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Tesla Is Working With AMD To Develop Its Own AI Chip For Self-Driving Cars (cnbc.com)
An anonymous reader quotes a report from CNBC: Tesla is getting closer to having its own chip for handling autonomous driving tasks in its cars. The carmaker has received back samples of the first implementation of its processor and is now running tests on it, said a source familiar with the matter. The effort to build its own chip is in line with Tesla's push to be vertically integrated and decrease reliance on other companies. But Tesla isn't completely going it alone in chip development, according to the source, and will build on top of AMD intellectual property. On Wednesday Sanjay Jha, CEO of AMD spin-off GlobalFoundries, said at the company's technology conference in Santa Clara, California, that the company is working directly with Tesla. GlobalFoundries, which fabricates chips, has a wafer supply agreement in place with AMD through 2020. Tesla's silicon project is bounding ahead under the leadership of longtime chip architect Jim Keller, the head of Autopilot hardware and software since the departure of Apple veteran Chris Lattner in June. Keller, 57, joined Tesla in early 2016 following two stints at AMD and one at Apple. Keller arrived at Apple in 2008 through its acquisition of Palo Alto Semiconductor and was the designer of Apple's A4 and A5 iPhone chips, among other things. More than 50 people are working on the initiative under Keller, the source said. Tesla has brought on several AMD veterans after hiring Keller, including director Ganesh Venkataramanan, principal hardware engineer Bill McGee and system circuit design lead Dan Bailey.
According to Tom's Hardware, this story is a misunderstanding, and does not represent the actual words of the presentation.
From TH:
Some media outlets are reporting that GlobalFoundries is working with Tesla on AI technology for its cars. This erroneous report stems from a comment GloFlo's CEO Sanjay Jha made on stage on Wednesday at the fab's annual get-together in San Jose. ...
But what Jha actually said—which we can confirm because we were present to hear it firsthand—was that GlobalFoundries is trying to attract companies as business models change:
"As we develop these new technologies, we are also seeing a big shift in the business model and the foundry business. What is happening is that system companies like Google, like Amazon, like Tesla, like Microsoft, are coming directly to foundries. They are working directly with IP companies and system development companies because they want to control the hardware and software."
Global Foundries is not saying that it's working with Tesla--but that's not to say that AMD isn't working with Tesla. Jim Keller, formerly the chief architect for AMD's microprocessors, is now VP of autopilot hardware at Tesla.
Last year, AMD lost what Tesla CEO Elon Musk called a tight race against Nvidia for the auto company's GPU/AI business. Since that time, AMD has continued to show strength across multiple sectors.
The CNBC report said that its sources tied AMD and Tesla together, but neither AMD or Tesla will comment on the situation. The report indicated that Tesla was on a mission to develop its own chip for autonomous cars in order to be more vertically integrated, but that Tesla was potentially relying on building that "on top of AMD intellectual property." That particular wording certainly paints a dotted line to GlobalFoundries.
Full story at http://www.tomshardware.com/ne...
Florian Mueller predicts the (German) auto companies will become patent trolls, as the tech industry takes over autonomous car design:
http://www.fosspatents.com/201...
Are we going to see a convergence, where tech companies and auto companies team up, or a divergence, where tech companies produce the new vehicles and legacy car companies shrink into irrelevance?
The only thing I can predict with great confidence is that the cost for a replacement CPU board for a Tesla will be A Lot More than the cost of the constituent parts. (Nissan charged me $1500 for a truck wiring harness after mice chewed the insulation. It's really hard to believe that almost 6% of the cost of that truck was in the wiring harness.)
I was at the Global Foundries event and the keynote, no such thing was said. The Keynote recordings did not say that either, Tesla was mentioned as an example but the article is badly off base, so badly that it seems intentional. I checked with the speakers in question, other journalists, and the PR people at the show, ALL confirmed the story was not true and what was claimed to have been said was not.
-Charlie
For AI/machine learning the parts are rather specialized. For example, look at Google's tensor processing unit (TPU). Machine learning typically involves a lot of large integer matrix multiply operations where dedicated hardware makes a big difference in performance.
For example, Google's TPU consists of 64K 8-bit multipliers in a 256x256 array along with around 4M adders. A general purpose CPU or even a GPU will not be nearly as optimal. Google's TPU performance per watt is around 83x as good as a CPU and 28x as good as a GPU.
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