Carlos Eduardo Arango Gutierrez's Projects
NVIDIA GPU Operator creates/configures/manages GPUs atop Kubernetes
A Container implementation for the Google Drive Client
Google Drive client with support for new Drive REST API and partial sync
Hands on Linux Containers
High Performance Container Workshop website
Hyperscale OpenShift - clusters with hosted control planes
Fast Distribution of Docker Images on Clusters
Download Latest Ionic v3 Weather App ->
Ionic Push Notifications Base App for iOS and Android
2021 IN PROGRESS -- Getting Started with Containers on HPC
Deployment Automation for OpenShift on Baremetal in Red Hat's Shared Labs
The repository for the YouTube series JustForFunc
NVIDIA device plugin for Kubernetes
Dynamic Resource Allocation (DRA) for NVIDIA GPUs in Kubernetes
The NVIDIA Driver Manager is a Kubernetes component which assist in seamless upgrades of NVIDIA Driver on each node of the cluster.
Kubernetes files for various *.k8s.io sites
kcp is a prototype of a Kubernetes API server that is not a Kubernetes cluster - a place to create, update, and maintain Kube-like APIs with controllers above or without clusters.
Kubernetes Operations (kops) - Production Grade K8s Installation, Upgrades, and Management
Repository for code and documentation for the KubeFlux project: a joint effort with IBM, Red Hat, and LLNL
Production-Grade Container Scheduling and Management
Bootstrap Kubernetes the hard way on Google Cloud Platform. No scripts.
Kueue: Kubernetes-native Job Queueing
Container def files for Kwant
Cloud Native Landscape
PƔgina web del laboratorio de redes y sistemas distribuidos de la Universidad del Valle
libpod is a library used to create container pods. Home of Podman.
Libretto is a Golang library to create Virtual Machines (VMs) on any cloud and Virtual Machine hosting platforms such as AWS, Azure, OpenStack, vSphere, or VirtualBox.
lolcow singularity definition file
MetropolisāHastings algorithm In statistics and in statistical physics, the MetropolisāHastings algorithm is a Markov chain Monte Carlo (MCMC) method for obtaining a sequence of random samples from a probability distribution for which direct sampling is difficult. This sequence can be used to approximate the distribution (e.g., to generate a histogram), or to compute an integral (such as an expected value). MetropolisāHastings and other MCMC algorithms are generally used for sampling from multi-dimensional distributions, especially when the number of dimensions is high. For single-dimensional distributions, other methods are usually available (e.g. adaptive rejection sampling) that can directly return independent samples from the distribution, and are free from the problem of autocorrelated samples that is inherent in MCMC methods.