Stanford University, in conjunction with Sun, AMD, NVIDIA, IBM, Intel, and HP, is working to create a new computing model that fully exploits modern, multicore processing. As a feature in Ars Technica ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

SANTA CLARA, CA—APRIL 30, 2008—NVIDIA Corporation has announced that it is a founding member of Stanford University’s new Pervasive Parallelism Lab (PPL). The PPL will develop new techniques, tools, ...

Parallel computing is hard. Nothing new about that—it has been hard for the last four decades—but it used to be only the NSA and the occasional university who cared; parallel computers weren't cheap ...

Today NVIDIA let it be known that they've named Stanford University a CUDA Center of Excellence for their work in parallel computing research using NVIDIA GPUs and NVIDIA CUDA technology. NVIDIA's ...

Bill Dally, chairman of Stanford University's computer science department, will join the company as chief scientist and vice president of Nvidia Research. Brooke Crothers writes about mobile computer ...

The promise of quantum computing is that it will dramatically outshine traditional computers in tackling certain key problems: searching large databases, factoring large numbers, creating uncrackable ...

Stanford University and a consortium of technology companies are announcing a joint effort to build a Pervasive Parallelism Lab. The initiative pools the efforts of many Stanford computer scientists ...