The effect of in-networking computing capable interconnects on scalability of cae simulations

From concept to design, testing and manufacturing, engineers from a wide range of industries face an ever-increasing need for complex, realistic models to analyze the most challenging industrial problems. Finite Element Analysis (FEA) simulations help to both secure quality and speed up the development process. These simulations are designed effectively to run on large-scale computational High-Performance Computing (HPC) systems. The latest revolution in HPC platforms is the move to a co-design architecture, to reach Exascale performance by taking a holistic system-level approach to fundamental performance improvements. Co-design architecture exploits system efficiency and optimizes performance by creating synergies between the hardware and the software, and between the different hardware elements within the data center. Co-design recognizes that the CPU has reached the limits of its scalability, and offers an intelligent network as the new “co-processor” to share the responsibility for handling and accelerating application workloads. By placing data-related algorithms on an intelligent network, we can dramatically improve data center and application performance. Smart interconnect solutions are based on an “offloading architecture” that can offload all network functions from the CPU to the network, freeing CPU cycles and increasing the system’s efficiency. With the innovative efforts of the codesign approach, the newer generations of interconnects are including more and more data algorithms that can be managed and executed within the network, thus allowing users to run data algorithms on the data as the data is being transferred within the system interconnect, rather than waiting for the data to reach the CPU. Today, In-Network Computing and In-Network Memory is the leading approach to achieving performance and scalability for Exascale systems. HPC Advisory Council performed deep investigations on a few popular CFD software to evaluate its performance and scaling capabilities and to explore potential optimizations. The study reviews the recent developments of innetwork computing architectures, and how they can influence on the runtime, scalability and performance of CAE simulations. THE EFFECT OF IN-NETWORKING COMPUTING-CAPABLE INTERCONNECTS ON SCALABILITY OF CAE SIMULATIONS