Singularity icon
Singularity icon

Singularity

Singularity is a container solution with a focus on building reproducible software stacks and running them most efficiently on existing HPC, scientific, compute farm and even enterprise architectures.

Screenshot of singularity building an hello-world container

Cost / License

  • Free
  • Open Source

Platforms

  • Mac
  • Windows
  • Linux
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Our users have written 2 comments and reviews about Singularity, and it has gotten 10 likes

Singularity was added to AlternativeTo by Luca Gibelli on and this page was last updated .

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TBayAreaPat
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Linux containers like Singularity cannot run natively on Windows or Mac. First, install the following software for Windows: Git for Windows VirtualBox for Windows Vagrant for Windows Vagrant Manager for Windows

linuxvps
1

Singularity is a lightweight, non-invasive, easily implementable container infrastructure that supports existing workflows and focuses on application portability and mobility. With Singularity you can build containers based on your host or predefined operating system and define the execution environment. Processes inside the container can be single binaries or a group of binaries, scripts, and data.

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What is Singularity?

Singularity creates a virtual environment for applications without the performance penalties associated with virtual machines. Best of both worlds: it simplifies the deployment of applications across different clusters and supercomputers by avoiding the laborious process of rehosting those applications for each distinct environment, without requiring a virtualized hardware layer.

Singularity is the container platform of choice to run deep learning and machine learning workloads with TensorFlow, Theano, SciKit.

Early containerization solutions focused on microservices and did not play well with some types of computing that rely on processing jobs instead of services, which is a requirement in the high-performance computing field. Singularity was designed from the ground up to be optimized for the kinds of performance-demanding environments used for scientific computing.

  • Targeted at emerging fields such as artificial intelligence, deep learning, machine learning, and data analytics

  • Trusted by the top supercomputing centers around the world

  • Compatible with data-intensive workloads that demand HPC-like resources

  • Integrates with container orchestration tools, specifically Kubernetes and Mesos, and also with Microsoft’s Azure Batch tool

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