NAFEMS Americas and Digital Engineering (DE) teamed up (once again) to present CAASE, the (now Virtual) Conference on Advancing Analysis & Simulation in Engineering, on June 16-18, 2020!

CAASE20 brought together the leading visionaries, developers, and practitioners of CAE-related technologies in an open forum, unlike any other, to share experiences, discuss relevant trends, discover common themes, and explore future issues, including:
-What is the future for engineering analysis and simulation?
-Where will it lead us in the next decade?
-How can designers and engineers realize its full potential?
What are the business, technological, and human enablers that will take past successful developments to new levels in the next ten years?

Resource Abstract

High-performance computing (HPC) technologies are used in the engineering and automotive design and manufacturing industry. One of the applications is the computer-aided engineering (CAE), from component-level design to full analyses such as: crash simulations, structure integrity, thermal management, climate control, modeling, acoustics, and much more. HPC helps drive faster time-to-market, realizing significant cost reductions over laboratory testing and tremendous flexibility. HPC’s strength and efficiency depend on the ability to achieve sustained top performance by driving the CPU performance toward its limits. The motivation for high-performance computing has long been its tremendous cost savings and product improvements; the cost of a high-performance compute cluster can be just a fraction of the price of a single crash test for example, and the same cluster can serve as the platform for every test simulation going forward.



The recent trends in cluster environments, such as multi-core CPUs, GPUs, and advanced high speed, low latency interconnect with offloading capabilities, are changing the dynamics of cluster-based simulations. Software applications are being reshaped for higher degrees of parallelism and multi-threading, and hardware is being reconfigured to solve new emerging bottlenecks to maintain high scalability and efficiency. Applications like LS-DYNA, ANSYS Fluent, OpenFoam and others are widly used and provide better flexibility, scalability, and efficiency for such simulations, allowing for larger problem sizes and speeding up time to results.



CAE Applications relies on Message Passing Interface (MPI), the de-facto messaging library for high performance clusters that is used for node-to-node inter-process communication (IPC). MPI relies on a fast, unified server and storage interconnect to provide low latency and high messaging rate. Performance demands from the cluster interconnect increase exponentially with scale due in part to all-to-all communication patterns. This demand is even more dramatic as simulations involve greater complexity to properly simulate physical model behaviors.

In this paper we will focus on the value of In-Network computing for InfiniBand Networks for CAE applications.