Wherever you look nowadays companies are searching for ways to market themselves as the environmental alternative, both because it makes customers feel good and promises to save them money. It follows that this is particularly true of large computing companies, given the cost of running data centres. As an example, US data centres alone run at an estimated cost of $2.7 billion, 1.2% of the total national energy consumption (ref).
The challenge is in finding ways to reduce the waste.
Broadly speaking there are two complementary approaches to reducing energy consumption: by making hardware more efficient, and software less resource intensive. Database research is beginning to appear on the latter approach, but I think a lot of the work on the hardware side is just as interesting.
Hardware Optimization
In The Case for Energy-Proportional Computing Barroso and Hölzle look at the energy efficiency of typical data centres. They show that the energy efficiency of a server is not directly proportional to its utilization – so, for example, a server running at near 0% utilization is using 50% of the power it uses at peak utilization. Ideally servers should use no power when not in use and power only in proportion to their utilization when they are. The authors call for future hardware design to aim for better energy proportionality, so that machines that are doing little, cost little.
Software Optimization
Two recent CIDR papers look at reducing energy consumption in database systems.
Energy Efficiency: The New Holy Grail of Data Management Systems Research looks at areas where software optimizations can be made, and more generally provides a number of approaches to reducing energy waste. It’s a worthwhile read if you want to get a good feel for the area.
Towards Eco-friendly Database Management Systems proposes that energy consumption be considered a first-class performance goal when planning and processing queries. The authors give details of two optimizations which can help to reduce the energy consumption of a database system.
The first uses the ability of modern processors to execute at a lower power voltage and frequency – their database can explicitly order the processor to operate at a lower voltage when such a change is desirable.
Their second technique is to queue queries where possible so that query aggregation can be used more often, reducing the number of repeat queries to the database. In some evaluations these approaches yield a 49% reduction in energy consumption against only a 3% increase in response time.
While these kind of solutions are not the whole answer (in many cases any reduction in performance would be unacceptable), they at the very least provide an interesting perspective.
Existing Resources
One of the most interesting statistics from this work is the 50% energy consumption of servers doing nothing at all. Essentially, machines doing nothing are still doing something. If we assume that we can’t reduce the energy consumption of these machines to zero, then the question becomes how can these machines be used?
When it comes to user workstations various volunteer computing projects (see Seti@HOME, Folding@Home) strive to make use of unused capacity. But within an enterprise there is a paucity of software able to take advantage of unused resources – resources, which as this article points out, are still costing companies money.
This is one of the motivations behind the H2O project which I am currently involved in.
http://www.cs.st-andrews.ac.uk/~angus/2009/07/trends-in-database-systems-research-column-stores/
