Can Nvidia Play with the Big Boys?

Despite reporting a second-quarter loss last night, due in part to costs associated with the faulty packaging on some of its chips placed in thousands of laptops, Nvidia still has a plan for semiconductor domination through the GPU. But if it wants to execute, it needs to accept the realities that come with stepping into a competitive market. The earnings call shows Nvidia still has a lot to learn.

In yesterday evening’s call, CEO Jen-Hsun Huang admitted to a $196 million charge because of problems with its GPUs in some laptops. He also talked about some pricing mishaps that occurred as AMD pushed out a highly competitive product with a lower price. Nvidia is learning, but there are two bright spots in the call, related to its Tegra chipset for mobile Internet devices and smartphones and bringing high-level parallel processing to the consumer.

Huang said Tegra wouldn’t be shipping in products until next year (something he told us earlier this year in an interview), but growth from CUDA on laptops and desktops should have an impact over the second half of this year (which will be the second half of fiscal 2009 for the firm). CUDA is a programming tool that allows software coded in C languages to run on the multiple cores in a GPU. It helped the company make inroads in the scientific computing community, and thanks to software from startups such as Elemental Technologies, the goal is to bring that level of parallel processing to consumers.

“We can’t just keep selling chips that make graphics run faster and cheaper. I mean, that’s all very nice and it’s all good but we need to advance the visual computing field in some remarkable and important way, and parallel computing is one of the most important investments that we are making,” Huang said on the call.

Such a shift, if well executed, will bring a level of power to computers that has been reserved for research institutions and mainframes. The next laptop you purchase could very well be able to analyze real-time trading data and spit out investment decisions. The key will be building software that’s designed to take advantage of it.

image courtesy of Nvidia