Lambda the Ultimate

Energy-efficient computing is important in several systems ranging from embedded devices to large scale data centers. Several application domains offer the opportunity to tradeoff quality of service/solution (QoS) for improvements in performance and reduction in energy consumption. Programmers sometimes take advantage of such opportunities, albeit in an ad-hoc manner and often without providing any QoS guarantees. We propose a system called Green that provides a simple and flexible framework that allows programmers to take advantage of such approximation opportunities in a systematic manner while providing statistical QoS guarantees. Green enables programmers to approximate expensive functions and loops and operates in two phases. In the calibration phase, it builds a model of the QoS loss produced by the approximation. This model is used in the operational phase to make approximation decisions based on the QoS constraints specified by the programmer. The operational phase also includes an adaptation function that occasionally monitors the runtime behavior and changes the approximation decisions and QoS model to provide strong QoS guarantees.

The basic approach is not specific to energy considerations, and is basically based on placing approximation code based on profiling data. Energy is measured by sampling current and voltage from the main power cable.

It is nice to see programming language ideas being put to use to help protect the environment...

The system was implemented using the Phoenix compiler framework.

I Googled around quite a bit and didn't turn up much. I do note mllex and mlyacc distributed with SMLNJ, but it's not clear how to handle user defined operators with a yacc based strategy, or even whether SMLNJ uses these tools to implement itself.

Is this typically a job for good old hand rolled recursive descent?

For any and all pointers, info - thanks much!

Scott