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Not a lot of information about the chips yet. About 100B transistors in the AI chip. For comparison, an RTX 4090 has 76B, and an H100 has about 80B. So the Maia

Not a lot of information about the chips yet. About 100B transistors in the AI chip. For comparison, an RTX 4090 has 76B, and an H100 has about 80B. So the Maia chip is pretty massive.

hulitu 3y ago
This is like performance review based on written line of code.
- Slartie 3y ago
  GPUs (and AI chips) are highly parallel, containing thousands upon thousands of the same compute units. The performance of these chips is very much dependent on having a sheer number of transistors to form into as many compute units as possible. If we assume that Microsoft is roughly able to architect compute units of a similar performance-to-number-of-transistors ratio as nVidia is, then having twice the number of transistors should roughly result in twice the performance. That is very different than it is with typical software. If you give a programmer who needs to write 100 lines of code to solve a given problem 100 more lines to fill, he won't simply be able to copy-paste his 100 lines another time and by that action be twice as fast at solving whatever problem you tasked him with. With GPU compute units, such copy-pasting of compute units is exactly what's being done (at least until you hit the limits of other resources such as management units, memory bandwidth etc.).
- kergonath 3y ago
  They did not mention performance, just size.
- pseudosavant 3y ago
  In a way, it is the opposite. Code is what you execute. The transistors are the engines that do the execution. They are going to expect a chip they designed with 105B transistors to perform (speed/efficiency/whatever) in the same ballpark as a high=end GPU for their AI workloads. It is like knowing the kind of engine a car has. Not all V8 gas engines produce the same power, but knowing that it is a V8 instead of an inline three cylinder does give you an idea of the expected performance characteristics.
  - c0pium 3y ago
    > It is like knowing the kind of engine a car has. In a way you’re right, neither tells you anything about performance. An sf90 has a v8. So does an 83 mustang, and it even has 25% higher displacement! So clearly the 2023 Ferrari is basically a fastback mustang…

Not a lot of information about the chips yet. About 100B transistors in the AI chip. For comparison, an RTX 4090 has 76B, and an H100 has about 80B. So the Maia chip is pretty massive.

hulitu 3y ago

This is like performance review based on written line of code.

Slartie 3y ago
GPUs (and AI chips) are highly parallel, containing thousands upon thousands of the same compute units. The performance of these chips is very much dependent on having a sheer number of transistors to form into as many compute units as possible. If we assume that Microsoft is roughly able to architect compute units of a similar performance-to-number-of-transistors ratio as nVidia is, then having twice the number of transistors should roughly result in twice the performance. That is very different than it is with typical software. If you give a programmer who needs to write 100 lines of code to solve a given problem 100 more lines to fill, he won't simply be able to copy-paste his 100 lines another time and by that action be twice as fast at solving whatever problem you tasked him with. With GPU compute units, such copy-pasting of compute units is exactly what's being done (at least until you hit the limits of other resources such as management units, memory bandwidth etc.).
kergonath 3y ago
They did not mention performance, just size.
pseudosavant 3y ago
In a way, it is the opposite. Code is what you execute. The transistors are the engines that do the execution. They are going to expect a chip they designed with 105B transistors to perform (speed/efficiency/whatever) in the same ballpark as a high=end GPU for their AI workloads. It is like knowing the kind of engine a car has. Not all V8 gas engines produce the same power, but knowing that it is a V8 instead of an inline three cylinder does give you an idea of the expected performance characteristics.
- c0pium 3y ago
  > It is like knowing the kind of engine a car has. In a way you’re right, neither tells you anything about performance. An sf90 has a v8. So does an 83 mustang, and it even has 25% higher displacement! So clearly the 2023 Ferrari is basically a fastback mustang…