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Researchers at Harvard and Microsoft have authored a paper that seeks to prove that a small, power-efficient core like the Intel Atom chip can be better suited for search, a conclusion that might help explain Google’s recent acquisition of the Agnilux chip house.

There’s one catch: The ideal chip is not one of the Atom chips Intel ships, but a hypothetical, multicore Atom chip that Intel could build, but has not publicly announced. The current Atom designs don’t provide the proper resources to the search engine. The result? Degraded search results, a big no-no.

The paper has been accepted for presentation at the International Symposium on Computer Architecture in Saint-Malo, France, on June 19, where it will be publicly presented.

The paper compares the performance, reliability, and cost of ownership of two microprocessors: a power-optimized “Harpertown” L5420 four-core Xeon, a 2.5-GHz, 45nm part based on the “Penryn” core; and the “Diamondville” dual-core Atom, a 1.6-GHz microprocessor also fabricated on a 45nm process.

The new conventional wisdom says that small, power-efficient cores may be better suited to specialized functions like search, in part because the power efficiencies and multicore architecture mitigate any drop in performance. But the team of Microsoft and Harvard researchers, led by Vijay Janapa Reddi, a doctoral candidate at Harvard’s School of Engineering and Applied Sciences, came to a different conclusion, using Microsoft’s own Bing search engine as a research tool.

“Based on our analysis of running Bing.com on Atom-based servers at Microsoft Research, we find that small mobile cores aren’t an easy transition for data centers to make,” Reddi wrote in an email. “The benefits of lower power consumption come at the price of efficiency. Simply put, your search engine results will be different if you run Bing.com (and perhaps even Google.com) on Atom versus using Xeon servers. End user satisfaction can suffer.”

The test pitted each processor as an index serving node (ISN). Under Bing, if the top-level aggregator that receives the search query hasn’t stored it in its local cache, it needs to send it out to an ISN. Each node uses neural networks to identify and to return some number of the most relevant pages and their dynamic ranks. Each ISN is responsible for ranking pages, as well as generating descriptions of relevant pages for the user.

For the test, the researchers used real Bing search queries that had been previously sampled. For each query, the ISN computed overall ranks for pages that matched the query for a 1GB production index, which was stored in memory to eliminate the variable time in which the data would have to otherwise be fetched from a hard disk.

And there was also a critical metric: “The quality of search or the relevance of pages depends upon ISN performance.” In other words, each chip had to maintain some critical quality-of-service level, returning the right results to a particular query. As it stands, that’s the Diamondville’s fatal flaw, the researchers found.

Typically, a server uses a server-class processor, in this case the Xeon. The paper argues from the premise that a Xeon is the de facto server processor, and sets out to prove whether or not the Atom can upend it.