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Merged
mariogeiger merged 2 commits into from
Feb 17, 2026
Merged

prepare for v0.9.0 #252

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8b48da3
update changelog and version
mariogeiger Feb 17, 2026
e66293d
update third party list
mariogeiger Feb 17, 2026
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18 changes: 14 additions & 4 deletions CHANGELOG.md
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## Latest Changes
## (unreleased)

## 0.9.0 (unreleased)
## 0.9.0 (2026-02-17)

### Added
- GB10 (DGX Spark) support
- Support for Python 3.13 and 3.14
- [JAX] Support for Triton 3.6.0
- [JAX] `flax.nnx` MACE example
- [Torch/JAX] Deterministic indexing mode for uniform 1d kernels
- [Torch/JAX] Parallel JIT compilation for uniform_1d kernels with per-kernel caching, significantly reducing compilation time. New optional environment variable `CUEQUIVARIANCE_OPS_NVRTC_CACHE_DIR` allows setting a directory for caching compiled kernels.
- Documentation: new tutorials for JAX and PyTorch segmented polynomials

### Bug fix
- [JAX] Fixed Triton tuning issue for triangular multiplicative update
- [JAX] Compatibility with JAX 0.8.2: fixed FFI interface and dtype casting issues when x64 mode is not enabled
- [JAX] Improved triangle attention error messages
- [Torch/JAX] Fixed `yx_rotation` descriptor
- [Torch] TensorRT QDP plugin workaround

### Breaking Changes
- [Torch/JAX] The environment variable `CUEQUIVARIANCE_OPS_USE_JIT` no longer exists. JIT compilation is now the default behavior for uniform_1d kernels (already since few releases).
- [Torch/JAX] Renamed `filter_drop_unsued_operands` to `filter_drop_unused_operands` (typo fix)
- [Torch/JAX] Removed `nvfatbin` optional dependency
- [Torch] Removed deprecated primitive classes: `TensorProduct`, `EquivariantTensorProduct`, `SymmetricTensorProduct`, and `IWeightedSymmetricTensorProduct`. Use `cuet.SegmentedPolynomial` with `method='uniform_1d'` instead, or the high-level APIs (`cuet.ChannelWiseTensorProduct`, `cuet.FullyConnectedTensorProduct`, `cuet.SymmetricContraction`). Attempting to import these classes will raise an `ImportError` with migration instructions.
- [Torch] Removed deprecated low-level wrapper classes: `TensorProductUniform1d`, `TensorProductUniform4x1d`, `TensorProductUniform3x1dIndexed`, `TensorProductUniform4x1dIndexed`, and `SymmetricTensorContraction` from `cuequivariance_ops_torch`. Use `torch.ops.cuequivariance.uniform_1d` or `cuet.SegmentedPolynomial` instead.

### Notes
- [JAX] DGX Spark/GB10 (sm_121) with CUDA 12.9: This release uses PTX 87, which works correctly for most architectures but is not compatible with DGX Spark/GB10 on CUDA 12.9. To enable DGX Spark/GB10 support with CUDA 12.9, refer to [#250](https://github.com/NVIDIA/cuEquivariance/pull/250) for a simple frontend integration tweak that restricts PTX 88 to sm_121 only. This fix will be merged after the 0.9.0 release.

### Added
- [Torch/JAX] New environment variable `CUEQUIVARIANCE_OPS_NVRTC_CACHE_DIR` allows setting a directory for caching compiled kernels, improving JIT compilation time for uniform_1d kernels.

## 0.8.1 (2026-01-09)

### Bug fix
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