• Radhika Gundavelli

In this study, we explore a novel approach that combines high-performance computing (HPC) with cloud-native frameworks to improve the efficiency of Automotive simulation based workflows. We propose a hybrid cloud architecture that leverages both HPC clusters and cloud-native frameworks.The simulation component runs on the HPC cluster, while the cloud handles CFD output processing. Microservice-like processes optimize resource utilization and minimize idle times. The hybrid model adapts dynamically to varying workloads. scalability ensures efficient resource allocation across simulations and locations. Centralized services facilitate collaboration among users. Machine learning algorithms benefit from automatic data provision. We present a proof of concept implementation, demonstrating the framework’s effectiveness.

High Performance Computing, Automotive HPC, HPC, Cloud

"HPC-cloud native concurrent simulation of Automotive workflows", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 6, page no.h802-h808, June-2024, Available :http://www.jetir.org/papers/JETIR2406785.pdf

"HPC-cloud native concurrent simulation of Automotive workflows", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 6, page no. pph802-h808, June-2024, Available at : http://www.jetir.org/papers/JETIR2406785.pdf