Parallel Works ACTIVATE is an orchestration platform for hybrid and distributed computing. It unifies SLURM, Kubernetes, OpenStack, and other compute environments into a single, intuitive interface. This enables teams to provision, manage, and share HPC and AI/ML resources at scale without rearchitecting or retraining.
Born out of Argonne National Laboratory in 2015, ACTIVATE simplifies infrastructure complexity through automated workflows, API-driven processes, and policy-based governance. With real-time cost tracking, flexible cluster creation, and secure hybrid workflows, ACTIVATE helps organizations accelerate research, simulation, and AI innovation while maintaining control over budgets, compliance, and performance.
Cost Governance: Real‑time tracking, budgeting, chargeback, and enforcement at project/budget granularity
Security & Compliance: Includes IL‑5/CUI/ITAR compliant High‑Security Platform (HSP) option, with the Authorization to Operate (ATO) at the U.S. Department of Defense (DoD) Impact Level 5 (IL-5), granted by the High Performance Computing Modernization Program in August 2025
Unified Orchestration: Administer and monitor all control plane elements through our unified user interface and API to interact with and share diverse computing environments—on-premise, cloud, or edge
ACTIVATE HSP is the first hybrid, multi-cloud platform purpose-built for US national security workloads. It transforms secure computing by offering a preauthorized, mission-ready control plane for managing cloud, on-prem, and edge resources.
ACTIVATE AI extends the capabilities of the platform with tools purpose-built for GPU-intensive AI workloads. It delivers Kubernetes-native orchestration across hybrid and multi-cloud environments, enabling teams to run, scale, and govern AI/ML workflows with the same policy-driven control, real-time cost tracking, and hybrid flexibility that define ACTIVATE.
ACTIVATE integrates seamlessly with leading open-source tools and frameworks, giving users flexibility and choice across the HPC and AI stack.
