GitLab

Improve the performance of sending the AmoebaVdwLambda to Cuda using pinned host memory; Updated the AmoebaVdwForceProxy to version 3, and added backward compatibility to version 2; updated TestAPIUnits.py to handle the per particle lambda flag

changed the type of the isAlchemical Cuda array to float, which is needed for the CudaNonbondedUtilities.addParameter method to work; the TestCudaAmoebaVdwForce now passes for its current set of tests, but new tests are needed to check the softcore behavior

Rough draft AmoebaVdwForce Cuda code; next steps are to add CUDA kernal compilation support for USE_SOFTCORE, VDW_LAMBDA, VDW_SOFTCORE_POWER, VDW_SOFTCORE_ALPHA, and per particle isAlchemicalI / isAlchemicalJ flags

Fixed units in swigInputConfig.py for new Alchemical AMOEBA vdW methods exposed in the OpenMM API; implemented the getDefaultParameters() on the AmoebaVdwForceImpl to return 1.0 for AmoebaVdwAlpha; Use AmoebaVdwForce::Lambda() to refer to this parameter rather than the String AmoebaVdwAlpha

AMOEBA vdW softcore is propogated through the Reference platform; pending some feedback adding it to the CUDA code can begin

for the AmoebaVdwLambda global parameter was added that returns the parameter's name; added the value None to the AlchemicalMethod enumeration; provided default values for the isAlchemical flag

* Created API for HIPPO force field

* Beginning of reference implementation of HIPPO

* Continuing reference implementation of HIPPO

* Continuing reference implementation of HIPPO

* Continuing reference implementation of HIPPO

* Continuing reference implementation of HIPPO

* Continuing reference implementation of HIPPO

* Continuing reference implementation of HIPPO

* Continuing reference implementation of HIPPO

* Completed reference of HIPPO with no cutoff

* Beginning cutoffs/PME for reference implementation of HIPPO

* Continuing PME for reference implementation of HIPPO

* Continuing PME for reference implementation of HIPPO

* Continuing PME for reference implementation of HIPPO

* Completed reference implementation of HIPPO

* Cleanup and optimization to HIPPO reference

* Further cleanup to HIPPO

* Combined direct space interactions into a single loop

* Compute direct space interactions in quasi-internal frame

* Beginning of CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Continuing CUDA implementation of HIPPO

* Finished CUDA implementation of HIPPO

* More features and test cases for HippoNonbondedForce

* Serialization and Python API for HippoNonbondedForce

* Fixed sign error in computing forces