From training in the data center to inferencing at the edge, Sylabs makes it easy to manage your containerized workflows with machine learning frameworks and leverage the power of GPUs while optimizing security and repeatability.

Containerize genomics analyses and other workflows to provide long-term reproducibility and ease deployment to local HPC and the cloud.

Sylabs develops advanced tools that seamlessly integrate with existing DevSecOps workflows to shield mission-critical edge and IoT device software from IP theft.

“By using SingularityPRO, we will be able to facilitate Fugaku to be a secure, reproducible and portable high-performance computing environment for a wide spectrum of users spanning academia to industry.”

Satoshi Matsuoka

Director of RIKEN Center for Computational Science (R-CCS)

“As an early adopter of Singularity, the San Diego Supercomputer Center (SDSC) has been collaborating with Sylabs and the development team for several years. The scientific community is developing software at an unprecedented rate, and our collaboration with Sylabs helps us more quickly respond to the evolving needs of our users.”

Mahidhar Tatineni

User Support Group Lead at San Diego Supercomputer Center

“The availability of ready-to-use binary distributions is the primary benefit we’ve derived from SingularityPRO. This has made it much easier for our systems configuration staff to provision SingularityPRO onto servers and compute nodes."

Oleksandr Moskalenko

Research Computing Applications and Facilitation Lead, University of Florida

“When we first adopted Singularity a few years ago, the driving case was to support TensorFlow on our cluster with GPUs and an old operating system. It was relatively easy to build a container with the right libraries and environment using Singularity. The use cases today are increasing even as we update our clusters, so Singularity is more than a transient solution.”

Chris Reidy

Research Facilitation Manager, University of Arizona

“Reproducibility is especially important to ensure scientific integrity and accuracy, making Singularity containers incredibly valuable because they can be shared so seamlessly. Along with many other bioinformatics researchers (too many to name), we are helping set a new standard for scientific discovery with our commitment to ensuring our studies are entirely reproducible with Singularity containers from Sylabs.”

Mark T. W. Ebbert, Ph.D

Assistant Professor Sanders-Brown Center, University of Kentucky

“As our advanced simulation codes push the boundaries towards more specialized hardware and systems, the need for performance portability and adaptability grows in HPC. It's about ensuring our software doesn't just run, but runs efficiently and consistently, regardless of the underlying system. SingularityCE 4.0 addresses this vision in an open-source context, offering interoperable OCI support and facilitating adaptable and efficient containerized application deployments. Amidst the complexities of large-scale computing environments, teams thrive when collaboration is seamless; SingularityCE 4.0 takes a commendable step in facilitating the power of teamwork."

Andrew J Younge

R&D Manager of the Scalable Computer Architectures, Sandia National Laboratories