v1.0.0-beta.5

[1.0.0-beta.5] - 2023-11-22

• Fix for kernel caching when function argument types change
• Fix code-gen ordering of dependent structs
• Fix for wp.Mesh build on MGPU systems
• Fix for name clash bug with adjoint code: #154
• Add wp.frac() for returning the fractional part of a floating point value
• Add support for custom native CUDA snippets using @wp.func_native decorator
• Add support for batched matmul with batch size > 2^16-1
• Add support for tranposed CUTLASS wp.matmul() and additional error checking
• Add support for quad and hex meshes in wp.fem
• Detect and warn when C++ runtime doesn't match compiler during build, e.g.: libstdc++.so.6: version `GLIBCXX_3.4.30' not found
• Documentation update for wp.BVH
• Documentaiton and simplified API for runtime kernel specialization wp.Kernel

[1.0.0-beta.4] - 2023-11-01

• Add wp.cbrt() for cube root calculation
• Add wp.mesh_furthest_point_no_sign() to compute furthest point on a surface from a query point
• Add support for GPU BVH builds, 10-100x faster than CPU builds for large meshes
• Add support for chained comparisons, i.e.: 0 < x < 2
• Add support for running warp.fem examples headless
• Fix for unit test determinism
• Fix for possible GC collection of array during graph capture
• Fix for wp.utils.array_sum() output initialization when used with vector types
• Coverage and documentation updates

[1.0.0-beta.3] - 2023-10-19

• Add support for code coverage scans (test_coverage.py), coverage at 85% in omni.warp.core
• Add support for named component access for vector types, e.g.: a = v.x
• Add support for lvalue expressions, e.g.: array[i] += b
• Add casting constructors for matrix and vector types
• Add support for type() operator that can be used to return type inside kernels
• Add support for grid-stride kernels to support kernels with > 2^31-1 thread blocks
• Fix for multi-process initialization warnings
• Fix alignment issues with empty wp.struct
• Fix for return statement warning with tuple-returning functions
• Fix for wp.batched_matmul() registering the wrong function in the Tape
• Fix and document for wp.sim forward + inverse kinematics
• Fix for wp.func to return a default value if function does not return on all control paths
• Refactor wp.fem support for new basis functions, decoupled function spaces
• Optimizations for wp.noise functions, up to 10x faster in most cases
• Optimizations for type_size_in_bytes() used in array construction

[1.0.0-beta.2] - 2023-09-01

• Fix for passing bool into wp.func functions
• Fix for deprecation warnings appearing on stderr, now redirected to stdout
• Fix for using for i in wp.hash_grid_query(..) syntax

[1.0.0-beta.1] - 2023-08-29

• Fix for wp.float16 being passed as kernel arguments
• Fix for compile errors with kernels using structs in backward pass
• Fix for wp.Mesh.refit() not being CUDA graph capturable due to synchronous temp. allocs
• Fix for dynamic texture example flickering / MGPU crashes demo in Kit by reusing ui.DynamicImageProvider instances
• Fix for a regression that disabled bundle change tracking in samples
• Fix for incorrect surface velocities when meshes are deforming in OgnClothSimulate
• Fix for incorrect lower-case when setting USD stage "up_axis" in examples
• Fix for incompatible gradient types when wrapping PyTorch tensor as a vector or matrix type
• Fix for adding open edges when building cloth constraints from meshes in wp.sim.ModelBuilder.add_cloth_mesh()
• Add support for wp.fabricarray to directly access Fabric data from Warp kernels, see https://omniverse.gitlab-master-pages.nvidia.com/usdrt/docs/usdrt_prim_selection.html for examples
• Add support for user defined gradient functions, see @wp.func_replay, and @wp.func_grad decorators
• Add support for more OG attribute types in omni.warp.from_omni_graph()
• Add support for creating NanoVDB wp.Volume objects from dense NumPy arrays
• Add support for wp.volume_sample_grad_f() which returns the value + gradient efficiently from an NVDB volume
• Add support for LLVM fp16 intrinsics for half-precision arithmetic
• Add implementation of stochastic gradient descent, see wp.optim.SGD
• Add warp.fem framework for solving weak-form PDE problems (see https://nvidia.github.io/warp/_build/html/modules/fem.html)
• Optimizations for omni.warp extension load time (2.2s to 625ms cold start)
• Make all omni.ui dependencies optional so that Warp unit tests can run headless
• Deprecation of wp.tid() outside of kernel functions, users should pass tid() values to wp.func functions explicitly
• Deprecation of wp.sim.Model.flatten() for returning all contained tensors from the model
• Add support for clamping particle max velocity in wp.sim.Model.particle_max_velocity
• Remove dependency on urdfpy package, improve MJCF parser handling of default values