lot of buzz around cloud computing – the relatively new computing paradigm in which the resources, software, and information are shared on the computer clusters and delivered to the users on demand through the Internet. The idea behind cluster computing is not new: if your applications require a lot of computing resources or impose very strict reliability requirements which cannot be met by a single personal computer or a server, you can link a group of computers into a cluster that will provide a much better performance.

Why Not Build a Cluster Yourself?

Building and maintaining a computer cluster in your organization may have some downsides, such as large upfront investments into technology infrastructure.and high running costs. Of course, there are companies that will do the job of building and managing a computer cluster for you, but anyway, the bottom line is: depending on how loaded your cluster is going to be, it may or may not be economically feasible for your company to run it on-site. For instance, if you need to quickly perform a very CPU-intensive calculation (e.g. render a complex 3D scene), but only once a day, chances are the cluster will not pay off.

And here’s where cloud computing comes into play: you can have access to great computing resources, pay only as you use them, and not worry about the underlying technology infrastructure. These factors combined can provide a great economic benefit, and some major Internet players, including Amazon and Google, are already offering cloud computing platforms for those who want to make their businesses more efficient.

Is Cloud Computing a Good Fit for Risk Analysis?

As one might guess, not just any kind of application can be efficiently run on the cloud. Because at the core of a cloud is a number of computers linked into a cluster, it is very good at processing a large number of independent tasks, such as requests to a web server. That might be the reason why the cloud computing platforms offered by Amazon and Google are mostly used to run websites.

If you consider risk analysis, it looks like an ideal application to be run on the cloud: an input model of several megabytes that can be easily sent to the cloud, a need for huge computational resources to quickly perform Monte Carlo simulation and distribution fitting, sometimes a need for a lot of storage to hold intermediate results, and relatively small-sized analysis results that can be sent back to the users as text and graphics. Add to that the ever-increasing complexity of risk models used across various industries, causing analysts to wait for hours while their simulations are running, and you have a potentially good opportunity to make risk analysis more economically efficient.

To perform further research in this field, we have partnered with Supportex, a technology services company based in Czech Republic, Europe. Supportex has some good experience providing a cloud computing platform for solving problems much more complex than just processing requests to a web server, that is why we have decided to rely on their hardware infrastructure and domain knowledge to run some test applications and see if cloud computing can be of real help in the field of risk analysis.

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