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IBM · IBM Spectrum LSF → Run:ai · Migration

Proven LSF to runai Migrations for Enterprise AI

Migrating from IBM Spectrum LSF to Run:ai is a straightforward project. Our senior engineers execute a fixed-scope migration, containerizing workloads and shifting scheduling to Kubernetes—without disrupting

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No-obligation consultation with a senior engineer.

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Powered by the 3PS Migration Engine

The lowest-cost way off IBM Spectrum LSF: our migration tooling automates the repetitive work —you pay senior engineers for judgment, not keystrokes.

Automated discovery
Your IBM Spectrum LSF estate mapped — workloads, dependencies, licensing — before day one
Conversion tooling
Schema, config and workload translation to Run:ai, automated where it's safe
Parity validation
Side-by-side testing proves Run:ai matches production before cutover
Runbook cutover
Rehearsed, reversible, scheduled in your maintenance window
40-70%
Savings vs OEM LSF support
24/7
US-based support
Multi-vendor
Coverage for hybrid environments

How we support IBM Spectrum LSF → Run:ai after migration

  • Containerize legacy CUDA binaries for Run:ai compatibility.
  • Preserve user workflows during the phased migration.
  • Maintain LSF vendor support until cutover is safe.
  • Fixed-scope projects with senior GPU infrastructure engineers.
  • 40-70% savings vs legacy LSF support renewals.
  • 24/7 US-based support throughout the transition.

Low GPU Utilization on LSF

Your Spectrum LSF scheduler cannot efficiently handle massive generative AI and deep learning workloads, leaving GPU clusters underused.

Disrupting Legacy Workflows

Migrating away from proprietary LSF tools and non-containerized CUDA binaries risks halting active research and developer productivity.

Forced Renewal Fees

While planning your move to Run:ai, the looming LSF renewal deadline pressures you into paying for another year of expensive vendor support.

IBM Spectrum LSF → Run:ai migration — your questions answered

How long does an LSF to runai migration typically take?+

Our fixed-scope migrations for IBM Spectrum LSF to Run:ai run 3-6 months with 2-3 senior GPU infrastructure engineers. The timeline depends on workload complexity and cluster size.

Will my existing CUDA binaries and LSF scripts work on Run:ai?+

We containerize your legacy CUDA binaries and migrate proprietary dataset management tools to Run:ai's Kubernetes environment. Your users' command-line habits are preserved through familiar interfaces where possible.

Can we keep IBM Spectrum LSF running during the migration to Run:ai?+

Yes. We maintain your active LSF deployment under vendor support while we migrate workloads in phases. Your contract stays active, so there is no forced big-bang cutover. If the renewal lapses, our third-party support covers most operational issues.

What post-migration support do you offer for the Run:ai platform?+

After migration, we provide Run:ai platform optimization, Kubernetes cluster scaling support, and monthly GPU resource consumption reports to ensure maximum utilization and cost efficiency.

Next Step: Run:ai GPU Orchestration Assessment

Our Run:ai GPU Orchestration Architecture Assessment evaluates your current LSF setup and designs a migration plan with fixed scope and budget. After the move, we continue optimizing your Run:ai environment, managing Kubernetes scaling, and delivering monthly GPU resource reports. Get a clear path to higher GPU utilization and lower costs.

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