All Projects → azurebigcompute → BigComputeLabs

azurebigcompute / BigComputeLabs

Licence: other
Big Compute Learning Labs

Programming Languages

shell
77523 projects
python
139335 projects - #7 most used programming language
SystemVerilog
227 projects

Projects that are alternatives of or similar to BigComputeLabs

LAB
MIT IT Lab Repository
Stars: ✭ 23 (+21.05%)
Mutual labels:  lab, labs
awesome-mobile-robotics
Useful links of different content related to AI, Computer Vision, and Robotics.
Stars: ✭ 243 (+1178.95%)
Mutual labels:  lab, labs
sparkucx
A high-performance, scalable and efficient ShuffleManager plugin for Apache Spark, utilizing UCX communication layer
Stars: ✭ 32 (+68.42%)
Mutual labels:  hpc, rdma
HPC
A collection of various resources, examples, and executables for the general NREL HPC user community's benefit. Use the following website for accessing documentation.
Stars: ✭ 64 (+236.84%)
Mutual labels:  hpc, lab
omnia
An open-source toolkit for deploying and managing high performance clusters for HPC, AI, and data analytics workloads.
Stars: ✭ 128 (+573.68%)
Mutual labels:  hpc, hpc-clusters
ParallelUtilities.jl
Fast and easy parallel mapreduce on HPC clusters
Stars: ✭ 28 (+47.37%)
Mutual labels:  hpc, hpc-clusters
phenol
phenol: Phenotype ontology library
Stars: ✭ 15 (-21.05%)
Mutual labels:  genomics
SplitThreader
Explore rearrangements and copy-number amplifications in a cancer genome
Stars: ✭ 65 (+242.11%)
Mutual labels:  genomics
amqv7-workshop
No description or website provided.
Stars: ✭ 22 (+15.79%)
Mutual labels:  lab
Jamf-Nation-Roadshow-London-2018
No description or website provided.
Stars: ✭ 16 (-15.79%)
Mutual labels:  lab
nerd
Your personal nerd that takes care of running jobs on the Nerdalize cloud
Stars: ✭ 15 (-21.05%)
Mutual labels:  hpc
assembly improvement
Improve the quality of a denovo assembly by scaffolding and gap filling
Stars: ✭ 46 (+142.11%)
Mutual labels:  genomics
iterated-function-systems
Iterated Function Systems fractals with OCaml.
Stars: ✭ 33 (+73.68%)
Mutual labels:  visualisation
claw-compiler
CLAW Compiler for Performance Portability
Stars: ✭ 38 (+100%)
Mutual labels:  hpc
bsuir-csn-cmsn-helper
Repository containing ready-made laboratory works in the specialty of computing machines, systems and networks
Stars: ✭ 43 (+126.32%)
Mutual labels:  labs
prologix-gpib-ethernet
Simple wrapper for the Prologix GPIB-to-Ethernet adapter.
Stars: ✭ 20 (+5.26%)
Mutual labels:  lab
disq
A library for manipulating bioinformatics sequencing formats in Apache Spark
Stars: ✭ 29 (+52.63%)
Mutual labels:  genomics
bap
Bead-based single-cell atac processing
Stars: ✭ 20 (+5.26%)
Mutual labels:  genomics
Game-Animation
A python tool to visualise game animations
Stars: ✭ 74 (+289.47%)
Mutual labels:  visualisation
fwdpy11
Forward-time simulation in Python using fwdpp
Stars: ✭ 25 (+31.58%)
Mutual labels:  genomics

BigComputeLabs

Big Compute Learning Labs

Azure CycleCloud Labs

Introduction

These are technical labs to help you get started using CycleCloud to create, use, and manage Azure HPC clusters.

Objectives

In these labs, you will:

  • Understand Azure Resource Manager templates and versioning.
  • Use Azure Resource Manager version profiles to install PowerShell
  • Create an Azure resource group and deploy an Azure Resource Manager template.
  • Use the Azure Stack Policy module to constrain the resource group and test the limits of the constrained resource group.
  • Use the Azure Stack template validator to identify versioning incompatibilities.
  • Update templates for Azure Stack.
  • setup and install CycleCloud on a VM using an ARM template
  • configure CycleCloud to use Azure credentials
  • create a simple HPC cluster consisting of a job scheduler and an NFS file server
  • submit jobs and observe the cluster autoscale up and down automatically
  • review CycleCloud's cost reporting & controls, reporting, and other features

Resources can be located at the end of the Lab, as well as links for more advanced topics. These labs should take no more than 60-120 minutes to complete per lab, and many much faster than that.

We welcome any thoughts or feedback. We are always looking for ways to improve the experience of learning Azure CycleCloud!

Azure CycleCloud

Azure CycleCloud provides a simple, secure, and scalable way to manage compute and storage resources for HPC workloads in Microsoft Azure. Azure CycleCloud enables users to create environments for workloads on any point of the parallel and distributed processing spectrum, from parallel workloads to tightly-coupled applications such as MPI jobs on Infiniband/RDMA. By managing resource provisioning, configuration, and monitoring, Azure CycleCloud allows users and IT staff to focus on business needs instead infrastructure.

Azure CycleCloud delivers:

  • Complete control over compute environments, including VM resources, storage, networking, and the full application stack
  • Data transfer and management tools
  • Role-based access control (RBAC)
  • Templated applications and reference architectures
  • Cost reporting and controls
  • Monitoring and alerting
  • Automated, customizable configuration
  • Consistent security and encryption

If this is your first time using Azure CycleCloud, we recommend reading the product documentation to get more familiar with common Azure CycleCloud concepts: clusters, nodes and node arrays, data management, etc. Azure CycleCloud is freely available, downloadable, packaged, licensed application. For support options or other general questions, email askcyclecloud @ microsoft.com.

Intended audience

This lab is intended for people who would like to learn how to use Azure CycleCloud to create, customize, and manage HPC environments in Azure.

Labs

Prerequisites

  • Azure subscription (You can sign up for a free account here.)

Contributing

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].