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Addressing the Scientific Reproducibility Crisis with Singularity

Michael Bauer from Sylabs gave this talk at the Perth HPC Conference. “Containers provide the means to encapsulate an application, its dependencies, data, and configurations, that allows for full mobility and reproducibility of the software stack. Containers have disrupted the Linux scene within the last few years because they have created a paradigm shift in what it means to package up and move applications and data.”

Singularity 3.4.0 Enables Build and Run Encrypted Containers

Sylabs just released the Singularity 3.4.0. The major new feature of this release is the ability to build and run encrypted containers. “Singularity containers remain encrypted throughout their entire lifecycle — when they are created, when they are at rest or transferred around, and yes, even when they are in use. Owing to their use of kernel space for data decryption, there is no need to clean up a decrypted rootfs upon termination.”

Video: Providing a National Software Repository for Interactive HPC

Lance Wilson from Monash University gave this talk at the Singularity User Group. “The repository for the build files is public and is run in the same way as a software development project. In addition to the build files being public, the repository is linked to singularity hub, such that the containers are easily available to anyone in the characterisation research community.”

Singularity 3.3.0 Goes GA

Today Sylabs announced the Generally Available Release of Singularity 3.3.0. As the premier Container platform for performance-sensitive workloads, this release of Singularity focused on quality and stability. “Given the frenetic pace of development, we saw this as an opportunity to double down on quality and stability. Three release candidates later, you can appreciate that the quality and stability objective has been achieved in spades. Kudos to the entire user, developer, and provider community for their collective and substantial efforts in reaching this milestone.”

Decoupling EDA Toolchains from the OS with Singularity Containers

Singularity containers introduce a compelling means for unlocking the implied dependency between application toolchains and operating system. By encapsulating everything but the kernel in a single file, Singularity containers decouple the runtime and allow it to be highly portable in a trusted way. 

Benchmarking MPI Applications in Singularity Containers on Traditional HPC and Cloud Infrastructures

Andrei Plamada from ETH Zurich gave this talk at the hpc-ch forum on Cloud and Containers. “Singularity is a container solution that promises to both integrate MPI applications seamlessly and run containers without privilege escalation. These benefits make Singularity a potentially good candidate for the scientific high-performance computing community. However, the performance overhead introduced by Singularity is unclear. In this work we will analyze the overhead and the user experience on both traditional HPC and cloud infrastructures.”

Towards Reproducible Data Analysis Using Cloud and Container Technologies

Sergio Maffioletti from the University of Zurich gave this talk at the hpc-ch forum on Cloud and Containers. “In this talk, we’ll provide an overview of the challenges faced by both research infrastructure providers and Science IT units, along with best practices to improve the reproducibility of data analysis using cloud and container technologies.”

How Singularity Containers can ease the Transition to RHEL 8

The general availability of Red Hat Enterprise Linux 8 was announced this week at the Red Hat Summit in Boston. In this special guest feature, Ian Lumb writes that the company’s Singularity containers can ease the transition to RHEL 8. “RHEL 8 is a transition over time, not a discrete event in time. Singularity containers preserve your heavily vested legacy deployments, while enabling you to make the transition on your terms.”

Video: Managing large-scale cosmology simulations with Parsl and Singularity

Rick Wagner from Globus gave this talk at the Singularity User Group “We package the imSim software inside a Singularity container so that it can be developed independently, packaged to include all dependencies, trivially scaled across thousands of computing nodes, and seamlessly moved between computing systems. To date, the simulation workflow has consumed more than 30M core hours using 4K nodes (256K cores) on Argonne’s Theta supercomputer and 2K nodes (128K cores) on NERSC’s Cori supercomputer.”

SingularityPRO comes to Google Cloud

Today Sylabs announced a multi-phase collaboration with Google Cloud as a technology partner. Aimed at systematically addressing enterprise requirements in a cloud-native fashion, the first phase of the collaboration will be based upon availability of Sylabs’ SingularityPRO via the Google Cloud Platform Marketplace. “Singularity is a widely adopted container runtime that implements a unique security model to mitigate privilege escalation risks, and provides a platform to capture a complete application environment into a single file.”