You can read Part I here: https://www.simops.com/post/how-to-reach-simops-maturity-for-your-organization-s-engineering-simulation-operations
As discussed in Part I of this article, the SimOps Maturity Model provides a structured framework for organizations to advance their simulation operations from initial implementation to full optimization. By following this roadmap, organizations can enhance collaboration, drive innovation, and improve product quality, ensuring success in today's dynamic and competitive engineering landscape. SimOps empowers teams to achieve strategic objectives, maintain a leadership position in their respective industries, and unlock the full potential of simulation-driven decision-making. Part II now presents several maturity approaches and examples for SimOps compliant engineering simulation infrastructures.
SimOps Maturity Approaches for Your Organization’s Engineering Simulation Infrastructure
The decision to build and maintain a custom simulation platform on premises or in the cloud, or to purchase a ready-made cloud-based solution is crucial for organizations seeking to optimize their engineering simulation operations. This section explores the trade-offs associated with each approach, focusing on balancing speed, quality, and cost in simulation processes.
Building a Custom Simulation Platform (Do It Yourself)
Building a custom simulation platform allows organizations to tailor solutions to specific needs, offering control over their simulation infrastructure. This can be achieved by your own IT department, or outsourcing it to your expert HPC System Integrator (SI, if you have one). However, this approach involves significant challenges:
Complexity and Cost: Developing a custom platform requires substantial investment in hardware, software, and skilled personnel. Organizations must manage software and hardware dependencies, ensure infrastructure tuning for specific applications, and address security and compliance requirements.
Specialized Expertise: Maintaining a custom platform necessitates specialized expertise in areas such as high-performance computing (HPC), cloud architecture, and simulation technologies. This expertise can be scarce and costly, increasing the operational burden on IT teams.
Uncertainty of Time and Cost: Because of lack of experience in designing and building a custom platform, these projects can easily run out of time and budget.
Scalability and Flexibility: Custom platforms may struggle to scale efficiently with changing project demands, limiting an organization's ability to adapt to new challenges and opportunities. The lack of flexibility can hinder innovation and slow down development cycles.
According to McKinsey and other multinational strategy and management consulting firms, the risk of failure of DIY digital transformation processes is over 70%.
Acquiring a Cloud-Based Simulation Platform
Purchasing, licensing (e.g. annually), or using an off-the-shelf cloud-based simulation platform on demand offers several advantages over building a custom solution yourself, particularly in terms of scalability, cost-effectiveness, and ease of use:
Scalability and Resource Optimization: Cloud-based platforms provide on-demand access to scalable computational resources, enabling organizations to handle variable workloads efficiently. This flexibility allows teams to run complex simulations without the constraints of a fixed infrastructure.
Cost-Effectiveness: Cloud platforms convert capital expenses into operational expenses, reducing the need for upfront investments in hardware and infrastructure. Organizations can optimize costs by leveraging the cloud's consumption-based pricing models, paying only for the resources they use.
Rapid Deployment and Integration: Cloud-based platforms offer rapid deployment capabilities, allowing organizations to quickly integrate new tools and technologies. This agility enables teams to stay ahead of technological advancements and respond swiftly to changing market conditions.
Managed Services and Support: Cloud providers offer managed services that simplify platform maintenance, allowing IT teams to focus on strategic initiatives rather than operational challenges. These services include automatic updates, security monitoring, and technical support, ensuring that the platform remains secure and reliable.
Example: Independent Software Vendors’ Clouds
This solution is often well suited for Small and Medium Enterprises (SMEs) that use only a few (or even just one) commercial solvers, e.g. from Ansys, Cadence, Dassault, and Siemens. These ISVs offer their own cloud for their (major) commercial software packages, tailored to their solvers. They are user friendly and support cloud-based licensing (cloud tokens / elastic units, per hour per node credits). But they often come with some limitations: e.g. choice and number of compute nodes; aged hardware; data has to be downloaded to local machine after processing; no GPU acceleration for compute; and jobs run in the ISV’s own cloud subscription, i.e. engineers lose control over their simulation and data.
Example: Cloud Services Providers
Cloud Service Providers (CSPs) like Rescale, SimR (formerly UberCloud), and SimScale are often more flexible than ISV Clouds. They offer more and different solver options for more applications, and can usually run on several cloud infrastructures (e.g. from Amazon, Microsoft, Google, or Oracle). Some CSPs are limited to just solvers commercial or open source (Rescale, SimScale), others can do complex commercial, open source, and home-made proprietary workflows (SimR).
Some are limited in the choice of resources and focus more on SMEs (SimScale), others focus on large enterprises (SimR). Some offer mainly one software release (SimScale), others offer multiple solver releases. Some handle complex and custom workflows (in-house, multiphysics, FSI, Digital Twins, ML, . . .) on any Cloud and arbitrary multi-node scalable parallel clusters. Some request data download to a local machine, some also download results to cloud storage.
Some offer just CPUs, others CPU/GPUs for compute, post-processing, and remote high-definition visualization. And most important: Only a few run in customer‘s own cloud subscription and thus provide engineers exclusive control over their simulations and data!
Therefore, in the situation of working with CSPs it is highly recommended to set up a list of major requirements and best practices and then contact CSPs to check their offers.
The decision to build or buy a simulation platform should be based on an organization's specific needs, resources, and strategic objectives. While building a custom platform offers control and customization, purchasing a cloud-based solution provides scalability, cost-effectiveness, ease of use, and predictability in time and cost. By leveraging a comprehensive cloud-based platform, organizations can enhance their simulation operations, drive innovation, and maintain a competitive edge in today's dynamic engineering landscape.
