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CHANGELOG.md

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Changelog

[2.3.8] - 2024-12-15

Fixed

  • fix os version in CI to resolve windows mismatch compiler problem

[2.3.7] - 2024-12-08

Changed

  • add python 3.13 and cuda 12.1/12.4/12.6 prebuilts, drop python 3.7/3.8 prebuilts, change manylinux glibc from 2_17 to 2_28 if cuda >= 12.4, which requires recent OS such as ubuntu 18.10+.

[2.3.6] - 2023-04-19

Fixed

  • Fix a CI bug that cpu cumm and spconv use different gcc compiler, must be same.

[2.3.5] - 2023-03-24

Fixed

  • use a flag to enable large kernel algo (need time to compile at runtime)

[2.3.4] - 2023-03-23

Added

  • Add SparseGlobalMaxPool and SparseGlobalAvgPool for training only. libspconv don't support it.

[2.3.3] - 2023-02-02

Fixed

  • Fix int8 nvrtc error when use prebuilt
  • Fix int8 kernel when run on turing GPU

[2.3.2] - 2023-01-20

Changed

  • change version

[2.3.1] - 2023-01-20

Changed

  • change version

[2.3.0] - 2023-01-19

Added

  • Add int8 quantization support
  • Add large kernel support for implicit gemm (kv <= 128)

[2.2.6] - 2022-11-06

Fixed

  • CI fail because of pypi temporary shutdown. assign a new version and run again.

[2.2.5] - 2022-11-05

Fixed

  • Fix overflow when shape is too large

[2.2.4] - 2022-10-13

Added

  • Add prebuilt for CUDA 11.8 (RTX 4090 and H100) and CUDA 11.6.

Fixed

  • Fix small bugs

[2.2.3] - 2022-9-28

Fixed

  • Fix missing .contiguous for input feature
  • Add some debug msg if points vanished.

[2.2.2] - 2022-9-25

Fixed

  • Fix CI problem: main function too long and cause OOM in CI vm.

[2.2.1] - 2022-9-25

Fixed

  • Fix build problem
  • Fix nvrtc problem

[2.2.0] - 2022-9-24

Added

  • Add Ampere support. faster fp16, faster tf32 and greatly faster int8 kernels in Ampere GPUs.
  • Add pure c++ code generation (libspconv.so) for deploy (or train in another deeplearning framework)
  • Add NVRTC support for all gemm kernels. if your GPU architecture isn't compiled in prebuilt, spconv will use slightly slower (10-20us overhead for every kernel launch) NVRTC kernels.

Fixed

  • Fix launch fail in maxpool if too much voxels

Changed

  • all weight layout will be KRSC, don't support old spconv 1.x weights anymore.
  • previous gemm ops in ops.py now move to c++ by default (controlled by spconv.constants.SPCONV_CPP_GEMM)

Removed

  • drop python 3.6 support.
  • pascal and kepler architecture is removed in CUDA 12 prebuilt.

[2.1.22] - 2022-6-11

Fixed

  • Fix thrust problem by adding -fvisibility=hidden

[2.1.22] - 2022-4-14

Added

  • add full nvrtc support
  • add support for large spatial shape and batch size. if detect large shape, we use int64 instead of int32 when hashing.

[2.1.21] - 2021-12-9

Added

  • add sm_37
  • add fp16 kernels witl fp32 accumulator (run slower, but can avoid nan if channel size is too large)
  • add SPCONV_BWD_SPLITK env to control splitk candidates.

[2.1.20] - 2021-12-6

Added

  • Add fp16 conv simt kernels for mixed-training in pascal or older GPUS. WARNING: not optimized for TESLA P100 which has 2x throughput in half.

[2.1.19] - 2021-12-3

Fixed

  • Fix wrong arch assert in all kernels for old GPUs to make spconv work in sm_50 GPUs

[2.1.18] - 2021-11-29

Fixed

  • Fix a small bug of spatial_shape.
  • Fix a bug in PointToVoxel, we must always return a clone instead of a view.

[2.1.17] - 2021-11-29

Fixed

  • Fix a bug in sparse add.
  • Fix a serious bug in conv weight init.

Added

  • Add more wrong usage check
  • Add insert_exist_keys for hash table

[2.1.16] - 2021-11-28

Fixed

  • Fix strange compile problem in windows

[2.1.15] - 2021-11-28

Fixed

  • Fix missing pccm.Class in setup.py

[2.1.14] - 2021-11-28

Added

  • Add hash table
  • update cumm version
  • Add AddTableMisaligned for sptensors with same shape but different indices.

Fixed

  • Fix a bug already fixed in 2.1.10 but introduced in 2.1.12 again.

[2.1.13] - 2021-?-?

Added

  • Add some ops from spconv 1.x, see spconv.utils for more details.
  • Add some debug tool for users to attach more info in issue.

[2.1.12] - 2021-11-23

Added

  • Add a method for voxel generator to get pc_voxel_id, which is usually used in semantic segmentation

Fixed

  • Fix a bug in cuda voxel generater when max_voxels is smaller than real number of voxels

[2.1.11] - 2021-11-22

Fixed

  • Fixed a bug Volta kernels (TITAN V, Tesla V100), backward weight kernels use f16 as accumulator. we should use f32.
  • Fixed a corner case when user use kernel size = 1x1 but stride != 1.
  • Fixed a corner case when input feature is non-contiguous when maxpool.

[2.1.10] - 2021-11-19

Fixed

  • Fixed a bug in utils.PointToVoxel, shouldn't get cuda stream in cpu code

[2.1.9] - 2021-11-18

Removed

  • Remove a wrong assert

[2.1.8] - 2021-11-15

Added

  • Add support for pytorch 1.5

[2.1.7] - 2021-11-11

Fixed

  • Fix a bug when net have inverse and run inference in eval mode.

[2.1.6] - 2021-11-10

Fixed

  • Fix missing -fopenmp in linker for CPU only

Removed

  • remove stale comment sending in CI

[2.1.5] - 2021-11-10

Added

  • Add cuda profile tool
  • Add python 36 support

Changed

  • Format all code

Removed

  • remove a unnecessary device sync and slightly improve performance.

[2.1.4] - 2021-11-10

Fixed

  • Fix a bug of SparseInverseConv3d

[2.1.3] - 2021-11-08

Fixed

  • Fix a bug of CPU only package

[2.1.2] - 2021-11-06

Fixed

  • Fix a bug of python 3.7

[2.1.0] - 2021-10-31

Added

  • add implicit gemm algorithm for all kind of convolution with kernel volume <= 32. this algorithm is very fast with float16.
  • add pytorch wrapper for voxel generator
  • add CPU support and CPU-only build.

[2.0.2] - 2021-10-26

Fixed

  • Fix a serious bug that do nothing with non-spconv layers in SparseSequential
  • Fix a bug of ProxyableClassMeta

[2.0.0] - 2021-10-16

Changed

  • Change build system from cmake to pccm.
  • Change pytorch python code to spconv.pytorch
  • Rewrite All c++ code.

[1.2.1] - 2020-06-04

Changed

  • The subm indice pair generation speed is greatly increased by two tricks: 1. most subm conv use only kernelsize=3, so we can unroll loops to get 100% performance increase. 2. subm indice pairs have a property: indicePairs[0, i] = indicePairs[1, kernelVolume - i - 1], so we can get another 100% performance increase.

[1.2.0] - 2020-05-28

Added

  • add batch gemm support. small performance increasement but more gpu memory usage. you can use algo=spconv.ConvAlgo.Batch to use it.

Changed

  • replace most of 'functor' with c++14 dispatch in c++ code.

Fixed

  • change gather/scatterAdd kernel parameter to support large points.