Altair Grid Engine™

Distributed Resource Management and Optimization

Boosting HPC for Biotechnology: Bielefeld University's Biotechnology Center Transcends Research Boundaries

Widely recognized for its interdisciplinary research-oriented teaching, Germany’s Bielefeld University encompasses humanities, technology, and natural and social sciences. The university’s Center for Biotechnology (CeBiTec) bundles the institution’s biotechnological activities and research projects, fostering cross-field collaboration and innovation. Massive volumes of data and growing user demand meant they needed a powerful, efficient workload orchestrator. The team selected Altair Grid Engine for its optimized throughput and performance, rich features, reliability, expert support, and no learning curve.

Customer Stories

Maximizing Data Resources: ISI's VISTA Lab Speeds Up Machine Learning Research and Lowers Expenses

The Information Sciences Institute (ISI) is a world leader in research and development of advanced information processing, computing, and communications technologies — one of the nation’s largest, most successful university-affiliated computer research institutes. ISI’s Video, Image, Speech and Text Analytics (VISTA) lab makes extensive use of machine learning in a variety of application areas such as facial identification, natural language processing, and handwriting recognition. VISTA selected Altair® Grid Engine® to manage growing infrastructure and accelerate its machine learning research. Key contributing factors for VISTA’s decision to transition to Altair Grid Engine over other vendors included built-in advanced GPU support, detailed documentation, ongoing product upgrades, and expert support.

Customer Stories

Silicon Design in the Cloud: Mellanox Scales Up EDA Cluster Capacity With On-demand Hybrid Cloud

Mellanox Technologies is a leading supplier of end-to-end Ethernet and InfiniBand intelligent interconnect solutions for servers, storage, and hyper-converged infrastructure. Half the world’s top 500 fastest supercomputers employ Mellanox solutions including high-performance network and multicore processors, network adapters, switches, cables, software, and silicon. Mellanox needed a robust cluster management and scheduling solution from a trusted partner, leveraging hybrid cloud. In assessing potential solutions, the Mellanox team analyzed performance, features, and costs, ultimately selecting Altair Navops Launch™ and Altair® Grid Engine®, proven solutions that offered the shortest implementation effort with leading price/performance metrics. Navops Launch seamlessly enabled Mellanox’s existing on-premises infrastructure and workflows to encompass the cloud.

Customer Stories

Efficient HPC Enables Research: Queen Mary University of London Maximizes HPC Cluster Performance

Globally recognized for pushing the boundaries of research and innovation, Queen Mary University of London (QMUL) is one of the United Kingdom’s leading higher education institutions, with 5 campuses in London plus sites across Europe and Asia. Queen Mary’s high-performance computing cluster supports a student and research community of over 2,000 users in disciplines including astronomy, computational chemistry, bioinformatics, computer science, engineering, mathematics and statistics, and clinical research. QMUL needed a robust solution that could take them forward and allow their researchers to run any application type. Having eliminated offerings that were cost-prohibitive, migration-intensive, or lacked support, QMUL selected Altair® Grid Engine® for its rich features, high performance, large installed base, expert support, and easy upgrade path.

Customer Stories

Expanding Life Sciences Research: Wellcome Centre for Human Genetics Broadens Research Workloads

The Wellcome Centre for Human Genetics (WHG) is a leading research institute within the Nuffield Department of Medicine at the University of Oxford. With more than 400 researchers, the Centre is an international leader in genetics, genomics, statistics, and structural biology. WHG’s mission is to advance the understanding of genetically-related conditions through a broad range of multi-disciplinary research. To support its research community, the Centre operates a shared HPC cluster comprising more than 4,000 InfiniBand-connected, high-memory compute cores. With continuing rapid growth and new types of workloads expected, WHG was reaching the limits of their previous open-source Grid Engine scheduler, plus there were no practical options for support or addressing software bugs and security vulnerabilities. After an internal evaluation process and consulting with their user communities, WHG selected Altair® Grid Engine® as the scheduler to power their HPC environment.

Customer Testimonials

Boosting Stability and Scalability: CC-IN2P3 Provides Robust Infrastructure for Nuclear Physics and Particle Physics

The computing center at the National Institute of Nuclear and Particle Physics (CC-IN2P3) is dedicated to data storage and analysis for France’s National Center for Scientific Research. CCIN2P3 provides a 24/7 data hub for international physics, allowing more than 2,500 researchers to collaborate through its data storage, processing, and high-speed network facilities. The CC-IN2P3 recently expanded to two computer rooms with several thousand servers and libraries, enabling the storage of nearly 340 petabytes of data. As the demand for CC-IN2P3 grew, the team needed to find a robust and stable system backed by full enterprise-class support. They tested, validated, and selected Altair® Grid Engine® to address that challenge.

Customer Stories

Altair Grid Engine for Enterprise-class Scheduling and Optimization

Altair® Grid Engine® manages workloads automatically, maximizes shared resources, and accelerates the execution of containers, applications, and services. The solution can be deployed in any technology environment: on-premises, cloud, hybrid cloud, or cloud-native high-performance computing (HPC). By using Altair Grid Engine, enterprises and organizations can deliver products and results faster, more efficiently, and with lower overall costs.