GitLab

* Initial implementation of C++ API

* Add kernel interface and information for API generation

* API updates for updating electrode parameters

* Add serialization proxy for ConstantPotentialForce

* Update file headers

* Add CG error tolerance and fix units on getCharges() return value

* Initial implementation of matrix solver

* Fixes and conjugate gradient solver

* Try to fix Linux and Windows builds

* Make sure charge constraint target is on total charge

* Restore handling of exceptions like NonbondedForce since they won't involve electrode atoms

* Ameliorate numerical instability in constrained conjugate gradient

* Fix uninitialized pointers, memory leak, and style

* Set CG tolerance units in Python API

* Test ConstantPotentialForce serialization

* Read/write ExceptionsUsePeriodicBoundaryConditions as bool

* Improve constrained conjugate gradient robustness to roundoff error accumulation

* Recompute matrix if electrode atoms move due to setPositions()

* Tolerance is now in gradient (potential) units again

* Add neutralizing background correction

* Add Python API tests

* Fixes for CG and nonbonded exceptions

* Add initial tests checking against existing NonbondedForce behavior

* Expand test suite and fix some implementation issues

* Add additional tests using larger reference system

* Add Gaussian test

* Finish test against reference computation

* CPU platform implementation

* Fixes for compilation on some platforms

* Fixes for constant potential with AVX/AVX2

* Test linking CPU PME library to constant potential test directly

* Older SWIG versions don't support Python set to C++ set conversion

* Add user guide entry

* Increase speed of reference test

* Conditional building constant potential CPU test is unreliable

* Debugging

* Miscellaneous fixes and improvements for CI

* Cache charges so solver will not run if system and coordinates have not changed

* Preconditioner flag, stability, and automatic detection improvements

* Add GPU platform-specific constant potential kernel classes

* PME and device-host I/O changes to support constant potential

* Initial common constant potential implementation

* Constant potential fixes:

* Fix preconditioner PME position/charge save/restore logic

* Fix reduction synchronization in constant potential solver kernels

* Add double-float accumulation for conjugate gradient solver when
  double unsupported by hardware

* Improve conditioning of a test system, and make sure particles are in or
out of cutoff for consistency and ease of comparing between platforms

* Reorder guess charges for CG when atom reordering changes positions

* Remove PME queue for now

* Trying to debug optimized direct space derivative kernel

* Remove extraneous debugging lines

* Style updates; just make CPU preconditioner double precision

* Debugging updated optimized direct derivatives kernel for all but OpenCL CPU

* OpenCL CPU implementation of direct space derivatives, and cleanup

* Try to make test even shorter to not time out on CI

* Temporary - Debugging

* Debugging

* Debugging

* Debugging

* Debugging

* Remove debugging code and fix reduction synchronization

* Fix other reductions

* Debugging - are tests hanging or just slow on CI?

* Debugging

* Debugging

* Fix macro for case when double precision is available on hardware

* Remove changes for debugging again

* Try to improve matrix solver cache locality by uploading transpose

* Fixes for atom ordering and periodic images

* Can't rely on reorder listener for cell offset updates

* Test reducing number of contexts and timing for CI

* Debugging

* Remove timing code and revert debugging changes

* Matrix solver and plasma term optimizations

* Reduce CG solver kernel calls and downloads

* Don't read back convergence flag from global memory

* Update PME due to refactoring in master branch

* Faster matrix solver (1st step)

* Faster matrix solver for CUDA

* Faster matrix solver compatibility with non-CUDA platforms

* Matrix solver fixes

* Use warp shuffle reductions when possible

* Attempt to work around intermittent compiler crash in Intel CPU OpenCL

* Optimize CG solver kernel 1

* Rework CG solver so some kernels can use more than 1 block

* Don't run out of shared memory

* Asynchronously download convergence flag while clearing buffers

---------
Co-authored-by: Evan Pretti <pretti@sh03-17n15.int>

* Use fixed point spread charge on RDNA4 as it is faster

Even though RDNA4 (gfx12) has global_atomic_add_f32, micro-benchmarks and OpenMM benchmarks show
that it is very slow compared to global_atomic_add_u64.

* Add a workaround for fixed point gridSpreadCharge on RDNA4

Workaround for rare cases when few values of pmeGrid are very large and
incorrect. The cause is unknown. Why this workaround or other irrelevant
changes like printf help is also unknown.

* PME_ORDER threads process one atom;
* PME_ORDER threads access consecutive addresses;
* No need to permute z indices with zindexTable;
* finishSpreadCharge is needed only with fixed point charge spreading;

* Support kernel files with extensions of any length (like .hip)

* Do not allow to replace symbols in single-line comments

* Add OPENMM_BUILD_COMMON CMake option

It allows to build and install common platform files even if
CUDA or OpenCL platforms are not built.
This is required for HIP platform (openmm-hip) if ROCm OpenCL
packages are not installed.

* Add an option for Python wrapper to install into user packages

OPENMM_PYTHON_USER_INSTALL is OFF be default.

* Support FFT backends in Amoeba plugin

The HIP platform supports FFT backends, this commit moves
findLegalFFTDimension to ComputeContext, so platforms can have their own
implementations.

* Compatibility for common platform w/ new HIP platform

* Do not use volatile with private and local AtomData parameters on HIP

The generated code is not optimal, for example, the compiler generates
flat_load instructions instead of ds_read.

* Tune launch bounds for PME grid-related kernels and add WA for RDNA

Force the compiler to use all registers for gridSpreadCharge and
gridInterpolateForce by limiting max waves per EU to 1 on CDNA GPUs,
RDNA GPUs work better without it.

* Optimize atom data structs in GBSA and Amoeba on HIP

Manually rearrange fields, add paddings and force alignments to
have faster accesses to shared memory: ds_read and ds_write may
work slower if addresses are not aligned by 16 bytes.
Co-authored-by: Anton Gorenko <anton@streamhpc.com>
Co-authored-by: Nick Curtis <nicholas.curtis@amd.com>

It allows to use a faster float-to-int64 in the HIP platform.

* Began converting AMOEBA to common platform

* Beginning of OpenCL platform for AMOEBA

* Converted AmoebaVdwForce to common platform

* Cleaned up reference AMOEBA tests

* Began converting AmoebaMultipoleForce to common platform

* Continue converting AmoebaMultipoleForce to common platform

* Bug fixes

* Bug fix

* Continue converting AmoebaMultipoleForce to common platform

* Converting AmoebaMultipoleForce and AmoebaGeneralizedKirkwoodForce to common platform

* Converting AmoebaMultipoleForce and AmoebaGeneralizedKirkwoodForce to common platform

* Creating OpenCL version of AmoebaMultipoleForce and AmoebaGeneralizedKirkwoodForce

* Creating OpenCL version of AmoebaMultipoleForce and AmoebaGeneralizedKirkwoodForce

* Creating OpenCL version of AmoebaMultipoleForce and AmoebaGeneralizedKirkwoodForce

* Converted arrays from real3 to real

* Bug fix to OpenCL AmoebaGeneralizedKirkwoodForce

* Fixes for AMD GPUs

* Began converting HippoNonbondedForce to common platform

* Continuing to convert HippoNonbondedForce to common platform

* Continuing to convert HippoNonbondedForce to common platform

* Working on unifying PME kernels

* Fixed error on devices without 64 bit atomics

* Unified PME kernels

* Converted HippoNonbondedForce to common platform

* Creating OpenCL implementation of HippoNonbondedForce

* Continuing OpenCL implementation of HippoNonbondedForce

* Mostly finished OpenCL implementation of HippoNonbondedForce

* Eliminated three component vector types in host code

* Fix errors on CPU OpenCL

* Skip double precision tests for AMOEBA on OpenCL

* Bug fixes

* Bug fixes

* Fixed compilation error

When converting to fixed point, multiply by 0x100000000 instead of 0xFFFFFFFF.  This should be (very very slightly) more accurate, since its reciprocal can be exactly represented in floating point.