Cutting cost and power consumption for big data
Random-access memory, or RAM, is where computers like to store the data they’re working on. A processor can retrieve data from RAM tens of thousands of times more rapidly than it can from the computer’s disk drive. But in the age of big data, data sets are often much too large to fit in a single computer’s RAM. The data describing a single human genome would take up the RAM of somewhere between 40 and 100 typical computers. Flash memory — the type of memory used by most portable devices — could provide an alternative to conventional RAM for big-data applications. It’s about a tenth as expensive, and it consumes about a tenth as much power. The problem is that it’s also a tenth as fast. But at the International Symposium on Computer Architecture in June, MIT researchers presented a new system that, for several common big-data applications, should make servers using flash...