An open-source toolkit for deploying and managing high performance clusters for HPC, AI, and data analytics workloads.
-
Updated
Dec 6, 2024 - YAML
An open-source toolkit for deploying and managing high performance clusters for HPC, AI, and data analytics workloads.
🚀 R package: future: Unified Parallel and Distributed Processing in R for Everyone
PMIx Reference RunTime Environment (PRRTE)
Tools for computation on batch systems
Dasandata's Open HPC Cluster Recipes & Document.
A Slurm-based HPC workload management environment, driven by Ansible.
Prometheus exporter for a Infiniband Fabric
Pavilion is a Python 3 (3.5+) based framework for running and analyzing tests targeting HPC systems.
🚀 R package: future.apply - Apply Function to Elements in Parallel using Futures
Big Compute Learning Labs
OAR: versatile resource and job manager for cluster (third generation)
Prometheus exporter for the stats in the cgroup accounting with slurm. This will also collect stats of a job using NVIDIA GPUs.
Filesystem overlay for transparent, distributed migration of active data across separate storage systems.
slurm-docker-integration provides HPC-Kubernetes integration artifacts
This project provides provisioned HPC cluster models using underlying virtualization mechanisms.
A highly scalable framework for the performance and energy monitoring of HPC servers
🚀 R package: doFuture - Use Foreach to Parallelize via Future Framework
🧰 Toolkit for creating virtual clusters with public cloud resources
Self explained tutorial for molecular dynamics simulation using gromacs
Add a description, image, and links to the hpc-clusters topic page so that developers can more easily learn about it.
To associate your repository with the hpc-clusters topic, visit your repo's landing page and select "manage topics."