131–140 of 193 posts
The RPi, unlike the Cray-1, does not offer ample sitting space.
yeah, the pi cases have been disappointing. Few have adequate cooling. (flirc is good, the ones with fans are just annoying) I'd love to have a pi case that had a built-in breadboard. ...or a case with comfortable seating.
I'm waiting for the follow-up from Jeff Geerling where he fits a Raspberry Pi into a Cray-1 enclosure.
I'm waiting for the follow-up from Jeff Geerling where he fits a Raspberry Pi into a Cray-1 enclosure.
I would totally love a Cray1 shaped PC enclosure. A even smaller one for Raspberry Pis would also be cool.
When I see comparisons like this, the first thought I have is not the benchmarks, but rather what the most “heroic” real-world calculation of the day would have been on something like the Cray-1, and how to replicate those calculations today on something like a RPi. Weather/climate models? Rad-hydro? The fidelity would almost certainly be super low compared to modern FEA software, but it would be a fun exercise to tr…
nuclear weapons simulations the first machine went to Los Alamos https://www.theatlantic.com/technology/archive/2014/01/these...
These are incredibly expensive even on today’s hardware. If you look through some of the unclassified ASCI reports from the early 2000s, 3D calculations of this equation set were implied to be leadership-class computations. At the time of the Cray, it must’ve been coarse-grid 1D as the standard, with 2D as the dream.
When I see comparisons like this, the first thought I have is not the benchmarks, but rather what the most “heroic” real-world calculation of the day would have been on something like the Cray-1, and how to replicate those calculations today on something like a RPi. Weather/climate models? Rad-hydro? The fidelity would almost certainly be super low compared to modern FEA software, but it would be a fun exercise to tr…
One of the early customers was the European Centre for Medium-Range Weather Forecasts, so, wild guess, they probably used it for medium-range weather forecasts.
TL; DR: ten years ago, Raspberry Pis and Android phones were a handful times faster. Nowadays, they are around 100 times faster. Pretty impressive, considering they fit in our pockets.
Thank god they have a modern OS to slow them down. /s
It's wild to imagine that 40 or so years from now, someone will have a drawer full of cheap plastic boxes, each with more power than the fastest computing cluster of 2023... promising to themselves that one day they're finally going to build that hobby project with one of them.
You really think so? Aren’t we at the end of Moore’s law, so I’m really doubtful that we’ll see massive leaps like that.
Or when economics of fabricating such structures just aren't worth it.
The pi Pico would be an interesting comparison. It doesn't have an fpu, and not much ram so it might actually be a close race for some of these tests.
It's wild to imagine that 40 or so years from now, someone will have a drawer full of cheap plastic boxes, each with more power than the fastest computing cluster of 2023... promising to themselves that one day they're finally going to build that hobby project with one of them.
Didn’t the Apollo guidance computer, which took people to the moon, have 4K of RAM? Today, 1 million times that barely runs the OS and a few Chrome tabs.
Earlier quoted context omitted.
Those are largely simd but not vector.
How is vector different from simd?
With x86 SIMD the standard solution is to compile the same code multiple times for different SIMD widths (using different instructions) and then detect the CPU at runtime. Though that is such a pain that it's only really done in explicitly numerical libraries (Numpy, Eigen, etc.). In theory with Vector you can compile once, run anywhere.