Lots Of Questions On Google's 'Trillium' TPU V6, A Few Answers
The Next Platform, Monday, June 10th, 2024
It has been more than a decade since Google figured out that it needed to control its own hardware fate when it came to the tensor processing that was going to be required to support machine learning algorithms.
A few weeks ago, at its annual I/O event, Google announced its sixth generation Tensor Processing Units, or TPUs, and there are still more questions than answers about them at this point.
This is fine, since we don't expect Hypercomputer systems to be installed by Google using the TPU v6 devices until the fourth quarter of this year. But we are impatient observers of compute engine and system architecture, and have thus tried to figure out what the salient characteristics of these TPU v6 engines and how they might stack up in terms of bang for the buck compared to prior TPU generations. So, we have taken a first stab at a comparative analysis across the TPU line, which spans from the TPU v1, which was first deployed in 2015, and across eight distinct TPU devices including the new TPU v6.