SparkleDock: Scalable High-Fidelity Macromolecular Docking for GPU-Accelerated Supercomputers(AE)

Overview

SparkleDock is a GPU-native Glowworm Swarm Optimization (GSO) docking system, enabling large-scale flexible macromolecule docking. It supports:

• A fine-grained, glowworm-level parallelization to match the SM in GPU.

• TensorCore-accelerated CUDA kernel design to enhance the computing efficiency.

• Efficient MPI design to adaptively scale across multi-GPU systems.

SparkleDock can accelerate the macromolecule docking by over two orders of magnitude compared to the existing flexible macromolecule docking.

Install SparkleDock

Requirements

software requirements

openmpi/4.1.5
cuda/11.8.0 
gcc/11.3.0
cmake/3.16.5

Hardware requirements

NVIDIA GPU or multi-GPU supercomputers.

Benchmark dataset

The table below shows the benchmark dataset from The Protein-Protein Benchmark 5 and Affinity Benchmark Version 2 (BM5). The Category denotes the macromolecule type: antibody-antigen (A); enzyme–inhibitor (EI); enzyme–substrate (ES); enzyme complex with a regulatory or accessory chain (ER); others, G-protein containing (OG); others, receptor containing (OR); others, miscellaneous (OX). The Swarms denotes the calculated swarm number by GSO. The Rec Atoms and Lig Atoms denote the backbone atom number.

Build the SparkleDock

Here is the build script 

cmake -S source -B build
cmake --build build --parallel 8 --verbose
cmake --install build

We also provide a build script, as shown in build.sh.

Execute the SparkleDock

Single GPU execution

Here is an example of the docking on a single GPU.

#!/bin/bash
dock_home=`pwd`
if [ -z $dock_home ]
then
    echo "not found envoriment variable : dock_home"
fi
set -ex
declare -a stringArray
stringArray=("4LW4" "2VXT" "1RKE" "2A1A" "2GTP" "2X9A" "3LVK" "3VLB" "4GAM" "4JCV")
HOME=$dock_home/bm/
STEPS=100
export LD_LIBRARY_PATH=$dock_home/lib:$LD_LIBRARY_PATH
export NUM_THREADS=32
export USE_CUDA=1
for str in "${stringArray[@]}"; do

echo "prepare $str" >> ${HOME}measure.txt

COMPLEX=$str

echo ${HOME}${COMPLEX}
cd ${HOME}${COMPLEX}

mpirun -np 1 $dock_home/bin/sparkledock -f setup.json -s $STEPS -l 1 >> ${HOME}measure.txt

done

multi-GPU execution

Here is an example of the SparkleDock on multi-GPUs. {NPROC} denotes the number of GPUs in a single node.

#!/bin/bash
dock_home=`pwd`
if [ -z $dock_home ]
then
    echo "not found envoriment variable : dock_home"
fi
set -ex
declare -a stringArray
stringArray=("4LW4" "2VXT" "1RKE" "2A1A" "2GTP" "2X9A" "3LVK" "3VLB" "4GAM" "4JCV")
HOME=$dock_home/bm/
STEPS=100
export LD_LIBRARY_PATH=$dock_home/lib:$LD_LIBRARY_PATH
export NUM_THREADS=32
export USE_CUDA=1
for str in "${stringArray[@]}"; do
echo "prepare $str" >> ${HOME}measure.txt

COMPLEX=$str

echo ${HOME}${COMPLEX}
cd ${HOME}${COMPLEX}
# # Setup
rm -rf lightdock* init/ swarm_*

mpirun -np ${NPROC} $dock_home/bin/sparkledock -f setup.json -s $STEPS -l 1 >> ${HOME}measure.txt

done

load balance evaluation

Here is the load balance evaluation.

#!/bin/bash
dock_home=`pwd`
if [ -z $dock_home ]
then
    echo "not found envoriment variable : dock_home"
fi
set -ex
declare -a stringArray
stringArray=("4LW4" "2VXT" "1RKE" "2A1A" "2GTP" "2X9A" "3LVK" "3VLB" "4GAM" "4JCV")
HOME=$dock_home/bm/
STEPS=100
export LD_LIBRARY_PATH=$dock_home/lib:$LD_LIBRARY_PATH
export NUM_THREADS=32
export USE_CUDA=1
for str in "${stringArray[@]}"; do
echo "prepare $str" >> ${HOME}measure.txt

COMPLEX=$str

echo ${HOME}${COMPLEX}
cd ${HOME}${COMPLEX}
# # Setup
rm -rf lightdock* init/ swarm_*

mpirun -np ${NPROC} $dock_home/bin/sparkledock_lb -f setup.json -s $STEPS -l 1 >> ${HOME}measure.txt

done