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Graphtoy: Fast Software Simulation of Applications for AMD’s AI Engines

Jonathan Strobl, Leonardo Solis-Vasquez, Yannick Lavan, Andreas Koch

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Tags: ATI, Computer science, FPGA, molecular docking, Package

February 18, 2024 by hgpu

Out of kernel tuning and optimizations for portable large-scale docking experiments on GPUs

Gianmarco Accordi, Davide Gadioli, Emanele Vitali, Luigi Crisci, Biagio Cosenza, Andrea Beccari, Gianluca Palermo

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Tags: Computer science, CUDA, HPC, molecular docking, nVidia, nVidia A100, oneAPI, Performance, SYCL

February 12, 2024 by hgpu

Experiences Migrating CUDA to SYCL: A Molecular Docking Case Study

Leonardo Solis-Vasquez, Edward Mascarenhas, Andreas Koch

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Tags: Chemistry, Computer science, CUDA, molecular docking, nVidia, nVidia A100, oneAPI, Package, SYCL

May 28, 2023 by hgpu

Accelerating AutoDock VINA with GPUs

Shidi Tang, Ruiqi Chen, Mengru Lin, Qingde Lin, Yanxiang Zhu, Jiansheng Wu, Haifeng Hu, Ming Ling

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Tags: Chemistry, Databases, Heterogeneous systems, molecular docking, nVidia, nVidia GeForce GTX 1060, nVidia GeForce RTX 2080 Ti, nVidia GeForce RTX 3090, OpenCL, Package

October 17, 2021 by hgpu

Accelerating AutoDock4 with GPUs and Gradient-Based Local Search

Diogo Santos-Martins, Leonardo Solis-Vasquez, Andreas Koch, and Stefano Forli

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Tags: Algorithms, Chemistry, Macromolecule, molecular docking, OpenCL, Package, Physics

February 28, 2021 by hgpu

GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research

Scott LeGrand, Aaron Scheinberg, Andreas F. Tillack, Mathialakan Thavappiragasam, Josh V. Vermaas, Rupesh Agarwal, Jeff Larkin, Duncan Poole, Diogo Santos-Martins, Leonardo Solis-Vasquez, Andreas Koch, Stefano Forli, Oscar Hernandez, Jeremy C. Smith, Ada Sedova

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Tags: Biology, Biomolecules, Computational biology, CUDA, molecular docking, nVidia, nVidia DGX-2, nVidia GeForce RTX 2080 Ti, OpenCL, supercomputer, Tesla V100

July 12, 2020 by hgpu

Evaluating the Energy Efficiency of OpenCL-accelerated AutoDock Molecular Docking

Leonardo Solis-Vasquez, Diogo Santos-Martins, Andreas Koch, Stefano Forli

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Tags: AMD Radeon RX Vega 56, ATI, Biology, Chemistry, Energy-efficient computing, Heterogeneous systems, molecular docking, nVidia, OpenCL, Tesla V100

March 1, 2020 by hgpu

Exploiting OpenMP & OpenACC to Accelerate a Molecular Docking Mini-App in Heterogeneous HPC Nodes

Emanuele Vitali, Davide Gadioli, Gianluca Palermo, Andrea Beccari, Carlo Cavazzoni, Cristina Silvano

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Tags: Computer science, CUDA, Heterogeneous systems, HPC, molecular docking, MPI, nVidia, OpenACC, OpenMP, Tesla K80

January 27, 2019 by hgpu

Exploiting Multi-level Parallelism on a Many-core System for the Application of Hyperheuristics to a Molecular Docking Problem

Jose M. Cecilia, Jose-Matias, Cutillas-Lozano, Domingo Gimenez, Baldomero Imbernon

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Tags: Bioinformatics, Biology, Chemistry, Intel Xeon Phi, Metaheuristics, molecular docking

March 20, 2017 by hgpu

Calculation of Force Field Grids for Molecular Docking Using Graphics Processing Unit

Mikhail A. Farkov

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Tags: Algorithms, Bioinformatics, Biology, CUDA, molecular docking, nVidia, nVidia GeForce GT 440, Tesla K20, Tesla M2090

September 24, 2014 by hgpu

High performance in silico virtual drug screening on many-core processors

Simon McIntosh-Smith, James Price, Richard B Sessions, Amaurys A Ibarra

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Tags: GPU, molecular docking, OpenCL, performance portability, virtual screening, Xeon Phi

April 11, 2014 by simonmcs

QArray

QArray: a GPU-accelerated constant capacitance model simulator for large quantum dot arrays

Celerity: High-level C++ for Accelerator Clusters

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

Parallel Gaussian process with kernel approximation in CUDA

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

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