Skip to content

Releases: deepmodeling/deepmd-kit

v2.0.0-beta.3

05 Jul 00:42
de428e3
Compare
Choose a tag to compare
v2.0.0-beta.3 Pre-release
Pre-release

New feature:

  • derivatives for deep tensor (#805)

Performance improvement:

  • speedup ROCm kernels which use atomicAdd (#809 #815 ) (from ByteDance)
  • speedup CUDA kernels (use atomicAdd inside) by reducing the global memory write (#811)

Enhancement:

  • add type-embedding developer doc (#762)
  • add model compression support for models with exclude_types feature (#754)
  • improve the doc and user interface of model compression (#772)
  • allow c++ tests to run without internet (#785)
  • support converting models generated in v1.3 to 2.0 compatibility (#725)
  • give a default value to T and convert models from v1.2 to 2.0 compatibility (#789)
  • improved documents for conda (#798)
  • throw a message if tf runtime is incompatible (#797)
  • capture OOM and print debug message (#801)

Bug fixings

  • fix bug of custom op's multiple initialization (#812)
  • fix bug of empty input in gelu.cu (#800)
  • fix model compression bug of zero environment matrix (#808)
  • box.npy is not necessary for nopbc (#810)
  • fill rij with zero (#818)
  • NOT_LOADABLE should be tuple (#825)

v2.0.0-beta.2

15 Jun 23:44
c200e9a
Compare
Choose a tag to compare
v2.0.0-beta.2 Pre-release
Pre-release

New features:

  • Add subcommand and python interface to calculate model-deviation (#715)

Enhancements

  • Use fmod to wrap the coord of atoms. UT for force/virial ops (#741)
  • UT for model devi C++ interface (#731)
  • add CUDA/ROCM buidling documents (#739)
  • add op unittests for prod_force, prod_virial, prod_force_grad and prod_virial_grad (#703)

Bug fixings:

  • fix bug of adding int to a None random seed (#705)
  • reuse the zero layer rather than building a new one (#714)
  • fix CI (#739)

v2.0.0-beta.1

03 Jun 08:14
ab7621e
Compare
Choose a tag to compare
v2.0.0-beta.1 Pre-release
Pre-release

New hardware support:

  • ROCM support

Enhancement:

  • Document and examples for the C++ interface
  • Instructions for the i-pi
  • Document for the network size and sel

Bug fixing:

  • Illegal nlist #680
  • Bug in prod_virial_grad that causes wrong results when training with virials #685
  • Uniform random seed #691

v2.0.0-beta.0

20 May 00:11
363f9ba
Compare
Choose a tag to compare
v2.0.0-beta.0 Pre-release
Pre-release

Increment to v2.0.0-alpha:

New features:

  • Atom type embedding
  • Model deviation for virial

Enhancement:

  • Improved documentation
  • Better support for dipole and polarizability learning
  • bit operations to encode neighbor information
  • MPI support for atomic model deviation #628
  • UT for GPU code #569
  • UT for model compression #586
  • Test Lammps build #600

Bug fixings

  • cuda memory access error #566
  • relative force model deviation is not copied back at single precision #599
  • correct way of allocating memory in float precision #612
  • fix TB logdir remove bug #617
  • Append out_file when lammps restarts #640

v2.0.0-alpha.1

21 Apr 05:33
a5cb130
Compare
Choose a tag to compare
v2.0.0-alpha.1 Pre-release
Pre-release

What's new to v2.0.0-alpha.0

  • Training and inference the dipole (vector).
  • Split of training and validation dataset.

Enhancement:

  • Strict argument check in the input script.
  • Update readme for v2.0
  • Auto conversion of input file to v2.0 compatibility

Bug fixings:

  • Fix bugs of broken examples.

v2.0.0-alpha.0

13 Apr 07:38
15fe795
Compare
Choose a tag to compare
v2.0.0-alpha.0 Pre-release
Pre-release

The very first alpha release of deepmd-kit version 2.0.0. It includes the following new features

  • Model compression
  • New descriptor: three body embedding
  • Hybridization of descriptors
  • Long-range modification
  • Type embedding (under development)
  • Training and inference the dipole (vector) and polarizability (matrix). (under development)
  • Split of training and validation dataset. (under development)
  • ROCm device support (under development)

Enhancements

  • More efficient training: all customized OPs are implemented with GPU.
  • Parallel training with multiple GPU support (under development)

Improvement of the code for developers

  • Supports version of the model. Easily check model compatability
  • Clear and pythonic python interface
  • C++ API that can be tested independently
  • OP supports multi-device.

Bug fixings:

  • remove using namespace std. Solves compiling compatability problem.
  • added deepmd namespace for the C++ API

v1.3.3

23 Mar 01:24
3a59596
Compare
Choose a tag to compare

Bug fixing:

  • Fix lammps memory leak when initialized pair_style deepmd for multiple times. #392
  • Fix GPU memory issues. #393 #407 #424

v1.3.2

02 Mar 00:55
2644cca
Compare
Choose a tag to compare

Improvements:

  • Compiling with Cuda 11.0 and 11.1 #390

Bug fixings:

  • Fix stress tensor bug of ASE interface #338
  • Fix neighbor list bug that may cause inconsistent results between CPU and GPU #334

v1.2.4

24 Feb 14:52
c3dff7c
Compare
Choose a tag to compare

Bug fixings

  • Fix several compiling issues of v1.2.3

v1.2.3

21 Feb 22:32
d7c4fc2
Compare
Choose a tag to compare

New feature:

  • added tool to convert a v1.2 compatible model to v1.3 compatible model.

Bug fixing:

  • neighbor list bug in the GPU implementation.