Abstract
High-Performance Computing is the target system for virtual screening applications, which aim to suggest which candidates to test in the drug discovery process. The HPC heterogeneity of modern systems raises the functional and performance portability challenge. LiGen is a well-known virtual screening application that can offload the most demanding computation on GPUs. It has been used to perform extreme-scale virtual screening campaigns on HPC systems equipped with NVIDIA cards using a CUDA implementation. This paper reports the experience of running its SYCL implementation on the LUMI-G HPC system that leverages AMD GPUs. Based on the experimental results, the LiGen SYCL implementation performs well on AMD GPUs, enabling LiGen to run a virtual screening campaign on LUMI-G HPC infrastructure.
Gianmarco Accordi
Ph.D. Student
Gianmarco Accordi is a PhD student at Politecnico di Milano specializing in performance portability for high-performance computing and drug discovery simulations.
Davide Gadioli
Assistant Professor
He earned his M.S. in Information Technology (2013) and Ph.D. cum laude in 2019 from Politecnico di Milano. A former Visiting Student at IBM Research (2015), he is now a postdoctoral researcher at DEIB, focusing on application autotuning, approximate computing, molecular docking, and drug discovery. He contributes to EXSCALATE software development.
Gianluca Palermo
Full Professor
Gianluca Palermo received the M.Sc. degree in Electronic Engineering in 2002, and the Ph.D degree in Computer Engineering in 2006 from Politecnico di Milano. He is currently an associate professor at Department of Electronics and Information Technology in the same University. Previously he was also consultant engineer in the Low Power Design Group of AST – STMicroelectronics working on network on-chip and research assistant at the Advanced Learning and Research Institute (ALaRI) of the Università della Svizzera italiana (Switzerland). His research interests include design methodologies and architectures for embedded and HPC systems, focusing on AutoTuning aspects.