This presentation was made at CAASE18, The Conference on Advancing Analysis & Simulation in Engineering. CAASE18 brought together the leading visionaries, developers, and practitioners of CAE-related technologies in an open forum, to share experiences, discuss relevant trends, discover common themes, and explore future issues.
From concept to engineering, and from design to test and manufacturing, engineers from wide ranges of industries face ever increasing needs for complex, realistic models to analyse the most challenging industrial problems; Finite Element Analysis is performed in an effort to secure quality and speed up the development process. Powerful virtual development software is developed to tackle these needs for the finite element-based Computational Fluid Dynamics (CFD) simulations with superior robustness, speed, and accuracy. Those simulations are designed to carry out on large-scale computational High-Performance Computing (HPC) systems effectively.
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 applications performance.
Smart interconnect solutions are based on an offloading architecture, which can
offload all network functions from the CPU to the network, freeing CPU cycles and increasing the system’s efficiency. With the new efforts in the co-design approach, the new generations of interconnects include more and more data algorithms that can be managed and executed within the network, allowing users to run data algorithms on the data as the data being transferred within the system interconnect, rather than waiting for the data to reach the CPU. These interconnects deliver In-Network Computing and In-Network Memory, which is the leading approach to achieve 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 in-network computing architectures, and how they can influence on the runtime, scalability and performance of CAE simulations.
|Date||6th June 2018|
|Organisation||HPC Advisory Council|