In Danny Hillis' lecture on the architecture of the CM-5 [1], he talks about some of the historical motivation behind the CM-2 described in his thesis paper turned into a book "The Connection Machine" [2] which goes into some detail on the alpha, beta, and dot operators and the xapping data type (the book calls it a "xector") described in detail in this paper.

Years ago I attempted to take a stab at implementing this language on CUDA I called hillisp [3] but at the time Dynamic Parallelism didn't exist yet and my available hardware was pretty weak, but it was fun to learn more about CUDA which was relatively early technology at the time.

[1] https://www.youtube.com/watch?v=Ua-swPZTeX4

[2] https://www.amazon.com/Connection-Machine-Press-Artificial-I...

[3] https://github.com/michelp/hillisp

Some of these books are still around ih various forms, for example:

https://www.amazon.com/Handbook-Artificial-Intelligence-Avro...

https://mitpress.mit.edu/books/parallel-distributed-processi...

https://www.amazon.com/Neural-Massively-Parallel-Computers-B...

https://www.amazon.com/Connection-Machine-Press-Artificial-I...

https://www.amazon.com/Legged-Robots-Balance-Artificial-Inte...

https://www.amazon.com/Machines-That-Walk-Adaptive-Suspensio...

...and more.

Yes this article is very old, and really only scratches the surface of Hillis' genius and puts a business failure angle on it.

Here's a great video describing the architecture of the CM-5

https://youtu.be/Ua-swPZTeX4

Note how similar the programming concepts are to CUDA (at an abstract level). Hillis also in the 80s published his MIT thesis as a book: The Connection Machine

https://www.amazon.com/Connection-Machine-Press-Artificial-I...

An incredibly well written and fascinating read, just as relevant today for programming a GPU as it was for programming the ancient beast of a CM-2. It's about algorithms, graphs, map/reduce, and other techniques of parallelism pioneered at Thinking Machines.

For example, Guy Blelloch worked at TM, and pioneered prefix scans on these machines, now common techniques used on GPUs.

https://www.youtube.com/watch?v=_5sM-4ODXaA

http://uenics.evansville.edu/~mr56/ece757/DataParallelAlgori...

There's also been a lot of hum lately on HN about APL, much of Hillis' *Lisp ideas come from parallelizing array processing primitives ("zectors" and "zappings"), ideas that originating in APL as he acknowledged in the paper describing the language:

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.108...

What's old is new... again.