GHDL Updated 2025-07-16
Examples under vhdl.
First install GHDL. On Ubuntu:
sudo apt install verilator
Tested on Verilator 1.0.0, Ubuntu 22.04.
Run all examples, which have assertions in them:
cd vhdl
./run
OurBigBook.com / Stack Exchange Updated 2025-07-16
Stack Exchange solves to a good extent the use cases:
points of view. It is a big open question if we can actually substantially improve it.
Major shortcoming are mentioned at idiotic Stack Overflow policies:
Because Ciro's a software engineer, and he's done enough staring in computers for a lifetime already, and he believes in the power of Git, he didn't pay much attention to this part ;-)
According to the eLife paper, the code appears to have been uploaded to: github.com/d-j-k/puntseq. TODO at least mention the key algorithms used more precisely.
Ciro can however see that it does present interesting problems!
Because it was necessary to wait for 2 days to get our data, the workshop first reused sample data from previous collections done earlier in the year to illustrate the software.
First there is some signal processing/machine learning required to do the base calling, which is not trivial in the Oxford Nanopore, since neighbouring bases can affect the signal of each other. This is mostly handled by Oxford Nanopore itself, or by hardcore programmers in the field however.
After the base calling was done, the data was analyzed using computer programs that match the sequenced 16S sequences to a database of known sequenced species.
This is of course not just a simple direct string matching problem, since like any in experiment, the DNA reads have some errors, so the program has to find the best match even though it is not exact.
The PuntSeq team would later upload the data to well known open databases so that it will be preserved forever! When ready, a link to the data would be uploaded to: www.puntseq.co.uk/data
gitk Updated 2025-07-16
Figure 1.
gitk 2.34.1 running on Ubuntu 22.04 with a simple repository.
git rebase does not tell you that, and that sucks.
We only know which commit from the feature branch caused the problem.
Generally we can guess or it is not needed, but imerge does look promising: stackoverflow.com/questions/18162930/how-can-i-find-out-which-git-commits-cause-conflicts
Git tips / git log --graph Updated 2025-07-16
For the strong.
git log --abbrev-commit --decorate --graph --pretty=oneline master HEAD
Output:
* b4ec057 (master) 5
* 0b37c1b 4
| * fbfbfe8 (HEAD -> my-feature) 7
| * 7b0f59d 6
|/
* 661cfab 3
* 6d748a9 2
* c5f8a2c 1
If we also add the --simplify-by-decoration, which you very often want want on a real repository with many commits:
* b4ec057 (master) 5
| * fbfbfe8 (HEAD -> my-feature) 7
|/
* c5f8a2c 1
As we can see, this removes any commit that is neither:
  • under a branch or tag
  • at the intersection of too branches or tags
In order to solve conflicts, you just have to understand what commit you are trying to move where.
E.g. if from:
5 master
|
4 7 my-feature HEAD
| |
3 6
|/
2
|
1
we do:
git rebase master
what happens step by step is first 6 is moved on top of 5:
6on5 HEAD
|
5 master
|
4                 7 my-feature
|                 |
3                 6
|                 |
2-----------------+
|
1
and then 7 is moved on top of the new 6:
7on5 HEAD
|
6on5
|
5 master
|
4                 7 my-feature
|                 |
3                 6
|                 |
2-----------------+
|
1
All good? so OK, let's move the my-feature to the new 7:
7on5 my-feature HEAD
|
6on5
|
5 master
|
4
|
3
|
2
|
1
Generate a minimal test repo. You should get in the habit of doing this to test stuff out.
#!/usr/bin/env bash

mkdir git-tips
cd git-tips
git init

for i in 1 2 3 4 5; do
  echo $i > f
  git add f
  git commit -m $i
done

git checkout HEAD~2
git checkout -b my-feature

for i in 6 7; do
  echo $i > f
  git add f
  git commit -m $i
done
Glucose Updated 2025-07-16
The most important on in metabolism internals, everything else gets converted to it before being processed in the .
GNOME Chess Updated 2025-07-16
The user friendly Chess UI! Exactly what you would expect from a GNOME Project package. But also packs some punch via the Universal Chess Interface, e.g. Stockfish just works.
GNU Taler Updated 2025-07-16
Centralized system that still attempts some level of privacy.
In it, a central bank issue tokens that are stored offline in your cell phone, a bit like cash bank notes.
When you take those tokens, a corresponding amount gets removed from your bank account, a bit like cash bank notes.
When a transaction is made, tokens are put into a spent token list via central API, and cannot be double spent thereafter. The corresponding ammount is then added to the bank account of the receiver. This also means that offline transactions are not possible.
When emitting, the bank signs the token with their private key. When spending, the bank checks that signature.
How do we prevent the bank from logging which token goes to which user besides trusting that they are running the software we whink they are running? Notably, couldn't timing be used to identify that?
Godlike Updated 2025-07-16
This vocabulary likely entered Ciro Santilli's vernacular through playing Counter-Strike when he was a teenager.
Good film Updated 2025-07-16
Ermm, as of February 2021, I was able to update my 2FA app token with the password alone, it did not ask for the old 2FA.
So what's the fucking point of 2FA then? An attacker with my password would be able to login by doing that!
Is it that Google trusts that particular action because I used the same phone/known IP or something like that?
Google custom silicon Updated 2025-07-16
Google has put considerable effort into custom hardware to greatly optimize its stack, in a way that is quite notable compared to other tech companies.
The best Romance of the Three Kingdoms adaptation of all time? Mind blowing.
www.youtube.com/watch?v=e8VWVvHjskM&list=PLIj4BzSwQ-_ueXTO7EBmShk1b3lEqc5b_ official CCTV电视剧 (CCTV TV Series Channel) upload without Chinese + English subtitles.
Video 1.
Title sequence of the Romance of the Three Kingdoms (1994 TV series)
Source. From this you can understand that the number os extras is off the charts!
PuntSeq is a side project led by a few University of Cambridge PhDs that aims to determine which bacteria are present in the River Cam.
In July 2019, the PuntSeq team got together with the awesome Cambridge Biomakespace, an awesome biology makerspace open to all, to create a two day science outreach activity showing their procedures.
The data collected in this experiment, together with other collection sessions done by the organizers actually led to a publication on eLife: elifesciences.org/articles/61504 "Freshwater monitoring by nanopore sequencing" by Lara Urban et al. (2021), so it is awesome to see that were are actual being part of "real science".
Ciro knows nothing about biology, but since he is very curious about it, he jumped at this opportunity, and decided to document things as well as his limited knowledge would allow.
All participants chipped in some money to help cover the experiment's costs. Ciro suspects that this activity was done partially to help crowdfund the experiment, but it was a worthy investment!
The impressions you get from the experiment as a software engineer will be:
  • OMG, this is so labour intensive, why haven't they automated this
  • OMG, this is frightening, all the 8 hours of work I've just done are present in that tiny plastic tube
  • Amazing! Look at that apparatus! And the bio people are like: I've used this a million times, it's cheap and every lab has one, just work faster and don't break you piece of junk!

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