v0.28.1-rc1

• Improved cuda performance for 512 filter networks on Amprere GPUs.
• Several fixes for the onnx backend.
• Command line options for network file conversion to/from onnx.
• Documentation updates.
• Correctness fixes for rescorer support functions.

v0.28.0

In this release:

• Multigather is now made the default (and also improved). Some search settings have changed meaning, so if you have modified values please discard them. Specifically, max-collision-events, max-collision-visits and max-out-of-order-evals-factor have changed default values, but other options also affect the search. Similarly, check that your GUI is not caching the old values.
• Updated several other default parameter values, including the MLH ones.
• Performance improvements for the cuda/cudnn backends. This includes the multi_stream cuda backend option that is off by default. You should test adding multi_stream=true to backend-opts (command line) or BackendOptions (UCI) if you have a recent GPU with a lot of VRAM.
• Support for policy focus during training.
• Larger/stronger 15b default net for all packages except android, blas and dnnl that get a new 10b network.
• The distributed binaries come with the mimalloc memory allocator for better performance when a large tree has to be destroyed (e.g. after an unexpected move).
• The legacy time manager is again the default and will use more time for the first move after a long book line.
• The --preload command line flag will initialize the backend and load the network during startup. This may help in cases where the GUI is confused by long start times, but only if backend and network are not changed via UCI options.
• A 'fen' command was added as a UCI extension to print the current position.
• Experimental onednn backend for recent intel CPUs and GPUs.
• Added support for ONNX network files and runtime with the onnx backend.
• Several bug and stability fixes.

Note: Some small third-party nets seem to play really bad with the dx12 backend and certain GPU drivers, setting the enable-gemm-metacommand=false backend option is reported to work around this issue.

v0.28.0-rc2

• The cuda backend option multi_stream is now off by default. You should
  consider setting it to on if you have a recent gpu with a lot of vram.
• Updated default parameters.
• Newer and stronger nets are included in the release packages.
• Added support for onnx network files and runtime with the "onnx" backend.
• Several bug and stability fixes.

v0.28.0-rc1

• Multigather is now made the default (and also improved). Some search settings
  have changed meaning, so if you have modified values please discard them.
  Specifically, max-collision-events, max-collision-visits and
  max-out-of-order-evals-factor have changed default values, but other options
  also affect the search. Similarly, check that your gui is not caching the old
  values.
• Performance improvements for the cuda/cudnn backends.
• Support for policy focus during training.
• Larger/stronger 15b default net for all packages except android, blas and dnnl
  that get a new 10b network.
• The distributed binaries come with the mimalloc memory allocator for better
  performance when a large tree has to be destroyed (e.g. after an unexpected
  move).
• The legacy time manager will use more time for the first move after a long
  book line.
• The --preload command line flag will initialize the backend and load the
  network during startup.
• A 'fen' command was added as a UCI extension to print the current position.
• Experimental onednn backend for recent intel cpus and gpus.

v0.27.0

• A better value for the backendbench Clippy threshold.

v0.27.0-rc2

• Fix additional cases where 'invalid move' could be incorrectly reported.
• Replace WDL softmax in cudnn backend with same implementation as cuda
  backend. This fixes some inaccuracy issues that were causing training
  data to be rejected at a fairly low frequency.
• Ensure that training data Q/D pairs form valid WDL targets even if there
  is accumulated drift in calculation.
• Fix for the calculation of the 'best q is proven' bit in training data.
• Multiple fixes for timelosses and infinite instamoving in smooth time
  manager. Smooth time manager now made default after these fixes.

v0.27.0-rc1

• Fix a bug which meant position ... moves ... didn't work if the moves went off the end of the existing tree. (Which happens normally when playing from an opening book.)

v0.27.0-rc0

Note: This version is very broken, do not attempt use it.

• Multigather search inspired by Ceres. (Default is off. Note that the meaning of max-collision-events changes considerably when enabled and max-collision-visits will need to be set to a value close to previous values of max-collision-events in order to have similar search behavior.)
• V6 training format with additional info for training experiments.
• Updated default search parameters.
• A better algorithm for the backendbench assistant.
• Terminate search early if only 1 move isn't a proven loss.
• Various build system changes.

v0.26.3

Starting with this release, we are distributing two packages for windows with Nvidia GPUs: the cuda package and the cudnn package. The cudnn package is what we used to distribute so far (but we called it cuda), and comes with the same versions of cuda and cudnn dlls we were using for the last few months. The new cuda package comes with cuda 11.1 dlls and requires at least version 456.38 of the windows Nvidia drivers, and should give better performance on RTX cards and in particular the new RTX 30XX cards.

Notes:

1. The cudnn package will work as-is in existing setups, but for the cuda package you may have to replace cudnn with cuda (or cuda-auto or cuda-fp16) as a backend (if specified) - this will certainly be necessary for multi-gpu setups.
2. Some testing indicates that cuda 11.1 may be slower for GTX 10XX cards, so owners of older cards may want to stay with the cudnn package. If your testing shows otherwise do let us know.

v0.26.3-rc2

• Fix for uninitialized variable that led to crashes with the cudnn backend.
• Correct windows support for systems with more than 64 threads.
• A new package is built for the cuda backend with cuda 11.1. The old cuda package is renamed to cudnn.

Note: The cuda package requires nvidia driver 456.38 or newer.