Tags: romesco/warp
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v1.6.1 Highlights: - Fix unaligned loads with offset 2D tiles in `wp.tile_load()`. - Fix FP64 accuracy of thread-level matrix-matrix multiplications. - Fix per-vertex colors not being correctly written out to USD meshes when a constant color is being passed. - Fix an error in capturing the `wp.sim.VBDIntegrator` with CUDA graphs when `handle_self_contact` is enabled. See the full changelog for more details: https://github.com/NVIDIA/warp/releases/tag/v1.6.1
v1.6.0 Highlights: - Add preview of Tile Cholesky factorization and solve APIs. - Support for loading tiles from arrays whose shapes are not multiples of the tile dimensions. - Support for higher-dimensional (up to 4D) tile shapes and memory operations. - Add intersection-free self-contact support in wp.sim.VDBIntegrator. - Support CUDA IPC on Linux. See the full changelog for more details: https://github.com/NVIDIA/warp/releases/tag/v1.6.0
v1.5.1 Highlights: - warp.sim: Fix a bug in which the color-balancing algorithm was not updating the colorings. - Fix custom colors being not being updated when rendering meshes with static topology in OpenGL. - Fix default arguments not being resolved for `wp.func` when called from Python's runtime. - Fix the OpenGL renderer not being able to run without a CUDA device available. - Fix incorrect CUDA driver function versions. See the full changelog for more details: https://github.com/NVIDIA/warp/releases/tag/v1.5.1
v1.5.0 Highlights: - Support for cooperative tile-based primitives using cuBLASDx and cuFFTDx - Support for saving Volumes into `.nvdb` files with the `save_to_nvdb` method. - Drop support for Python 3.7; Python 3.8 is now the minimum-supported version. - warp.fem: Add Nédélec (first kind) and Raviart-Thomas vector-valued function spaces providing conforming discretization of `curl` and `div` operators, respectively. - warp.sim: Add a graph coloring module that supports converting trimesh into a vertex graph and applying coloring. See the full changelog for more details: https://github.com/NVIDIA/warp/releases/tag/v1.5.0
v1.4.2: Patch release with bug fixes See CHANGELOG.md for details - Make the output of `wp.print()` in backward kernels consistent for all supported data types. - Fix printing vector and matrix adjoints in backward kernels. - Fix kernel compile error when printing structs. - Fix an incorrect user function being sometimes resolved when multiple overloads are available with array parameters with different `dtype` values. - Fix error being raised when static and dynamic for-loops are written in sequence with the same iteration variable names (NVIDIA#331). - Fix code generation of in-place multiplication and division operations (regression introduced in a69d061)(NVIDIA#342).
v1.4.1: Patch release with bug fixes - Fix `iter_reverse()` not working as expected for ranges with steps other than 1 (NVIDIA#311). - Fix potential out-of-bounds memory access when a `wp.sparse.BsrMatrix` object is reused for storing matrices of different shapes. - Fix robustness to very low desired tolerance in `wp.fem.utils.symmetric_eigenvalues_qr`. - Fix invalid code generation error messages when nesting dynamic and static for-loops. - Fix caching of kernels with static expressions. - Fix `ModelBuilder.add_builder(builder)` to correctly update `articulation_start` and thereby `articulation_count` when `builder` contains more than one articulation. - Re-introduced the `wp.rand*()`, `wp.sample*()`, and `wp.poisson()` onto the Python scope to revert a breaking change.
v1.4.0: Feature release See CHANGELOG.md for details - Support for a new wp.static(expr) function that allows arbitrary Python expressions to be evaluated at the time of function/kernel definition - Interoperability support for the PaddlePaddle ML framework - Improved Jax interop support for sharding and matrix multiplication - Numerous fixes related to kernel, function, and struct management
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