Results for parallel_machine

Javascript library for distributing tasks over many keys, limiting parallelism for each.

Scheduling algorithms in Rust — job scheduling, flow shop, branch and bound, priority rules, fleet scheduling

A distributed video encoder that splits files into chunks to encode them on multiple machines in parallel.

Query builder and iteration over rust-key-paths KpType for Vec collections

A rust crate for quick-and-dirty neuro network developing and training.

Distributed training and inference for ToRSh

Run one build entry across local and remote machines in parallel

Senior SysAdmin, Network Admin, Data Analyst, and Software Engineer living in your terminal. A high-precision local AI agent harness for LM Studio, Ollama, and other local OpenAI-compatible runtimes that runs 100% on your own silicon. Reads repos, edits files, runs builds, inspects full network state and workstation telemetry, and runs real Python/JS for data analysis.

A heavily parallelized neural network library designed for speed and flexability.

Tantale is a Rust library for Automated Machine Learning (AutoML) focusing on Hyperparameter Optimization and Neural Architecture Search. It provides a modular and extensible framework for defining search spaces, objectives, and optimization algorithms, with support for distributed computing and parallel execution.

Tantale is a Rust library for Automated Machine Learning (AutoML) focusing on Hyperparameter Optimization and Neural Architecture Search. It provides a modular and extensible framework for defining search spaces, objectives, and optimization algorithms, with support for distributed computing and parallel execution.

Tantale is a Rust library for Automated Machine Learning (AutoML) focusing on Hyperparameter Optimization and Neural Architecture Search. It provides a modular and extensible framework for defining search spaces, objectives, and optimization algorithms, with support for distributed computing and parallel execution.

Tantale is a Rust library for Automated Machine Learning (AutoML) focusing on Hyperparameter Optimization and Neural Architecture Search. It provides a modular and extensible framework for defining search spaces, objectives, and optimization algorithms, with support for distributed computing and parallel execution.