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@c0d1f1ed c0d1f1ed released this 28 Jul 05:18
· 246 commits to main since this release
v1.3.1
12892f0

[1.3.1] - 2024-07-27

  • Remove wp.synchronize() from PyTorch autograd function example
  • Tape.check_kernel_array_access() and Tape.reset_array_read_flags() are now private methods.
  • Fix reporting unmatched argument types

[1.3.0] - 2024-07-25

  • Warp Core improvements

    • Update to CUDA 12.x by default (requires NVIDIA driver 525 or newer), please see README.md for commands to install CUDA 11.x binaries for older drivers
    • Add information to the module load print outs to indicate whether a module was
      compiled (compiled), loaded from the cache (cached), or was unable to be
      loaded (error).
    • wp.config.verbose = True now also prints out a message upon the entry to a wp.ScopedTimer.
    • Add wp.clear_kernel_cache() to the public API. This is equivalent to wp.build.clear_kernel_cache().
    • Add code-completion support for wp.config variables.
    • Remove usage of a static task (thread) index for CPU kernels to address multithreading concerns (GH-224)
    • Improve error messages for unsupported Python operations such as sequence construction in kernels
    • Update wp.matmul() CPU fallback to use dtype explicitly in np.matmul() call
    • Add support for PEP 563's from __future__ import annotations (GH-256).
    • Allow passing external arrays/tensors to wp.launch() directly via __cuda_array_interface__ and __array_interface__, up to 2.5x faster conversion from PyTorch
    • Add faster Torch interop path using return_ctype argument to wp.from_torch()
    • Handle incompatible CUDA driver versions gracefully
    • Add wp.abs() and wp.sign() for vector types
    • Expose scalar arithmetic operators to Python's runtime (e.g.: wp.float16(1.23) * wp.float16(2.34))
    • Add support for creating volumes with anisotropic transforms
    • Allow users to pass function arguments by keyword in a kernel using standard Python calling semantics
    • Add additional documentation and examples demonstrating wp.copy(), wp.clone(), and array.assign() differentiability
    • Add __new__() methods for all class __del__() methods to handle when a class instance is created but not instantiated before garbage collection
    • Implement the assignment operator for wp.quat
    • Make the geometry-related built-ins available only from within kernels
    • Rename the API-facing query types to remove their _t suffix: wp.BVHQuery, wp.HashGridQuery, wp.MeshQueryAABB, wp.MeshQueryPoint, and wp.MeshQueryRay
    • Add wp.array(ptr=...) to allow initializing arrays from pointer addresses inside of kernels (GH-206)

  • warp.autograd improvements:

    • New warp.autograd module with utility functions gradcheck(), jacobian(), and jacobian_fd() for debugging kernel Jacobians (docs)
    • Add array overwrite detection, if wp.config.verify_autograd_array_access is true in-place operations on arrays on the Tape that could break gradient computation will be detected (docs)
    • Fix bug where modification of @wp.func_replay functions and native snippets would not trigger module recompilation
    • Add documentation for dynamic loop autograd limitations

  • warp.sim improvements:

    • Improve memory usage and performance for rigid body contact handling when self.rigid_mesh_contact_max is zero (default behavior).
    • The mask argument to wp.sim.eval_fk() now accepts both integer and boolean arrays to mask articulations.
    • Fix handling of ModelBuilder.joint_act in ModelBuilder.collapse_fixed_joints() (affected floating-base systems)
    • Fix and improve implementation of ModelBuilder.plot_articulation() to visualize the articulation tree of a rigid-body mechanism
    • Fix ShapeInstancer __new__() method (missing instance return and *args parameter)
    • Fix handling of upaxis variable in ModelBuilder and the rendering thereof in OpenGLRenderer

  • warp.sparse improvements:

    • Sparse matrix allocations (from bsr_from_triplets(), bsr_axpy(), etc.) can now be captured in CUDA graphs; exact number of non-zeros can be optionally requested asynchronously.
    • bsr_assign() now supports changing block shape (including CSR/BSR conversions)
    • Add Python operator overloads for common sparse matrix operations, e.g A += 0.5 * B, y = x @ C

  • warp.fem new features and fixes:

    • Support for variable number of nodes per element
    • Global wp.fem.lookup() operator now supports wp.fem.Tetmesh and wp.fem.Trimesh2D geometries
    • Simplified defining custom subdomains (wp.fem.Subdomain), free-slip boundary conditions
    • New field types: wp.fem.UniformField, wp.fem.ImplicitField and wp.fem.NonconformingField
    • New streamlines, magnetostatics and nonconforming_contact examples, updated mixed_elasticity to use a nonlinear model
    • Function spaces can now export VTK-compatible cells for visualization
    • Fixed edge cases with NanoVDB function spaces
    • Fixed differentiability of wp.fem.PicQuadrature w.r.t. positions and measures
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