Rescale
Data science and machine learning platforms
Simulation & CAE software
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What is Rescale
Rescale is a cloud-based high-performance computing (HPC) platform used to run engineering simulation and computational science workloads at scale. It provides a web interface and APIs to submit, schedule, and monitor batch jobs across multiple cloud infrastructure options, commonly for CAE, CFD, FEA, and related solver-based workflows. The platform focuses on packaging software environments, managing data movement, and orchestrating compute resources so engineering teams can run simulations without operating their own HPC clusters.
Cloud HPC job orchestration
Rescale centralizes submission, scheduling, and monitoring of batch simulation jobs through a web UI and programmatic interfaces. It supports common HPC patterns such as multi-node runs, queueing, retries, and job-level resource configuration. This reduces the operational burden of maintaining on-prem schedulers and cluster tooling for engineering teams.
Multi-cloud infrastructure abstraction
Rescale is designed to run workloads on cloud compute resources rather than tying execution to a single on-prem environment. It abstracts instance selection and provisioning so users can scale up for peak simulation demand and scale down afterward. This model can be useful for organizations that need burst capacity or want to avoid long procurement cycles for HPC hardware.
Solver-centric workflow support
The platform is oriented around running commercial and open-source simulation solvers and managing their runtime environments. It provides mechanisms to package dependencies, handle input/output data, and standardize job templates across teams. This specialization fits engineering simulation use cases more directly than general-purpose analytics notebooks or BI-oriented platforms.
Not a full CAE authoring tool
Rescale primarily manages execution and infrastructure for simulations rather than providing native CAD/CAE modeling and pre/post-processing capabilities. Many users still rely on separate desktop or specialized engineering tools for geometry creation, meshing, and results visualization. This can increase workflow complexity and integration requirements.
Cloud cost governance required
Because workloads run on elastic cloud resources, costs can vary significantly based on instance types, run duration, storage, and data egress. Organizations typically need strong policies for quotas, approvals, and tagging to prevent overruns. Without disciplined governance, usage-based billing can be harder to predict than fixed on-prem capacity.
Integration and portability effort
Connecting enterprise identity, storage, and CI/CD or MLOps tooling often requires configuration and ongoing maintenance. Some solver licensing models and specialized hardware requirements may limit portability across clouds or constrain instance choices. Teams may need to adapt job scripts and data layouts to align with the platform’s execution model.
Seller details
Rescale, Inc.
San Francisco, CA, USA
2011
Private
https://rescale.com/
https://x.com/rescaleinc
https://www.linkedin.com/company/rescale/
