2019-1-30 – Nvidia high-lights
“Each era of computing requires different kinds of chips. When desktops reigned supreme, chipmakers sought to maximize processing speed and graphics on a high-resolution screen, with far less concern about power consumption. (Desktops were, after all, always plugged in.) Intel mastered the design of these chips and made billions in the process. But with the advent of smartphones, demand shifted toward more efficient use of power, and Qualcomm, whose chips were based on designs by the British firm ARM, took the throne as the undisputed chip king.
Now, as traditional computing programs are displaced by the operation of AI algorithms, requirements are once again shifting. Machine learning demands the rapid-fire execution of complex mathematical formulas, something for which neither Intel’s nor Qualcomm’s chips are built. Into the void stepped Nvidia, a chipmaker that had previously excelled at graphics processing for video games. The math behind graphics processing aligned well with the requirements for AI, and Nvidia became the go-to player in the chip market.
These chips are central to everything from facial recognition to self-driving cars, and that has set off a race to build the next generation AI chip.”
AI Super-powers – China, Silicon Valley and the New World Order – p 96
“Creating a virtual environment that looks realistic takes time and skill. The details have to be hand-crafted using a graphics chip that renders 3D shapes, appropriate lighting, and textures. The latest blockbuster video game, Red Dead Redemption 2, for example, took a team of around 1000 developers more than eight years to create—occasionally working 100-hour weeks. That kind of workload might not be required for much longer. A powerful new AI algorithm can dream up the photorealistic details of a scene on the fly.
Developed by chipmaker Nvidia, the software won’t just make life easier for software developers. It could also be used to auto-generate virtual environments for virtual reality or for teaching self-driving cars and robots about the world.”
AI software can dream up an entire digital world from a simple sketch – MIT Technology Review
Nvidia has fulfilled its own goals and our expectation, from way back in 2010, that more and more of the aggregate double precision floating point computing power on the Top 500 list would come from accelerators. On the current November 2018 ranking, of the 1.41 exaflops of combined performance on the list, 702 petaflops of that is coming from accelerators, and 506 petaflops comes from Nvidia GPUs.
The Widening Gyre of Supercomputing – Next Platform
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