Back in January, Nvidia hired Mr. Dally as its new chief scientist. The move caught a lot of people’s attention, because Mr. Dally served as the chairman of Stanford University’s impressive computer science department and had done pioneering work in the semiconductor and software fields. Nvidia, however, has kept Mr. Dally under lock and key since his hiring, refusing to permit him to talk to the news media. Until now.

Earlier this week, Mr. Dally and I had a chat about his decision to bolt the comfy confines of academia for Nvidia’s life-or-death struggle with Intel and Advanced Micro Devices. (Mr. Dally continues to shepherd about 12 Stanford graduate students, although he’s full time at Nvidia.) “It seemed to me that now is the time you want to be out there bringing products to the marketplace rather than writing papers,” Mr. Dally said.

Mr. Dally has bought into the notion — often espoused by Nvidia’s chief executive, Jen-Hsun Huang — that we’re on the cusp of a computing revolution.

Nvidia likes to say that its graphics chips will move from gaming machines and engineers’ workstations into all types of computers and servers. This assumption hinges on graphics chips’ ability to crunch through complex software faster than mainstream chips. Today’s graphics chips rely on tens and even hundreds of tiny cores that can all work together on a specific software job at the same time. They divvy up the work and then assemble the result – a mode of computing known as parallel processing.

Chips like Intel’s Core products tend to throw just a couple of very large, powerful processing cores at software. These cores are great at handling the majority of software, which runs faster when it travels through a beefier engine.

Read the entire article at The New York Times.