Multicore Processors Create ­Software Headaches

For decades, improving processor performance meant cranking up a chip’s clock speed. The payoff was immediately obvious to users: applications ran faster. But a faster chip consumes more electricity, draining batteries dry in mobile devices. Consequently, chip makers moved to energy-saving multicore designs, where multiple low-power processors on a single chip combine to replicate the performance of a single, faster processor (see “Designing for Mobility”).

Unfortunately, applications on multicore systems don’t get faster automatically as cores are added. Software has to be written to take advantage of the parallel processing power. And writing programs that run efficiently and stably across multiple cores is hard. Unless we solve this programming problem, says Prith Banerjee, Hewlett-Packard’s senior vice president of research, users won’t see any speed advantage in new microprocessors. Banerjee adds, “This is a very fundamental problem.”

A promising potential solution is to take human programmers out of the loop as much as possible: rather than have individual programmers work out how to make their applications run across two, four, or more cores, the messy details could be left to compilers, the software used to convert high-level programming languages into the machine code a computer can understand. All the major software and chip companies, along with many academic researchers, are working to develop compilers that can handle such tasks. The biggest obstacle is that it’s difficult to identify the parts of a program that don’t depend on other parts, so that a core won’t be left idle while it waits for some piece of data. Simply persuading developers to write cleaner programs, with well-defined interfaces between blocks of code, would make the job much easier, says Wen-mei Hwu, a professor of electrical and computer engineering at the University of Illinois. But he estimates that it will be five years before multicore-friendly compilers and matching programming practices diffuse through the computer industry.