Mobile computing processors and flash memory are the basis of a new, energy-efficient server architecture created by researchers at Carnegie Mellon University and Intel Labs Pittsburgh. Cutting data center energy use is imperative for companies whose electricity bills are skyrocketing thanks to ever-higher chip densities and ever-hotter operating temperatures.

Fast Array of Wimpy Nodes (FAWN) consists of 21 nodes, each with a low-cost, low-power, off-the-shelf processor and a 4GB compact flash card. At peak utilization, the Linux-based cluster operates on less energy than a 100-watt light bulb, yet can perform up to 100 times as many queries using the same amount of energy as a conventional disk-based cluster, according to the researchers. Crafting software to leverage the capabilities of these small processors is the FAWN project’s top mission.  

 “Dave [Andersen] and I are focusing on the software—how to build system-level software and applications to exploit these properties,” said Michael Kaminsky, senior research scientist at Intel Labs Pittsburgh. Kaminsky and Andersen, a Carnegie-Mellon assistant professor of computer science, are leading the FAWN project.

FAWN is ideally suited for some kinds of processing, yet ill-suited to other kinds.

The architecture’s strong suit is handling key-value storage systems, in which small pieces of information must be accessed quickly. Key-value storage is used by social networking sites such as Facebook.com. Because FAWN operates according to the same principles as parallel processing, it is less well-suited for computing tasks that are best done by a single processor.

Some types of cloud-based computing could benefit from the FAWN architecture, said Andersen. “There is an aspect of cloud computing that is very suitable for this. Amazon, for example offers a cloud storage service, cloud database and cloud compute service. Of those three, the storage and database services will work well on FAWN, but not necessarily the compute services,” said Andersen.

Data-intensive analytic applications could also benefit from the architecture because FAWN helps relieve bandwidth limitations in getting data in or out of the CPU, said Andersen. Software built for distributed processing, such as Hadoop, could benefit as well, he added.

The current FAWN cluster uses 500MHz AMD processors. The team is currently at work on a 100-node FAWN cluster built with Intel dual-core 1.6GHz Intel Atom processors, which are commonly used in handheld devices and netbook computers.

The work was supported in part by gifts from Network Appliance, Google and Intel, and by a grant from the National Science Foundation.