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czl t1_jdq094y wrote

So this is like making software programmers more productive by giving them faster tools like compilers so there is less waiting time?

However once the design is done and tested and chips are being "printed" (?) this speed up does not help with that?

Asking because I want to know how this innovation will impact the production capacity of existing fabs.

The impact will be better designs due to more design productivity but actual production capacity does not change, yes?

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GPUoverlord t1_jdqgc9a wrote

You wanna become a computer scientist?

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czl t1_jdqk4ts wrote

> You wanna become a computer scientist?

I want to understand this discovery and its impact on capacity of chip production. The article describes the discovery as better parallelism (for “existing”?) algorithms so as to better use NVIDIA’s GPUs.

I wonder what the nature of these inverse lithography algorithms is. A domain specific numerical optimization problem? Why would that be hard to parallelize? Perhaps till now nobody translated the problem to efficiently use the NVIDIA CUDA API?

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GPUoverlord t1_jdqkw3m wrote

The teams of scientists that made these programs don’t fully understand how they work

This is an entire new field of science

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czl t1_jdqsyqt wrote

> The teams of scientists that made these programs don’t fully understand how they work. This is an entire new field of science

Yes it would not surprise me if teams of scientists that made these programs don’t fully understand how they work. Nearly always your “understanding” stops at some abstraction level below which others take over.

Making pencils is not exactly cutting edge technology yet somewhere I read that likely nobody understand all that is necessary to make an ordinary pencil if starting with nothing manufactured. Our technology builds on our technology builds on our technology …

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