mersenneforum.org  

Go Back   mersenneforum.org > Great Internet Mersenne Prime Search > Hardware

Reply
 
Thread Tools
Old 2022-11-13, 09:07   #1
preda
 
preda's Avatar
 
"Mihai Preda"
Apr 2015

22×192 Posts
Default Google open-source silicone manufacturing

According to https://www.phoronix.com/news/Google-GloFo-Sponsored-Si
Google is covering the cost of initial production of some open-source silicone projects.

Could we produce a design for specialized HW that would be useful for our project? i.e. that would be faster, more efficient, and/or cheaper than GPUs.

We should probably start with something as simple as possible initially, and iterate from there.
preda is offline   Reply With Quote
Old 2022-11-13, 09:14   #2
retina
Undefined
 
retina's Avatar
 
"The unspeakable one"
Jun 2006
My evil lair

11010000111012 Posts
Default

Quote:
Originally Posted by preda View Post
... silicone projects.
Google now pays for our breast implants.
retina is online now   Reply With Quote
Old 2022-11-13, 10:19   #3
LaurV
Romulan Interpreter
 
LaurV's Avatar
 
"name field"
Jun 2011
Thailand

3×23×149 Posts
Default

yeah, and you have to pay for my keyboard now, in case it gets damaged from the spilled coffee!
you could notify me before!

Joking apart, how about a 96 bits modular multiplier? (I think 128 bits is a bit more complicate?)
Or full modular exponentiator?
One register to hold the modulus, few more to hold the operands and a lot of VHDL... (for who knows it...)
I would buy such a chip if the price/performance worth.
I may also partially sponsor the initial hardware (FPGA, tools) if anybody convinces me that (s)he is skilled enough to do it.

Last fiddled with by LaurV on 2022-11-13 at 10:26 Reason: tyops
LaurV is offline   Reply With Quote
Old 2022-11-13, 10:30   #4
kriesel
 
kriesel's Avatar
 
"TF79LL86GIMPS96gpu17"
Mar 2017
US midwest

11100110001102 Posts
Default

Power efficiency and throughput would be poor. It's on 180nm process tech, a far cry from 10nm or 7nm used in recent CPUs or GPUs, or even some rather old hardware. Core 2 (2006-2012) was 65 nm to 45 nm. https://en.wikipedia.org/wiki/Intel_Core_2
kriesel is offline   Reply With Quote
Old 2022-11-13, 11:38   #5
LaurV
Romulan Interpreter
 
LaurV's Avatar
 
"name field"
Jun 2011
Thailand

3×23×149 Posts
Default

Not necessary. All Cortex M (like STM32Fxxxx) are 180nm, and they only switched to 90nm for the newer (G and C) series. And you get 480MHz clocks, 32 bits ARM (general processing), and 80uA/MHz power burning. ASICs for mining are other example.

Don't confuse general (x86) processors with dedicated, simple toys. We don't need (and not able to make, most probably) complex thingies like a CPU. We can start simple, make a modular multiplier, that can be tested in some FPGA and duplicated, put hundreds of them in a virtex, and kill few TF ranges. Then step-up, making an exponentiator. It will help a lot with TF, and we can get a lot of experience.

Then we see...

(small steps)

Last fiddled with by LaurV on 2022-11-13 at 11:39
LaurV is offline   Reply With Quote
Old 2022-11-13, 13:50   #6
xilman
Bamboozled!
 
xilman's Avatar
 
"๐’‰บ๐’ŒŒ๐’‡ท๐’†ท๐’€ญ"
May 2003
Down not across

101101100010112 Posts
Default

Suggestion: an ALU which uses RNS rather than classical multiple precision, where RNS is the Residue Number System.

Addition, subtraction and multiplication are inherently carry-free and so trivially parallizable. In particular, multiplication runs in time O(n).
Modular multiplication can be implemented in Montgomery arithmetic, though it does require O(n2) time.

Division and comparison (other than testing for equality) are tricky and detecting overflow is almost impossible.

Instructions for converting between RNS and conventional MP representations would also be necessary. Division, for instance, could be done on the cpu rather than on the co-processor.
xilman is offline   Reply With Quote
Old 2022-12-05, 23:34   #7
Gordon
 
Gordon's Avatar
 
Nov 2008

509 Posts
Default

Quote:
Originally Posted by preda View Post
According to https://www.phoronix.com/news/Google-GloFo-Sponsored-Si
Google is covering the cost of initial production of some open-source silicone projects.

Could we produce a design for specialized HW that would be useful for our project? i.e. that would be faster, more efficient, and/or cheaper than GPUs.

We should probably start with something as simple as possible initially, and iterate from there.
Bit late to the party, but I'd like to mfaktc as a custom chip...
Gordon is offline   Reply With Quote
Old 2022-12-11, 19:38   #8
28add11
 
28add11's Avatar
 
"Nicholas"
Dec 2022
Alberta, Canada

610 Posts
Default

This sounds like it could have good potential. The only question is if anyone wants to learn Verilog/VHDL !
It might be good to start practicing on some cheap FPGAs before we get into the weeds of things. I'm fairly new to the project and the math so I don't know what should be focused on but this does sound really interesting.
28add11 is offline   Reply With Quote
Reply

Thread Tools


Similar Threads
Thread Thread Starter Forum Replies Last Post
Nvidia transitioning to open source Linux GPU kernel driver M344587487 GPU Computing 4 2022-05-25 09:32
Closed vs open source observatory drivers chalsall Astronomy 2 2022-05-24 20:25
Strongest chesscomputer of the world (open source) NormanRKN Chess 4 2021-01-05 01:36
Open source chip design henryzz Hardware 12 2020-07-06 12:46
DRM, the end of open source, "grass roots", and creativity? E_tron Soap Box 1 2005-08-18 09:45

All times are UTC. The time now is 20:53.


Fri Feb 3 20:53:19 UTC 2023 up 169 days, 18:21, 1 user, load averages: 1.23, 1.19, 1.12

Powered by vBulletin® Version 3.8.11
Copyright ©2000 - 2023, Jelsoft Enterprises Ltd.

This forum has received and complied with 0 (zero) government requests for information.

Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation.
A copy of the license is included in the FAQ.

โ‰  ยฑ โˆ“ รท ร— ยท โˆ’ โˆš โ€ฐ โŠ— โŠ• โŠ– โŠ˜ โŠ™ โ‰ค โ‰ฅ โ‰ฆ โ‰ง โ‰จ โ‰ฉ โ‰บ โ‰ป โ‰ผ โ‰ฝ โŠ โŠ โŠ‘ โŠ’ ยฒ ยณ ยฐ
โˆ  โˆŸ ยฐ โ‰… ~ โ€– โŸ‚ โซ›
โ‰ก โ‰œ โ‰ˆ โˆ โˆž โ‰ช โ‰ซ โŒŠโŒ‹ โŒˆโŒ‰ โˆ˜ โˆ โˆ โˆ‘ โˆง โˆจ โˆฉ โˆช โจ€ โŠ• โŠ— ๐–• ๐–– ๐–— โŠฒ โŠณ
โˆ… โˆ– โˆ โ†ฆ โ†ฃ โˆฉ โˆช โŠ† โŠ‚ โŠ„ โŠŠ โŠ‡ โŠƒ โŠ… โŠ‹ โŠ– โˆˆ โˆ‰ โˆ‹ โˆŒ โ„• โ„ค โ„š โ„ โ„‚ โ„ต โ„ถ โ„ท โ„ธ ๐“Ÿ
ยฌ โˆจ โˆง โŠ• โ†’ โ† โ‡’ โ‡ โ‡” โˆ€ โˆƒ โˆ„ โˆด โˆต โŠค โŠฅ โŠข โŠจ โซค โŠฃ โ€ฆ โ‹ฏ โ‹ฎ โ‹ฐ โ‹ฑ
โˆซ โˆฌ โˆญ โˆฎ โˆฏ โˆฐ โˆ‡ โˆ† ฮด โˆ‚ โ„ฑ โ„’ โ„“
๐›ข๐›ผ ๐›ฃ๐›ฝ ๐›ค๐›พ ๐›ฅ๐›ฟ ๐›ฆ๐œ€๐œ– ๐›ง๐œ ๐›จ๐œ‚ ๐›ฉ๐œƒ๐œ— ๐›ช๐œ„ ๐›ซ๐œ… ๐›ฌ๐œ† ๐›ญ๐œ‡ ๐›ฎ๐œˆ ๐›ฏ๐œ‰ ๐›ฐ๐œŠ ๐›ฑ๐œ‹ ๐›ฒ๐œŒ ๐›ด๐œŽ๐œ ๐›ต๐œ ๐›ถ๐œ ๐›ท๐œ™๐œ‘ ๐›ธ๐œ’ ๐›น๐œ“ ๐›บ๐œ”