Virtual Molecule Screening (VMS) is a computational technique used in drug discovery that uses machine learning to predict if a chemical compound is likely to bind to a drug target.
This repo contains several implementations of VMS generated from a Matrix Factorization model built by SMURFF
- vms/pure_c: pure C with OmpSs, OpenMP, MPI, GASPI, and ArgoDSM
- vms/af_py: Python ArrayFire implementation for CUDA, OpenCL and MKL
- vms/af_cpp: C++ ArrayFire implementation for CUDA, OpenCL and MKL
- vms/openacc: OpenACC implementation, with and witouth OmpSs
- vms/smurfference: Python NumPy, Tensorflow implementation
- vms/fpga: Xilinx FPGA implementation, with OpenCL and with OmpSs@FPGA