Good questions. First, but answering your last question, my thesis is really just about proposing another way to quantify computational WORK. Currently, we use application-generic measures like Flops or application-specific measures like images/tokens processed. These definitions of work can then be normalized by unit time, energy, power, GHG emissions, water, etc, but my focus is on getting the numerator right (work) regardless of the denominator. I'm also only interested in application-generic measures of work.
You've got it exactly right that the amount ...
I've re-read your proposal and thought about it more. First, to answer your question, I think SRAM architectures fit into my proposal by accounting for the operations that are performed (just as in a von-Neumann machine). The only difference is the location, amount, and speed of memory. Ideal channel capacity and operational mutual information apply to any hardware that moves and processes data. An application most suited for SRAM architectures are slightly different than those for traditional architectures, but the performance accounting stays the same. T...
I would love to see a poem synthesizing your ideas from this post!
What are your next steps for this work? It seems like there are many options, but what are you two planning on prioritizing?
I also thought you might enjoy this poem I wrote about the growing issues with FLOP-based accounting (read it in a somewhat Dr. Seuss rhythm):
Isn’t it funny, the metric we flaunt?
A computer that’s better,
Faster!
More flop/s!
So what is a flop?
It’s a fine, funny thing.
Been around some years,
Well defined, so clean!
A flop is an op
On a float, not more
Than anything given
by (IEEE)-seven-five-four
You take sixty-four bits,
put them all in a line,
multiply, add them.
Flops divine!
And for 40 odd years,
This was stable and glad.
Then Dennard died,
And architects went mad!
To ...
I like this failure-mode analysis of computing performance modeling. I'm pretty ignorant about many of these topics, but I would like to add that, at least for measuring operational performance, I think mutual information and uncertainty reduction offer a more general solution. My thoughts are written up here and include comparison to historical US computing export control definitions of computing performance: https://arxiv.org/pdf/2508.05621
I look forward to seeing it. I'm not sure what that characterization would look like, but I personally would like to see a diagram/roadmap of computing from raw resource extraction through manufacturing as well as an organized list of computing architectures. It seems there are enough novel devices out there to warrant some categorization and listing.