Performance-Portable Extreme-Scale Virtual Screening on Heterogeneous HPC Systems
A presentation at the "Application Perspective on SYCL (APerOL)" mini-symposium at PASC 2025. Abstract:Virtual screening is an early stage of drug discovery that ranks a chemical library by estimating the interaction strength between drug candidates and target proteins. Recent work demonstrate how increasing the number of candidates evaluated in-silico increases the probability of finding promising drugs. Given its embarrassingly parallel nature and the computation effort required by extreme-scale virtual screening campaign, high-performance computing (HPC) systems are the natural target platform. Modern HPC systems are characterized by hardware heterogeneity, where nodes rely on accelerators from different vendors, raising functional and performance portability challenges. We present the evolution of LiGen, the virtual screening engine of the EXSCALATE platform, toward performance-portable execution across GPU-based HPC systems. LiGen adopts a batched strategy to exploit accelerator parallelism, combining architecture-aware workload partitioning with out-of-kernel optimizations that adapt execution parameters to device characteristics. To further analyze portability aspects, we developed muDock, a molecular docking mini-application derived from the widely used AutoDock implementation, preserving representative computational patterns while enabling cross-architecture performance evaluation. Experimental results across GPU and CPU platforms analyze the impact of programming models and architectural features on achieved throughput and efficiency.
Authors
- G. Palermo (ORCID: https://orcid.org/0000-0001-9275-2282)
- Gianmarco Accordi (ORCID: https://orcid.org/0000-0001-8023-2108)
- Davide Gadioli (ORCID: https://orcid.org/0000-0002-0143-0737)
- Beltrame Beltrame (ORCID: https://orcid.org/0009-0006-5994-0170)
Institutions
- Politecnico di Milano (IT)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-06-30
- DOI
- https://doi.org/10.5281/zenodo.21072878
- Primary Topic
- Parallel Computing and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00