v1.3.2

[1.3.2] - 2024-08-30

• Bug fixes
  • Fix accuracy of 3x3 SVD wp.svd3 with fp64 numbers (GH-281).
  • Fix module hashing when a kernel argument contained a struct array (GH-287).
  • Fix a bug in wp.bvh_query_ray() where the direction instead of the reciprocal direction was used
    (GH-288).
  • Fix errors when launching a CUDA graph after a module is reloaded. Modules that were used during graph capture
    will no longer be unloaded before the graph is released.
  • Fix a bug in wp.sim.collide.triangle_closest_point_barycentric() where the returned barycentric coordinates may be
    incorrect when the closest point lies on an edge.
  • Fix 32-bit overflow when array shape is specified using np.int32.
  • Fix handling of integer indices in the input_output_mask argument to autograd.jacobian and
    autograd.jacobian_fd (GH-289).
  • Fix ModelBuilder.collapse_fixed_joints() to correctly update the body centers of mass and the
    ModelBuilder.articulation_start array.
  • Fix precedence of closure constants over global constants.
  • Fix quadrature point indexing in wp.fem.ExplicitQuadrature (regression from 1.3.0).
• Documentation improvements
  • Add missing return types for built-in functions.
  • Clarify that atomic operations also return the previous value.
  • Clarify that wp.bvh_query_aabb() returns parts that overlap the bounding volume.

[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)

v1.3.1

[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

v1.3.0

[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

v1.2.2

[1.2.2] - 2024-07-04

• Support for NumPy >= 2.0

[1.2.1] - 2024-06-14

• Fix generic function caching
• Fix Warp not being initialized when constructing arrays with wp.array()
• Fix wp.is_mempool_access_supported() not resolving the provided device arguments to wp.context.Device

[1.2.0] - 2024-06-06

• Add a not-a-number floating-point constant that can be used as wp.NAN or wp.nan.
• Add wp.isnan(), wp.isinf(), and wp.isfinite() for scalars, vectors, matrices, etc.
• Improve kernel cache reuse by hashing just the local module constants. Previously, a
  module's hash was affected by all wp.constant() variables declared in a Warp program.
• Revised module compilation process to allow multiple processes to use the same kernel cache directory.
  Cached kernels will now be stored in hash-specific subdirectory.
• Add runtime checks for wp.MarchingCubes on field dimensions and size
• Fix memory leak in wp.Mesh BVH (GH-225)
• Use C++17 when building the Warp library and user kernels
• Increase PTX target architecture up to sm_75 (from sm_70), enabling Turing ISA features
• Extended NanoVDB support (see warp.Volume):
  • Add support for data-agnostic index grids, allocation at voxel granularity
  • New wp.volume_lookup_index(), wp.volume_sample_index() and generic wp.volume_sample()/wp.volume_lookup()/wp.volume_store() kernel-level functions
  • Zero-copy aliasing of in-memory grids, support for multi-grid buffers
  • Grid introspection and blind data access capabilities
  • warp.fem can now work directly on NanoVDB grids using warp.fem.Nanogrid
  • Fixed wp.volume_sample_v() and wp.volume_store_*() adjoints
  • Prevent wp.volume_store() from overwriting grid background values
• Improve validation of user-provided fields and values in warp.fem
• Support headless rendering of wp.render.OpenGLRenderer via pyglet.options["headless"] = True
• wp.render.RegisteredGLBuffer can fall back to CPU-bound copying if CUDA/OpenGL interop is not available
• Clarify terms for external contributions, please see CONTRIBUTING.md for details
• Improve performance of wp.sparse.bsr_mm() by ~5x on benchmark problems
• Fix for XPBD incorrectly indexing into of joint actuations joint_act arrays
• Fix for mass matrix gradients computation in wp.sim.FeatherstoneIntegrator()
• Fix for handling of --msvc_path in build scripts
• Fix for wp.copy() params to record dest and src offset parameters on wp.Tape()
• Fix for wp.randn() to ensure return values are finite
• Fix for slicing of arrays with gradients in kernels
• Fix for function overload caching, ensure module is rebuilt if any function overloads are modified
• Fix for handling of bool types in generic kernels
• Publish CUDA 12.5 binaries for Hopper support, see https://github.com/nvidia/warp?tab=readme-ov-file#installing for details

v1.2.1

[1.2.1] - 2024-06-14

• Fix generic function caching
• Fix Warp not being initialized when constructing arrays with wp.array()
• Fix wp.is_mempool_access_supported() not resolving the provided device arguments to wp.context.Device

[1.2.0] - 2024-06-06

• Add a not-a-number floating-point constant that can be used as wp.NAN or wp.nan.
• Add wp.isnan(), wp.isinf(), and wp.isfinite() for scalars, vectors, matrices, etc.
• Improve kernel cache reuse by hashing just the local module constants. Previously, a
  module's hash was affected by all wp.constant() variables declared in a Warp program.
• Revised module compilation process to allow multiple processes to use the same kernel cache directory.
  Cached kernels will now be stored in hash-specific subdirectory.
• Add runtime checks for wp.MarchingCubes on field dimensions and size
• Fix memory leak in wp.Mesh BVH (GH-225)
• Use C++17 when building the Warp library and user kernels
• Increase PTX target architecture up to sm_75 (from sm_70), enabling Turing ISA features
• Extended NanoVDB support (see warp.Volume):
  • Add support for data-agnostic index grids, allocation at voxel granularity
  • New wp.volume_lookup_index(), wp.volume_sample_index() and generic wp.volume_sample()/wp.volume_lookup()/wp.volume_store() kernel-level functions
  • Zero-copy aliasing of in-memory grids, support for multi-grid buffers
  • Grid introspection and blind data access capabilities
  • warp.fem can now work directly on NanoVDB grids using warp.fem.Nanogrid
  • Fixed wp.volume_sample_v() and wp.volume_store_*() adjoints
  • Prevent wp.volume_store() from overwriting grid background values
• Improve validation of user-provided fields and values in warp.fem
• Support headless rendering of wp.render.OpenGLRenderer via pyglet.options["headless"] = True
• wp.render.RegisteredGLBuffer can fall back to CPU-bound copying if CUDA/OpenGL interop is not available
• Clarify terms for external contributions, please see CONTRIBUTING.md for details
• Improve performance of wp.sparse.bsr_mm() by ~5x on benchmark problems
• Fix for XPBD incorrectly indexing into of joint actuations joint_act arrays
• Fix for mass matrix gradients computation in wp.sim.FeatherstoneIntegrator()
• Fix for handling of --msvc_path in build scripts
• Fix for wp.copy() params to record dest and src offset parameters on wp.Tape()
• Fix for wp.randn() to ensure return values are finite
• Fix for slicing of arrays with gradients in kernels
• Fix for function overload caching, ensure module is rebuilt if any function overloads are modified
• Fix for handling of bool types in generic kernels
• Publish CUDA 12.5 binaries for Hopper support, see https://github.com/nvidia/warp?tab=readme-ov-file#installing for details

v1.2.0

[1.2.0] - 2024-06-06

• Add a not-a-number floating-point constant that can be used as wp.NAN or wp.nan.
• Add wp.isnan(), wp.isinf(), and wp.isfinite() for scalars, vectors, matrices, etc.
• Improve kernel cache reuse by hashing just the local module constants. Previously, a
  module's hash was affected by all wp.constant() variables declared in a Warp program.
• Revised module compilation process to allow multiple processes to use the same kernel cache directory.
  Cached kernels will now be stored in hash-specific subdirectory.
• Add runtime checks for wp.MarchingCubes on field dimensions and size
• Fix memory leak in wp.Mesh BVH (GH-225)
• Use C++17 when building the Warp library and user kernels
• Increase PTX target architecture up to sm_75 (from sm_70), enabling Turing ISA features
• Extended NanoVDB support (see warp.Volume):
  • Add support for data-agnostic index grids, allocation at voxel granularity
  • New wp.volume_lookup_index(), wp.volume_sample_index() and generic wp.volume_sample()/wp.volume_lookup()/wp.volume_store() kernel-level functions
  • Zero-copy aliasing of in-memory grids, support for multi-grid buffers
  • Grid introspection and blind data access capabilities
  • warp.fem can now work directly on NanoVDB grids using warp.fem.Nanogrid
  • Fixed wp.volume_sample_v() and wp.volume_store_*() adjoints
  • Prevent wp.volume_store() from overwriting grid background values
• Improve validation of user-provided fields and values in warp.fem
• Support headless rendering of wp.render.OpenGLRenderer via pyglet.options["headless"] = True
• wp.render.RegisteredGLBuffer can fall back to CPU-bound copying if CUDA/OpenGL interop is not available
• Clarify terms for external contributions, please see CONTRIBUTING.md for details
• Improve performance of wp.sparse.bsr_mm() by ~5x on benchmark problems
• Fix for XPBD incorrectly indexing into of joint actuations joint_act arrays
• Fix for mass matrix gradients computation in wp.sim.FeatherstoneIntegrator()
• Fix for handling of --msvc_path in build scripts
• Fix for wp.copy() params to record dest and src offset parameters on wp.Tape()
• Fix for wp.randn() to ensure return values are finite
• Fix for slicing of arrays with gradients in kernels
• Fix for function overload caching, ensure module is rebuilt if any function overloads are modified
• Fix for handling of bool types in generic kernels
• Publish CUDA 12.5 binaries for Hopper support, see https://github.com/nvidia/warp?tab=readme-ov-file#installing for details

[1.1.1] - 2024-05-24

• wp.init() is no longer required to be called explicitly and will be performed on first call to the API
• Speed up omni.warp.core's startup time

v1.1.0

[1.1.0] - 2024-05-09

• Support returning a value from @wp.func_native CUDA functions using type hints
• Improved differentiability of the wp.sim.FeatherstoneIntegrator
• Fix gradient propagation for rigid body contacts in wp.sim.collide()
• Added support for event-based timing, see wp.ScopedTimer()
• Added Tape visualization and debugging functions, see wp.Tape.visualize()
• Support constructing Warp arrays from objects that define the __cuda_array_interface__ attribute
• Support copying a struct to another device, use struct.to(device) to migrate struct arrays
• Allow rigid shapes to not have any collisions with other shapes in wp.sim.Model
• Change default test behavior to test redundant GPUs (up to 2x)
• Test each example in an individual subprocess
• Polish and optimize various examples and tests
• Allow non-contiguous point arrays to be passed to wp.HashGrid.build()
• Upgrade LLVM to 18.1.3 for from-source builds and Linux x86-64 builds
• Build DLL source code as C++17 and require GCC 9.4 as a minimum
• Array clone, assign, and copy are now differentiable
• Use Ruff for formatting and linting
• Various documentation improvements (infinity, math constants, etc.)
• Improve URDF importer, handle joint armature
• Allow builtins.bool to be used in Warp data structures
• Use external gradient arrays in backward passes when passed to wp.launch()
• Add Conjugate Residual linear solver, see wp.optim.linear.cr()
• Fix propagation of gradients on aliased copy of variables in kernels
• Facilitate debugging and speed up import warp by eliminating raising any exceptions
• Improve support for nested vec/mat assignments in structs
• Recommend Python 3.9 or higher, which is required for JAX and soon PyTorch.
• Support gradient propagation for indexing sliced multi-dimensional arrays, i.e. a[i][j] vs. a[i, j]
• Provide an informative message if setting DLL C-types failed, instructing to try rebuilding the library

[1.0.3] - 2024-04-17

• Add a support_level entry to the configuration file of the extensions

v1.0.2

[1.0.2] - 2024-03-22

• Make examples runnable from any location
• Fix the examples not running directly from their Python file
• Add the example gallery to the documentation
• Update README.md examples USD location
• Update example_graph_capture.py description

v1.0.1

[1.0.1] - 2024-03-15

• Document Device total_memory and free_memory
• Documentation for allocators, streams, peer access, and generics
• Changed example output directory to current working directory
• Added python -m warp.examples.browse for browsing the examples folder
• Print where the USD stage file is being saved
• Added examples/optim/example_walker.py sample
• Make the drone example not specific to USD
• Reduce the time taken to run some examples
• Optimise rendering points with a single colour
• Clarify an error message around needing USD
• Raise exception when module is unloaded during graph capture
• Added wp.synchronize_event() for blocking the host thread until a recorded event completes
• Flush C print buffers when ending stdout capture
• Remove more unneeded CUTLASS files
• Allow setting mempool release threshold as a fractional value

v1.0.0

[1.0.0] - 2024-03-07

• Add FeatherstoneIntegrator which provides more stable simulation of articulated rigid body dynamics in generalized coordinates (State.joint_q and State.joint_qd)
• Introduce warp.sim.Control struct to store control inputs for simulations (optional, by default the Model control inputs are used as before); integrators now have a different simulation signature: integrator.simulate(model: Model, state_in: State, state_out: State, dt: float, control: Control)
• joint_act can now behave in 3 modes: with joint_axis_mode set to JOINT_MODE_FORCE it behaves as a force/torque, with JOINT_MODE_VELOCITY it behaves as a velocity target, and with JOINT_MODE_POSITION it behaves as a position target; joint_target has been removed
• Add adhesive contact to Euler integrators via Model.shape_materials.ka which controls the contact distance at which the adhesive force is applied
• Improve handling of visual/collision shapes in URDF importer so visual shapes are not involved in contact dynamics
• Experimental JAX kernel callback support
• Improve module load exception message
• Add wp.ScopedCapture
• Removing enable_backward warning for callables
• Copy docstrings and annotations from wrapped kernels, functions, structs