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December 2023: www.tudogostoso.com.br/receita/81176-gelatina-de-abacaxi-com-creme-de-leite.html Terribly explained recipe! Used 5 spoons of sugar rather than 10, and a 300ml cup of double cream. Turned out OK, except that the cream condensed all on top, and assumed the same coarse texture as when you do a fatty beef and let it cool, so not so nice,
Maybe this would be more successful: receitas.globo.com/tipos-de-prato/doces-e-sobremesas/gelatina-de-abacaxi-4e64345bddf17214b4003e71.ghtml They also use condensed milk, and beat the cream with the jelly, so it might mix better? It didn't really.
These come with pre-installed drivers, so e.g. nvidia-smi just works on them out of the box, tested on g5.xlarge which has an Nvidia A10G GPU. Good choice as a starting point for deep learning experiments.
However it did not happen on Lenovo ThinkPad P51 (2017) also on Ubuntu 23.10 which had been upgraded several times from God knows what starting point... At first one had X11 (forced by Nvidia drivers) and the other Wayland, but moving to p14s X11 changed nothing.
Both were running GNOME Display Manager.
Same happens with Super + L, but also CLI commands: askubuntu.com/questions/7776/how-do-i-lock-the-desktop-screen-via-command-line
Bibliography:
- askubuntu.com/questions/1242110/after-upgrading-to-ubuntu-20-04-lockscreen-not-working canon
- askubuntu.com/questions/1246622/ubuntu-20-04-unable-to-lock-screen
- askubuntu.com/questions/1245071/cant-lock-screen-with-shortcut-on-ubuntu-20-04-gnome
- askubuntu.com/questions/1248756/super-l-not-working-on-ubuntu-20-04
Had this happen on P14s on Ubuntu 23.10 while causally using Chromium. The screen went blank for a few seconds, but it apparently managed to reboot itself, and things started working again, except that and most windows were killed:It appears to be a bug in the AMDGPU open source driver.
[drm:gfx_v11_0_priv_reg_irq [amdgpu]] *ERROR* Illegal register access in command stream
[drm:amdgpu_job_timedout [amdgpu]] *ERROR* ring gfx_0.0.0 timeout, signaled seq=5774109, emitted seq=5774111
[drm:amdgpu_job_timedout [amdgpu]] *ERROR* Process information: process chrome pid 14023 thread chrome:cs0 pid 14087
amdgpu 0000:64:00.0: amdgpu: GPU reset begin!
[drm:mes_v11_0_submit_pkt_and_poll_completion.constprop.0 [amdgpu]] *ERROR* MES failed to response msg=3
[drm:amdgpu_mes_unmap_legacy_queue [amdgpu]] *ERROR* failed to unmap legacy queue
[drm:mes_v11_0_submit_pkt_and_poll_completion.constprop.0 [amdgpu]] *ERROR* MES failed to response msg=3
[drm:amdgpu_mes_unmap_legacy_queue [amdgpu]] *ERROR* failed to unmap legacy queue
[drm:mes_v11_0_submit_pkt_and_poll_completion.constprop.0 [amdgpu]] *ERROR* MES failed to response msg=3
[drm:amdgpu_mes_unmap_legacy_queue [amdgpu]] *ERROR* failed to unmap legacy queue
[drm:mes_v11_0_submit_pkt_and_poll_completion.constprop.0 [amdgpu]] *ERROR* MES failed to response msg=3
[drm:amdgpu_mes_unmap_legacy_queue [amdgpu]] *ERROR* failed to unmap legacy queue
[drm:mes_v11_0_submit_pkt_and_poll_completion.constprop.0 [amdgpu]] *ERROR* MES failed to response msg=3
[drm:amdgpu_mes_unmap_legacy_queue [amdgpu]] *ERROR* failed to unmap legacy queue
[drm:mes_v11_0_submit_pkt_and_poll_completion.constprop.0 [amdgpu]] *ERROR* MES failed to response msg=3
[drm:amdgpu_mes_unmap_legacy_queue [amdgpu]] *ERROR* failed to unmap legacy queue
[drm:mes_v11_0_submit_pkt_and_poll_completion.constprop.0 [amdgpu]] *ERROR* MES failed to response msg=3
[drm:amdgpu_mes_unmap_legacy_queue [amdgpu]] *ERROR* failed to unmap legacy queue
[drm:mes_v11_0_submit_pkt_and_poll_completion.constprop.0 [amdgpu]] *ERROR* MES failed to response msg=3
[drm:amdgpu_mes_unmap_legacy_queue [amdgpu]] *ERROR* failed to unmap legacy queue
[drm:mes_v11_0_submit_pkt_and_poll_completion.constprop.0 [amdgpu]] *ERROR* MES failed to response msg=3
[drm:amdgpu_mes_unmap_legacy_queue [amdgpu]] *ERROR* failed to unmap legacy queue
[drm:gfx_v11_0_cp_gfx_enable.isra.0 [amdgpu]] *ERROR* failed to halt cp gfx
Dec 27 15:03:38 ciro-p14s kernel: amdgpu 0000:64:00.0: amdgpu: MODE2 reset
Dec 27 15:03:38 ciro-p14s kernel: amdgpu 0000:64:00.0: amdgpu: GPU reset succeeded, trying to resume
Dec 27 15:03:38 ciro-p14s kernel: [drm] PCIE GART of 512M enabled (table at 0x0000008000900Related reports:
I think this was on Wayland. Possibly relatd but on X Window System, crashed the UI, showed message "oh no! Something has gone wrong."
2024-01-13_21-55-07@ciro@ciro-p14s$ cat /var/log/apport.log
ERROR: apport (pid 975172) 2024-01-13 21:41:02,087: host pid 3528 crashed in a separate mount namespace, ignoring
INFO: apport (pid 975227) 2024-01-13 21:41:02,398: called for pid 2728, signal 5, core limit 0, dump mode 1
INFO: apport (pid 975227) 2024-01-13 21:41:02,401: executable: /usr/bin/gnome-shell (command line "/usr/bin/gnome-shell")
INFO: apport (pid 975227) 2024-01-13 21:41:12,667: wrote report /var/crash/_usr_bin_gnome-shell.1000.crashMentioned e.g. at: videocardz.com/newz/amd-begins-rdna3-gfx11-graphics-architecture-enablement-for-llvm-project as being part of RDNA 3.
You get an error like this if you forget to call Related: quantumcomputing.stackexchange.com/questions/34396/aererror-unknown-instruction-c-unitary-while-using-control-unitary-operator/35132#35132
qiskit.transpile():qiskit_aer.aererror.AerError: 'unknown instruction: QFT'Ollama is a highly automated open source wrapper that makes it very easy to run multiple Open weight LLM models either on CPU or GPU.
Its README alone is of great value, serving as a fantastic list of the most popular Open weight LLM models in existence.
Install with:
curl https://ollama.ai/install.sh | shOn P14s it runs on CPU and generates a few tokens per second, which is quite usable for a quick interactive play.
As mentioned at github.com/jmorganca/ollama/blob/0174665d0e7dcdd8c60390ab2dd07155ef84eb3f/docs/faq.md the downloads to under The file:gives a the exact model name and parameters.
/usr/share/ollama/.ollama/models/ and ncdu tells me:--- /usr/share/ollama ----------------------------------
3.6 GiB [###########################] /.ollama
4.0 KiB [ ] .bashrc
4.0 KiB [ ] .profile
4.0 KiB [ ] .bash_logout/usr/share/ollama/.ollama/models/manifests/hf.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated-GGUF/Q2_KWe can also do it non-interactively with:which gave me:but note that there is a random seed that affects each run by default. ollama-expect is an attempt to make the output deterministic.
/bin/time ollama run llama2 'What is quantum field theory?'0.13user 0.17system 2:06.32elapsed 0%CPU (0avgtext+0avgdata 17280maxresident)k
0inputs+0outputs (0major+2203minor)pagefaults 0swapsSome other quick benchmarks from Amazon EC2 GPU on a g4nd.xlarge instance which had an Nvidia Tesla T4:and on Nvidia A10G in an g5.xlarge instance:
0.07user 0.05system 0:16.91elapsed 0%CPU (0avgtext+0avgdata 16896maxresident)k
0inputs+0outputs (0major+1960minor)pagefaults 0swaps0.03user 0.05system 0:09.59elapsed 0%CPU (0avgtext+0avgdata 17312maxresident)k
8inputs+0outputs (1major+1934minor)pagefaults 0swapsIt tends to babble quite a lot by default, but eventually decides to stop.
Mentioned at: aws.amazon.com/ec2/instance-types/g4/
TODO meaning of "nd"? "n" presumably means Nvidia, but what is the "d"? Compare it g4ad.xlarge which has AMD GPUs. aws.amazon.com/ec2/instance-types/g4/ mentions:
They have a tutorial at: jena.apache.org/tutorials/sparql.html
Once you've done the Apache Jena CLI tools setup we can query all users with Full Name (FN) "John Smith" directly fom the rdf/vcard.ttl Turtle RDF file with the rdf/vcard.rq SPARQL query:and that outputs:
sparql --data=rdf/vcard.ttl --query=rdf/vcard.rq---------------------------------
| x |
=================================
| <http://somewhere/JohnSmith/> |
---------------------------------The CLI tools don't appear to be packaged for Ubuntu 23.10? Annoying... There is a package
libapache-jena-java but it doesn't contain any binaries, only Java library files.To run the CLI tools easily we can download the prebuilt:and we can confirm it works with:which outputs:
sudo apt install openjdk-22-jre
wget https://dlcdn.apache.org/jena/binaries/apache-jena-4.10.0.zip
unzip apache-jena-4.10.0.zip
cd apache-jena-4.10.0
export JENA_HOME="$(pwd)"
export PATH="$PATH:$(pwd)/bin"sparql -versionApache Jena version 4.10.0If your Java is too old then then running
sparql with the prebuilts fails with:Error: A JNI error has occurred, please check your installation and try again
Exception in thread "main" java.lang.UnsupportedClassVersionError: arq/sparql has been compiled by a more recent version of the Java Runtime (class file version 55.0), this version of the Java Runtime only recognizes class file versions up to 52.0
at java.lang.ClassLoader.defineClass1(Native Method)
at java.lang.ClassLoader.defineClass(ClassLoader.java:756)
at java.security.SecureClassLoader.defineClass(SecureClassLoader.java:142)
at java.net.URLClassLoader.defineClass(URLClassLoader.java:473)
at java.net.URLClassLoader.access$100(URLClassLoader.java:74)
at java.net.URLClassLoader$1.run(URLClassLoader.java:369)
at java.net.URLClassLoader$1.run(URLClassLoader.java:363)
at java.security.AccessController.doPrivileged(Native Method)
at java.net.URLClassLoader.findClass(URLClassLoader.java:362)
at java.lang.ClassLoader.loadClass(ClassLoader.java:418)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:352)
at java.lang.ClassLoader.loadClass(ClassLoader.java:351)
at sun.launcher.LauncherHelper.checkAndLoadMain(LauncherHelper.java:621)Build from source is likely something like:TODO test it.
sudo apt install maven openjdk-22-jdk
git clone https://github.com/apache/jena --branch jena-4.10.0 --depth 1
cd jena
mvn clean installIf you make the mistake of trying to run the source tree without build:it fails with:as per: users.jena.apache.narkive.com/T5TaEszT/sparql-tutorial-querying-datasets-error-unrecognized-option-graph
git clone https://github.com/apache/jena --branch jena-4.10.0 --depth 1
cd jena
export JENA_HOME="$(pwd)"
export PATH="$PATH:$(pwd)/apache-jena/bin"Error: Could not find or load main class arq.sparqlAs of December 2023, the cheapest instance with an Nvidia GPU is g4nd.xlarge, so let's try that out. In that instance, lspci contains:so we see that it runs a Nvidia T4 GPU.
00:1e.0 3D controller: NVIDIA Corporation TU104GL [Tesla T4] (rev a1)Be careful not to confuse it with g4ad.xlarge, which has an AMD GPU instead. TODO meaning of "ad"? "a" presumably means AMD, but what is the "d"?
Some documentation on which GPU is in each instance can seen at: docs.aws.amazon.com/dlami/latest/devguide/gpu.html (archive) with a list of which GPUs they have at that random point in time. Can the GPU ever change for a given instance name? Likely not. Also as of December 2023 the list is already outdated, e.g. P5 is now shown, though it is mentioned at: aws.amazon.com/ec2/instance-types/p5/
When selecting the instance to launch, the GPU does not show anywhere apparently on the instance information page, it is so bad!
Also note that this instance has 4 vCPUs, so on a new account you must first make a customer support request to Amazon to increase your limit from the default of 0 to 4, see also: stackoverflow.com/questions/68347900/you-have-requested-more-vcpu-capacity-than-your-current-vcpu-limit-of-0, otherwise instance launch will fail with:
You have requested more vCPU capacity than your current vCPU limit of 0 allows for the instance bucket that the specified instance type belongs to. Please visit aws.amazon.com/contact-us/ec2-request to request an adjustment to this limit.
When starting up the instance, also select:Once you finally managed to SSH into the instance, first we have to install drivers and reboot:and now running:shows something like:
- image: Ubuntu 22.04
- storage size: 30 GB (maximum free tier allowance)
sudo apt update
sudo apt install nvidia-driver-510 nvidia-utils-510 nvidia-cuda-toolkit
sudo rebootnvidia-smi+-----------------------------------------------------------------------------+
| NVIDIA-SMI 525.147.05 Driver Version: 525.147.05 CUDA Version: 12.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 Tesla T4 Off | 00000000:00:1E.0 Off | 0 |
| N/A 25C P8 12W / 70W | 2MiB / 15360MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+If we start from the raw Ubuntu 22.04, first we have to install drivers:
- docs.aws.amazon.com/AWSEC2/latest/UserGuide/install-nvidia-driver.html official docs
- stackoverflow.com/questions/63689325/how-to-activate-the-use-of-a-gpu-on-aws-ec2-instance
- askubuntu.com/questions/1109662/how-do-i-install-cuda-on-an-ec2-ubuntu-18-04-instance
- askubuntu.com/questions/1397934/how-to-install-nvidia-cuda-driver-on-aws-ec2-instance
From there basically everything should just work as normal. E.g. we were able to run a CUDA hello world just fine along:
nvcc inc.cu
./a.outOne issue with this setup, besides the time it takes to setup, is that you might also have to pay some network charges as it downloads a bunch of stuff into the instance. We should try out some of the pre-built images. But it is also good to know this pristine setup just in case.
We then managed to run Ollama just fine with:which gave:so way faster than on my local desktop CPU, hurray.
curl https://ollama.ai/install.sh | sh
/bin/time ollama run llama2 'What is quantum field theory?'0.07user 0.05system 0:16.91elapsed 0%CPU (0avgtext+0avgdata 16896maxresident)k
0inputs+0outputs (0major+1960minor)pagefaults 0swapsAfter setup from: askubuntu.com/a/1309774/52975 we were able to run:which gave:so only marginally better than on P14s. It would be fun to see how much faster we could make things on a more powerful GPU.
head -n1000 pap.txt | ARGOS_DEVICE_TYPE=cuda time argos-translate --from-lang en --to-lang fr > pap-fr.txt77.95user 2.87system 0:39.93elapsed 202%CPU (0avgtext+0avgdata 4345988maxresident)k
0inputs+88outputs (0major+910748minor)pagefaults 0swaps Pinned article: Introduction to the OurBigBook Project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
Intro to OurBigBook
. Source. We have two killer features:
- topics: topics group articles by different users with the same title, e.g. here is the topic for the "Fundamental Theorem of Calculus" ourbigbook.com/go/topic/fundamental-theorem-of-calculusArticles of different users are sorted by upvote within each article page. This feature is a bit like:
- a Wikipedia where each user can have their own version of each article
- a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
Figure 1. Screenshot of the "Derivative" topic page. View it live at: ourbigbook.com/go/topic/derivativeVideo 2. OurBigBook Web topics demo. Source. - local editing: you can store all your personal knowledge base content locally in a plaintext markup format that can be edited locally and published either:This way you can be sure that even if OurBigBook.com were to go down one day (which we have no plans to do as it is quite cheap to host!), your content will still be perfectly readable as a static site.
- to OurBigBook.com to get awesome multi-user features like topics and likes
- as HTML files to a static website, which you can host yourself for free on many external providers like GitHub Pages, and remain in full control
Figure 2. You can publish local OurBigBook lightweight markup files to either OurBigBook.com or as a static website.
Figure 3. Visual Studio Code extension installation.
Figure 5. . You can also edit articles on the Web editor without installing anything locally. Video 3. Edit locally and publish demo. Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension. 
- Infinitely deep tables of contents:
All our software is open source and hosted at: github.com/ourbigbook/ourbigbook
Further documentation can be found at: docs.ourbigbook.com
Feel free to reach our to us for any help or suggestions: docs.ourbigbook.com/#contact