v1.2.2
版本发布时间: 2024-07-05 03:07:43
NVIDIA/warp最新发布版本:v1.3.3(2024-09-05 04:54:55)
[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 towp.context.Device
[1.2.0] - 2024-06-06
- Add a not-a-number floating-point constant that can be used as
wp.NAN
orwp.nan
. - Add
wp.isnan()
,wp.isinf()
, andwp.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
(fromsm_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 genericwp.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 usingwarp.fem.Nanogrid
- Fixed
wp.volume_sample_v()
andwp.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
viapyglet.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 onwp.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、 warp_lang-1.2.2+cpu-py3-none-macosx_10_13_universal2.whl 41.82MB
2、 warp_lang-1.2.2+cu11-py3-none-manylinux2014_aarch64.whl 58.92MB
3、 warp_lang-1.2.2+cu11-py3-none-manylinux2014_x86_64.whl 60.52MB
4、 warp_lang-1.2.2+cu11-py3-none-win_amd64.whl 51.67MB
5、 warp_lang-1.2.2+cu12-py3-none-manylinux2014_aarch64.whl 62.39MB
6、 warp_lang-1.2.2+cu12-py3-none-manylinux2014_x86_64.whl 62.95MB
7、 warp_lang-1.2.2+cu12-py3-none-win_amd64.whl 53.21MB