TY - GEN
T1 - Elastic Workflows in Hybrid Cloud for CAE Simulations
AU - Dasgupta, Srishti
AU - Gerndt, Michael
AU - Gholami, Babak
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Companies traditionally dependent on on-premise HPC clusters for simulations are increasingly migrating workloads to the cloud. Cloud computing offers greater flexibility in selecting processors, memory, network bandwidth, along with enhanced resource availability and scalability. Automotive companies rely on computationally intensive numerical simulation tools for CAE (Computer-Aided Engineering), particularly with the growing demand for generative design, which utilizes algorithms to automatically explore a large solution space. This work addresses the gap between the growing runtime demands of these simulations and the limitations of static HPC infrastructure by representing iterative workflows as Directed Acyclic Graphs (DAGs) and optimizing their scheduling. We propose a unified hybrid infrastructure that leverages the elasticity of cloud resources along with existing HPC clusters to maximize computational efficiency, ensure timely completion of simulations, and optimize resource utilization and costs.
AB - Companies traditionally dependent on on-premise HPC clusters for simulations are increasingly migrating workloads to the cloud. Cloud computing offers greater flexibility in selecting processors, memory, network bandwidth, along with enhanced resource availability and scalability. Automotive companies rely on computationally intensive numerical simulation tools for CAE (Computer-Aided Engineering), particularly with the growing demand for generative design, which utilizes algorithms to automatically explore a large solution space. This work addresses the gap between the growing runtime demands of these simulations and the limitations of static HPC infrastructure by representing iterative workflows as Directed Acyclic Graphs (DAGs) and optimizing their scheduling. We propose a unified hybrid infrastructure that leverages the elasticity of cloud resources along with existing HPC clusters to maximize computational efficiency, ensure timely completion of simulations, and optimize resource utilization and costs.
KW - CAE Workflows
KW - Cloud Computing
KW - High Performance Computing
KW - Hybrid Infrastructures
UR - http://www.scopus.com/inward/record.url?scp=85212203836&partnerID=8YFLogxK
U2 - 10.1109/IC2E61754.2024.00037
DO - 10.1109/IC2E61754.2024.00037
M3 - Conference contribution
AN - SCOPUS:85212203836
T3 - Proceedings - 2024 IEEE International Conference on Cloud Engineering, IC2E 2024
SP - 251
EP - 252
BT - Proceedings - 2024 IEEE International Conference on Cloud Engineering, IC2E 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th IEEE International Conference on Cloud Engineering, IC2E 2024
Y2 - 24 September 2024 through 27 September 2024
ER -