Compute and Data Orchestration for Hybrid- and Multi-Cloud AI and HPC
Organizations building AI and high-performance computing (HPC) environments increasingly operate across hybrid infrastructure that spans on-premises clusters and public cloud resources.
Hammerspace and Parallel Works offer a joint solution that makes it easy to access compute resources across any infrastructure and orchestrate the movement of data across compute, storage systems, locations, and clouds.
This solution is ideal for research institutions, government agencies, and enterprise AI teams that need to securely access distributed computing resources quickly and efficiently.
Typical Use Cases
Cloud Bursting for Hybrid AI and HPC Workloads
Organizations often need to scale compute resources dynamically when on-premises clusters reach capacity. Parallel Works enables seamless cloud bursting to additional compute resources, while Hammerspace ensures that the datasets required for these workloads are accessible locally regardless of where the compute job runs
Access GPU Resources in Multiple Cloud Regions and Providers
Many organizations deploy infrastructure across multiple cloud providers for flexibility, resilience, or availability of scarce computing and storage resources . The combined solution allows organizations to run workloads across AWS, Azure, Google Cloud, and Oracle Cloud while maintaining a unified data environment through the Hammerspace global namespace.
Secure Research and Government Computing Environments
Research institutions, defense organizations, and government agencies must operate in highly secure environments while still enabling collaboration and scalable computing. With support for Impact Level 5 (IL5) deployments, Parallel Works and Hammerspace provide secure access to distributed compute infrastructure while maintaining centralized governance of both compute and data.
Distributed Research and Engineering Teams
Teams working across multiple locations often struggle with fragmented access to compute infrastructure and data. The joint solution enables researchers and engineers to launch workloads from a centralized interface while ensuring consistent access to shared datasets across sites and cloud environments.
