The Automotive Makers Require Better Compute Simulations Capabilities

This week I presented in the LS-DYNA user conference. LS-DYNA is one of the most used applications for automotive related computer simulations – simulations that are being used throughout the vehicle design process and decreases the need to build expensive physical prototypes. Computer simulation usage has decreased the vehicle design cycle from years to month, and is responsible for cost reduction throughout the process. Almost every part in the vehicle is designed with computer aided simulations. From crash/safety simulation to engine and gasoline flow, from air condition to water pumps, almost every part of the vehicle is simulated.

Today challenges in vehicle simulations are around the motivation to build more economical and ecological designs, how to do design lighter vehicles (less material to be used) while meeting the increased safety regulation demands. For example, national and international standardizations have been put in place, which provide structural crashworthiness requirements for railway vehicle bodies.

In order to be able to meet all of those requirements and demands, higher compute simulation capability is required. It is not a surprise that LS-DYNA is being mostly used in high-performance clustering environments as they provide the needed flexibility, scalability and efficiency for such simulations. Increasing high-performance clustering productivity and the capability to handle more complex simulations is the most important factor for the automotive makers today. It requires using balanced clustering design (hardware – CPU, memory, interconnect, GPU; and software), enhanced messaging techniques and the knowledge on how to increase the productivity from a given design.

For LS-DYNA, InfiniBand interconnect-based solutions have been proven to provide the highest productivity compared to Ethernet (GigE, 10GigE, iWARP). With InfiniBand, LS-DYNA demonstrated high parallelism and scalability, which enabled it to take full advantage of multi-core high-performance computing clusters. In the case of Ethernet, the better choice between GigE, 10GigE and iWARP is 10GigE. While iWARP aim to provide better performance, typical high-performance applications are using send-receive semantics which iWARP does not provide any added value with, and even worse, it just increase the complexity and the CPU overhead/power consumption.

If you want to get a copy of a paper that present the capabilities to increase simulations productivity while decrease power consumption, don’t hesitate to send me a note (

Gilad Shainer