HPC & Cloud Solutions for Life Sciences

Top-performing life sciences organizations strike the right balance between flexibility for end users and robust, supported, scalable infrastructure for IT stakeholders. Johnson & Johnson’s Martin Dellwo, RCH Solutions’s Phil Eschallier, and Altair’s Bill Bryce outline how to build and manage a scalable, flexible, automated, cloud-agnostic, multi-cluster, heterogeneous HPC environment in this live webinar, followed by a Q&A.


Where to Begin: HPC and Cloud Computing Models for Engineers

In this session, cloud expert Rick Watkins presents three actionable HPC and cloud models designed to optimize innovation potential and longtime ROI, whether your team is small and nimble or maintains its own large compute infrastructure. Engineers interested in boosting performance with HPC will come away with an understanding of what HPC and cloud model could be right for them – as well as a high-level appreciation for the critical role that IT infrastructure optimization plays in maintaining your team’s competitive edge, and all the complexity involved in making appear simple.

Future.Industry 2021

Data Discipline: Managing Engineering Data for AI-powered Design

The advancements in the fields of AI and ML, combined with the increased availability of robust simulation, testing, and field data sets has made engineering data science a critical component of the modern product development lifecycle, but in order to extract maximum value from these exciting tools, companies need a plan to store, manage, and utilize their data efficiently. They need data discipline

Technical Document

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™ 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

Wharton School Scales Up HPC: High-performance Computing Upgrade Extends Research to the Cloud

Founded in 1881 as the world’s first collegiate business school, the Wharton School at the University of Pennsylvania is known for leadership and innovation in business education. Staying on top as a leader among world-class business schools necessitates an HPC infrastructure that can support a vast number of users. Wharton needed to extend its HPC environment in a cost-effective way — without impacting its large roster of users, who need ready access to the latest tools, infrastructure, and technical expertise. Since Wharton was already using Altair® Grid Engine® as its go-to solution for HPC job management, the team looked to Altair NavOps™, software designed for organizations experiencing increasing volumes of high-priority workloads, where response speed and accuracy is critical.

Customer Stories

Managing TCO in HPC Hybrid Cloud Environments

Enabled by improvements in security, new instance types, and fast interconnects, high-performance computing (HPC) users are increasingly shifting workloads to the cloud. With cloud usage increasing, however, managing and containing costs is a growing concern. As organizations become more reliant on cloud, they are also concerned with staying portable and flexible, and avoiding lock-in to a single cloud ecosystem or provider. In this paper, we make a case for HPC hybrid cloud and explain how operators can manage total cost of ownership (TCO) more effectively. We present a simple TCO model that can help users estimate the cost of hybrid cloud deployments and describe various Altair solutions that can help organizations quickly and cost-effectively implement private and hybrid multi-cloud HPC environments. Using our TCO model, we illustrate how Altair cloud automation and spend management solutions such as Altair® Control™ and Altair® NavOps® can boost productivity and reduce cloud-related expenses while delivering a compelling return on investment (ROI).

White Papers

Altair NavOps for Cloud Automation and Spend Management

Altair® NavOps® is an automation and spend management platform for migrating compute-intensive HPC workloads to the cloud. It provides organizations with insights into spending against budgets and end-to-end visibility into HPC cloud resources and applications. Using NavOps, enterprises can easily deploy hybrid and dedicated cloud clusters running Altair® Grid Engine® or other workload managers.


The Wharton School Powers World-changing Research with Altair HPC

The Wharton School of the University of Pennsylvania, one of the world’s most prominent business schools, depends on Altair Grid Engine and Altair NavOps to run a powerful, scalable and future-proof HPC infrastructure that enables researchers to focus on their core work.

Customer Stories

Powering Drug Discovery – HPC at Johnson & Johnson Supports Critical Pharmaceutical Development

Janssen Pharmaceuticals, a subsidiary of Johnson & Johnson, created the 1-dose COVID-19 vaccine that’s preventing infection and saving lives in 100+ countries around the world. When Janssen needed the right HPC management software for its cloud-based infrastructure, we upgraded the company's workload management software to Altair® Grid Engine® and deployed Altair® NavOps® to manage their complex cloud deployments — a solution that seamlessly integrated with AWS cloud services. The result was a simplified, automated, and extensible HPC infrastructure.

Customer Stories

Six Smarter Scheduling Techniques for Optimizing EDA Productivity

Semiconductor firms rely on software tools for all phases of the chip design process, from system-level design to logic simulation and physical layout. Given the enormous investment in tools, design talent, and infrastructure, even minor improvements in server farm efficiency can significantly impact the bottom line. As a result, verification engineers and IT managers are constantly looking for new sources of competitive advantage. Workload management plays a crucial role in helping design teams share limited resources, boost simulation throughput, and maximize productivity. In this paper, we discuss six valuable techniques to help improve design center productivity.

White Papers