Create 2024-04-16-enabling-performance-portability-on-the-ligen-drug-discovery-pipeline.md

adds, "Enabling performance portability on the LiGen drug discovery pipeline"

Author: codeplaymax

content/research_papers/2024/2024-04-16-enabling-performance-portability-on-the-ligen-drug-discovery-pipeline.md

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+---
+contributor: max
+date: '2024-04-16T08:08:10.490000+00:00'
+title: 'Enabling performance portability on the LiGen drug discovery pipeline'
+external_url: https://www.sciencedirect.com/science/article/pii/S0167739X24001195
+authors:
+  - name: Luigi Crisci
+  - name: Lorenzo Carpentieri
+  - name: Biagio Cosenza
+  - name: Leon Bogdanović
+  - name: Gianmarco Accordi
+  - name: Davide Gadioli
+  - name: Emanuele Vitali
+  - name: Gianluca Palermo
+  - name: Andrea Rosario Beccari
+tags:
+  - gpu
+  - sycl
+  - hpc
+  - cuda
+  - hip
+---
+
+In recent years, there has been a growing interest in developing high-performance implementations of drug discovery processing software. To target modern GPU architectures, 
+such applications are mostly written in proprietary languages such as CUDA or HIP. However, with the increasing heterogeneity of modern HPC systems and the availability of 
+accelerators from multiple hardware vendors, it has become critical to be able to efficiently execute drug discovery pipelines on multiple large-scale computing systems, 
+with the ultimate goal of working on urgent computing scenarios. This article presents the challenges of migrating LiGen, an industrial drug discovery software pipeline, 
+from CUDA to the SYCL programming model, an industry standard based on C++ that enables heterogeneous computing. We perform a structured analysis of the performance portability 
+of the SYCL LiGen platform, focusing on different aspects of the approach from different perspectives. First, we analyze the performance portability provided by the high-level semantics 
+of SYCL, including the most recent group algorithms and subgroups of SYCL 2020. Second, we analyze how low-level aspects such as kernel occupancy and register pressure affect 
+the performance portability of the overall application. The experimental evaluation is performed on two different versions of LiGen, implementing two different parallelization 
+patterns, by comparing them with a manually optimized CUDA version, and by evaluating performance portability using both known and ad hoc metrics. The results show that,
+thanks to the combination of high-level SYCL semantics and some manual tuning, LiGen achieves native-comparable performance on NVIDIA, while also running on AMD GPUs.