Publications [#374019] of Amanda Randles

Papers Published

1. Martin, A; Liu, G; Ladd, W; Lee, S; Gounley, J; Vetter, J; Patel, S; Rizzi, S; Mateevitsi, V; Insley, J; Randles, A, Performance Evaluation of Heterogeneous GPU Programming Frameworks for Hemodynamic Simulations, ACM International Conference Proceeding Series (November, 2023), pp. 1126-1137, ACM, ISBN 9798400707858 [doi]
   (last updated on 2024/11/20)

   Abstract:
   Preparing for the deployment of large scientific and engineering codes on upcoming exascale systems with GPU-dense nodes is made challenging by the unprecedented diversity of device architectures and heterogeneous programming models. In this work, we evaluate the process of porting a massively parallel, fluid dynamics code written in CUDA to SYCL, HIP, and Kokkos with a range of backends, using a combination of automated tools and manual tuning. We use a proxy application along with a custom performance model to inform the results and identify additional optimization strategies. At scale performance of the programming model implementations are evaluated on pre-production GPU node architectures for Frontier and Aurora, as well as on current NVIDIA device-based systems Summit and Polaris. Real-world workloads representing 3D blood flow calculations in complex vasculature are assessed. Our analysis highlights critical trade-offs between code performance, portability, and development time.