distributed_computing

Arboreto leverages Dask for parallelized computation, enabling efficient GRN inference from single-machine multi-core processing to multi-node cluster environments.

Skills
Scientific
0

What it does and how to use it

A skill that teaches Claude Code to do scientific tasks well. It is packaged knowledge the model uses whenever it is relevant.

Install the skill (command above).
In Claude Code, describe what you need - the skill turns on by itself when the context fits.
No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/distributed-computing && curl -fsSL https://doutorai.pt/data/lib/skills__distributed-computing.md -o .claude/skills/distributed-computing/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

# Distributed Computing with Arboreto

Arboreto leverages Dask for parallelized computation, enabling efficient GRN inference from single-machine multi-core processing to multi-node cluster environments.

## Computation Architecture

GRN inference is inherently parallelizable:
- Each target gene's regression model can be trained independently
- Arboreto represents computation as a Dask task graph
- Tasks are distributed across available computational resources

## Local Multi-Core Processing (Default)

By default, arboreto uses all available CPU cores on the local machine:

```python
from arbo

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