Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels
Technical University of Darmstadt, Darmstadt, Germany
Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC Workshops ’25), 2025
@article{solis2025architecting,
title={Architecting Tensor Core-Based Reductions for Irregular Molecular Docking Kernels},
author={Solis-Vasquez, Leonardo and Tillack, Andreas F and Santos-Martins, Diogo and Koch, Andreas and Forli, Stefano}
}
Tensor Cores (TCs) are specialized hardware units designed for efficient matrix multiplication and are widely utilized in deep learning workloads. However, their adoption in more irregular high-performance computing (HPC) applications remains limited. This paper presents a methodology for effectively integrating TCs into a representative HPC application: molecular docking with AutoDockGPU. The irregular computational patterns and strict accuracy requirements of this application pose significant challenges for TC utilization. To address these, we adopt a twofold strategy: (i) accelerating sum reduction operations using TCs, and (ii) applying state-of-the-art numerical error correction (EC) techniques to maintain accuracy. Experimental evaluations on NVIDIA A100, H100, and B200 GPUs show that our CUDA-based implementation consistently outperforms the baseline while preserving algorithmic accuracy.
October 26, 2025 by hgpu
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