Is one FP16 op equivalent to two INT8 ops?
That would put Google’s hypothetical figure of 50 FP16 teraops at 100 INT8 teraops.
Assuming Nvidia treats a “deep learning op” as an INT8 op, HW2 would have 10-12 INT8 teraops and if HW3 is 10x that, then it’s 100-120 INT8 teraops.
Intel/Mobileye wants to do 24 “deep learning” teraops with EyeQ5 in 2020.
Nvidia wants to 320 INT8 teraops with Pegasus (not sure when launching).
If all this is accurate (it might not be), we have:
- Mobileye EyeQ5: 24 DL teraops
- Google’s 2016 hypothetical: 100 INT8 teraops
- Tesla HW3: 100-120 DL/INT8 teraops (50-240 DL/INT8 teraops)
- Nvidia Pegasus: 320 INT8 teraops
Nvidia is also working on Orin, which is two Pegasuses, so 640 INT8 teraops total.
Not sure if Nvidia is getting these numbers from anywhere, or just going nuts?
“Pegasus is sufficient for a fully autonomous, Level 5 robotaxi... but now we’re gonna DOUBLE it!!”
When Nvidia announced AutoChauffeur with 24 DL teraops, it sure sounded to me like they were pitching it as a computer to power self-driving cars:
Nvidia still says on their website today that AutoChauffeur is supposed to be for “point-to-point travel”. I also found some
old Nvidia PowerPoint slides where the subheading was “AutoChauffeur & Fully Autonomous”. Confusing marketing at the very least.
Is Nvidia backpedaling, or has there been a consistent narrative all along?