Accelerating Group Fusion for Ligand-Based Virtual Screening on Multi-core and Many-core Platforms

Abstract

The performance issues of screening large database compounds and multiple query compounds in virtual screening highlight a common concern in Chemoinformatics applications. This study investigates these problems by choosing group fusion as a pilot model and presents efficient parallel solutions in parallel platforms, specifically, the multi-core architecture of CPU and many-core architecture of graphical processing unit (GPU). A study of sequential group fusion and a proposed design of parallel CUDA group fusion are presented in this paper. The design involves solving two important stages of group fusion, namely, similarity search and fusion (MAX rule), while addressing embarrassingly parallel and parallel reduction models. The sequential, optimized sequential and parallel OpenMP of group fusion were implemented and evaluated. The outcome of the analysis from these three different design approaches influenced the design of parallel CUDA version in order to optimize and achieve high computation intensity. The proposed parallel CUDA performed better than sequential and parallel OpenMP in terms of both execution time and speedup. The parallel CUDA was 5-10x faster than sequential and parallel OpenMP as both similarity search and fusion MAX stages had been CUDA-optimized.

Advances in Multimedia Computing and Security and the Introduction of New Senior Editors

“…It introduces as a new image clustering method [1], community model for Smart TV [2], eigenspaces for extracting features from facial images [3], an interactive authoring tool for mobile augmented reality (AR) content [4], an image deblocking scheme for JPEG compressed images [5], an image-centric integrated data model of medical information by diseases [6], the sparsification of digital images [7], treatment planning in smart medical technology [8], the detection of Korean vehicle license plates [9], and the acceleration of group fusion on multi-cores [10]. This issue also includes advanced security research [11,12] on multimedia security, a novel DWT-SVD canny-based watermarking [13], and a blind color images watermarking [14].…”