Ciro Santilli @cirosantilli  40

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gfx1103 Updated 2025-07-16

Mentioned e.g. at: videocardz.com/newz/amd-begins-rdna3-gfx11-graphics-architecture-enablement-for-llvm-project as being part of RDNA 3.

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AerError: 'unknown instruction Updated 2025-07-16

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You get an error like this if you forget to call qiskit.transpile():

qiskit_aer.aererror.AerError: 'unknown instruction: QFT'

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Argos Translate Updated 2025-07-16

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OpenNMT CLI front-end.

Hello world: askubuntu.com/questions/380847/is-it-possible-to-translate-words-via-terminal/1309774#1309774

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Ollama Updated 2025-07-16

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github.com/jmorganca/ollama

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 | sh

The below was tested on Ollama 0.1.14 from December 2013.

Download llama2 7B and open a prompt:

ollama run llama2

On 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 /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

The file:

/usr/share/ollama/.ollama/models/manifests/hf.co/mlabonne/Meta-Llama-3.1-8B-Instruct-abliterated-GGUF/Q2_K

gives a the exact model name and parameters.

We can also do it non-interactively with:

/bin/time ollama run llama2 'What is quantum field theory?'

which gave me:

0.13user 0.17system 2:06.32elapsed 0%CPU (0avgtext+0avgdata 17280maxresident)k
0inputs+0outputs (0major+2203minor)pagefaults 0swaps

but note that there is a random seed that affects each run by default. ollama-expect is an attempt to make the output deterministic.

Some other quick benchmarks from Amazon EC2 GPU on a g4nd.xlarge instance which had an Nvidia Tesla T4:

0.07user 0.05system 0:16.91elapsed 0%CPU (0avgtext+0avgdata 16896maxresident)k
0inputs+0outputs (0major+1960minor)pagefaults 0swaps

and on Nvidia A10G in an g5.xlarge instance:

0.03user 0.05system 0:09.59elapsed 0%CPU (0avgtext+0avgdata 17312maxresident)k
8inputs+0outputs (1major+1934minor)pagefaults 0swaps

So it's not too bad, a small article in 10s.

It tends to babble quite a lot by default, but eventually decides to stop.

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GitHub book repo Updated 2025-07-16

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Some amazing people have put book source codes on GitHub. This is a list of such repos.

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g5.xlarge Updated 2025-07-16

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1 Nvidia A10G GPU, 4 vCPUs.

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g4nd.xlarge Updated 2025-07-16

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1 Nvidia T4 GPU, 4 vCPUs.

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:

G4 instances are available with a choice of NVIDIA GPUs (G4dn) or AMD GPUs (G4ad).

Price:

2025-03-10: 0.526 USD / Hour

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g4ad.xlarge Updated 2025-07-16

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AMD GPUs as mentioned at: aws.amazon.com/ec2/instance-types/g4/

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Jena SPARQL hello world Updated 2025-07-16

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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:

sparql --data=rdf/vcard.ttl --query=rdf/vcard.rq

and that outputs:

---------------------------------
| x                             |
=================================
| <http://somewhere/JohnSmith/> |
---------------------------------

Bibliography:

stackoverflow.com/questions/41959550/cli-tool-ala-csvsql-for-sparql-and-ttl-n3-files-hello-world-example-for

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Apache Jena CLI tools setup Updated 2025-07-16

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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:

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"

and we can confirm it works with:

sparql -version

which outputs:

Apache Jena version 4.10.0

If 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:

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 install

TODO test it.

If you make the mistake of trying to run the source tree without build:

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"

it fails with:

Error: Could not find or load main class arq.sparql

as per: users.jena.apache.narkive.com/T5TaEszT/sparql-tutorial-querying-datasets-error-unrecognized-option-graph

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List of AWS AMIs Updated 2025-07-16

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Laucnh Amazin EC2 with existing EBS volume Updated 2026-10-19

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Not possible directly without first creating an AMI image from snapshot? So annoying!

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Amazon EC2 GPU Updated 2025-07-16

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As of December 2023, the cheapest instance with an Nvidia GPU is g4nd.xlarge, so let's try that out. In that instance, lspci contains:

00:1e.0 3D controller: NVIDIA Corporation TU104GL [Tesla T4] (rev a1)

so we see that it runs a Nvidia T4 GPU.

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:

image: Ubuntu 22.04
storage size: 30 GB (maximum free tier allowance)

Once you finally managed to SSH into the instance, first we have to install drivers and reboot:

sudo apt update
sudo apt install nvidia-driver-510 nvidia-utils-510 nvidia-cuda-toolkit
sudo reboot

and now running:

nvidia-smi

shows something like:

+-----------------------------------------------------------------------------+
| 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:

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.out

One 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:

curl https://ollama.ai/install.sh | sh
/bin/time ollama run llama2 'What is quantum field theory?'

which gave:

0.07user 0.05system 0:16.91elapsed 0%CPU (0avgtext+0avgdata 16896maxresident)k
0inputs+0outputs (0major+1960minor)pagefaults 0swaps

so way faster than on my local desktop CPU, hurray.

After setup from: askubuntu.com/a/1309774/52975 we were able to run:

head -n1000 pap.txt | ARGOS_DEVICE_TYPE=cuda time argos-translate --from-lang en --to-lang fr > pap-fr.txt

which gave:

77.95user 2.87system 0:39.93elapsed 202%CPU (0avgtext+0avgdata 4345988maxresident)k
0inputs+88outputs (0major+910748minor)pagefaults 0swaps

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.

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Amazon EC2 hello world Updated 2025-07-16

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Let's get SSH access, instal a package, and run a server.

As of December 2023 on a t2.micro instance, the only one part of free tier at the time with advertised 1 vCPU, 1 GiB RAM, 8 GiB disk for the first 12 months, on Ubuntu 22.04:

$ free -h
               total        used        free      shared  buff/cache   available
Mem:           949Mi       149Mi       210Mi       0.0Ki       590Mi       641Mi
Swap:             0B          0B          0B
$ nproc
1
$ df -h /
Filesystem      Size  Used Avail Use% Mounted on
/dev/root       7.6G  1.8G  5.8G  24% /

To install software:

sudo apt update
sudo apt install cowsay
cowsay asdf

Once HTTP inbound traffic is enabled on security rules for port 80, you can:

while true; do printf "HTTP/1.1 200 OK\r\n\r\n`date`: hello from AWS" | sudo nc -Nl 80; done

and then you are able to curl from your local computer and get the response.

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Ubuntu 18.04 Updated 2025-07-16

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Ubuntu 23.10 Updated 2025-07-16

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Virtuoso Universal Server Updated 2025-07-16

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RDFlib Updated 2025-07-16

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Hello world: stackoverflow.com/questions/16829351/is-there-a-hello-world-example-for-sparql-with-rdflib

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Apache Jena Updated 2025-07-16

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Bibliography:

www.reddit.com/r/semanticweb/comments/131wzn1/whats_the_best_way_to_work_with_apache_jena/

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RDNA 3 Updated 2025-07-16

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