Autodesk is now in Amazon Web Services

http://aws.amazon.com/solutions/case-studies/autodesk/

https://www.youtube.com/watch?v=TsRBftzZsQo

https://www.youtube.com/watch?v=v7ilSVM44MI

Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers.

Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 reduces the time required to obtain and boot new server instances to minutes, allowing you to quickly scale capacity, both up and down, as your computing requirements change. Amazon EC2 changes the economics of computing by allowing you to pay only for capacity that you actually use. Amazon EC2 provides developers the tools to build failure resilient applications and isolate themselves from common failure scenarios.

Firefly- Design Interactively

http://www.fireflyexperiments.com/#home

Fortunately, Firefly has an advanced Code Generation feature which translate the visual representation of your Grasshopper graph directly into Arduino compatible code.  And it does this all on the fly. Now, you don't need to worry about writing all of that code yourself.  Simply, prototype your design as you normally would, and the Code Generator will work in the background writing all of the code necessary to make your design come to life!

https://vimeo.com/93142381

https://www.youtube.com/watch?v=FHnaLbghZ1o

The Design of Software Engineering

http://www.danieldavis.com/thesis-ch3/

Comparison of various Software Engineering Bodies of Knowledge (click for larger image). Blue: Equivalent knowledge areas. Red: Areas of knowledge applied to parametric modelling in my research.

The programming languages architects use categorised by Appleby and VandeKopple’s (1997, xiv) taxonomy of programming paradigms.

To a computer, a parametric model reads as a set of instructions. The computer takes the inputs, applies the sequence of explicit functions, and thereby generates the parametric model’s outputs. “Anybody involved in any job that ultimately creates instructions that are executed by a computer, machine or even biological entity, can be said to be programming” argues David Rutten (2012), the developer of the popular parametric modelling interface, Grasshopper. This is not to say programming and parametric modelling are synonymous. There are clearly significant differences between designing architecture and designing software. Yet in both cases, there is a common concern with automating computation through sequences of instructions. Despite this “common ground” (Woodbury 2010, 66), and despite architects recognising that parametric modelling is often “more similar to programming than to conventional design” (Weisberg 2008, 16.12), the implications of the parallels between parametric modelling and software engineering remain largely unexplored. In particular, two pertinent questions remain unaddressed: if parametric modelling and software engineering both concern the automation of computers, do they both encounter the same challenges when doing so? And if they share the same challenges, are parts of their respective bodies of knowledge transferable in alleviating these challenges?