Moore's law for software

Software design has strange relationship with the computing resources. If the resources are low it is difficult to design and if the resources are in abundance it is a challenge to utilize them. It is rather odd to ask the designers and developers to have Moore's law for software, but this is true and it is happening.

The immense computing resources have opened up a lot of opportunities for the designers and developers to design agile and highly interactive web interfaces by tapping into this computing cloud. Effective resource utilization by software is by far lagging the fast growing computing resources. Google has successfully demonstrated a link between the humongous cloud infrastructure and the applications that effectively use these resources. Gmail and Google Maps are examples of agile and highly interactive interfaces that consumes heavy resources. Google's MapReduce is an example of effective utilization of the computing resources by designing the search to use heavy parallelization. One of the challenges that designers face these days is to be able construct an application from an interaction perspective such that it can actually use the available resources effectively to provide better use experience. Traditionally the performance tuning is all about fixing software to perform faster without adding extra computing resources. The designers and developers now have a challenge to actually use the resources. The cloud computing is going to be more and more relevant as various organizations catch up on Web 2.0 and Enterprise 2.0. Google, Yahoo, Salesforce, and Microsoft are betting on their huge infrastructure that can deliver the juice required for their applications. Cloud computing is not just about hardware - it is about the scale of computing and the infrastructure that is required to get to that scale such as physical location, energy and cooling requirements, dark fiber etc.

Not every single piece of code in software can be parallelized. Developers hit a set of serial tasks in the code flow for many dynamic conditions. Semantic search is a classic example that has many challenges to use parallel computing resources since you do end up serializing certain tasks due to the dynamic nature of many semantic search engines and their abilities of natural language processing. Cognitive algorithms are not the same as statistical or relevancy algorithms and require a radically different design approach to effectively utilize the available resources.

Intel has been pushing the industry to improve performance on its multi core CPU . Microsoft recently announced an initiative to redesign the next Windows for multiple cores. The design is not just about one, two, or three cores. The resources are going to increase at much faster pace and software designers and developers are late to react and follow this massive computing. Computing in a cloud requires a completely different kind of approach in software design and there are some great opportunities to innovate around it.