47 karma · joined June 12, 2023
It was a complete pain in the ass. You were constantly future-proofing your data structures because you knew you were going to be stuck with them for all eternity because the I/O framework was going to serialize them verbatim whether you liked it or not. Those were dark days...
https://arstechnica.com/science/2023/06/nanograv-picks-up-si...
The number of significant digits is identical for (nearly) the entire range of FP values. There's no value to keeping it "near 1" for IEEE 754 floats - the precision is exactly the same regardless whether near 1 or near 1 trillion. This makes them ideal for general computation and modeling physical properties.
In contrast, posits, the unum alternative to IEEE 754, are highly sensitive to absolute scale. Posits lose precision as the magnitudes increase. Otoh, for small values, you get much higher precision which is why they getting some attention from the AI world where normalized weights are everywhere.
100x throughput improvement might just come from caching results from earlier computations (less naive) - at the cost of 10x memory footprint possibly (different priorities).