change some doc

.github/workflows/build.yaml

@@ -15,7 +15,7 @@ jobs:
     runs-on: windows-2019
     strategy:
       matrix:
-        python-version: ['3.7', '3.8', '3.9', '3.10'] 
+        python-version: ['3.7', '3.8', '3.9', '3.10', '3.11'] 
         cuda-version: ['10.2', '11.1', '11.4']
     steps:
       - uses: actions/checkout@master
@@ -115,7 +115,7 @@ jobs:
     runs-on: ubuntu-20.04
     strategy:
       matrix:
-        python-version: ['3.6', '3.7', '3.8', '3.9', '3.10'] # this version is only used for upload.
+        python-version: ['3.6', '3.7', '3.8', '3.9', '3.10', '3.11'] # this version is only used for upload.
         cuda-version: ['102', '111', '113', '114', '']
 
     steps:

CHANGELOG.md

@@ -14,7 +14,6 @@
 
 ### Removed
 - drop python 3.6 support.
-- drop CUDA 10.2 support.
 - pascal and kepler architecture is removed in CUDA 12 prebuilt.
 
 ## [2.1.22] - 2022-6-11

README.md

@@ -51,7 +51,7 @@ Check [spconv 2.x algorithm introduction](docs/spconv2_algo.pdf) to understand s
 
 ## NEWS
 
-* spconv 2.2: ampere feature support (by @[EvernightAurora](https://github.com/EvernightAurora)), pure c++ code generation, nvrtc, drop cuda 10.2, drop python 3.6
+* spconv 2.2: ampere feature support (by [EvernightAurora](https://github.com/EvernightAurora)), pure c++ code generation, nvrtc, drop python 3.6
 
 ## Spconv 2.1 vs Spconv 1.x
 
@@ -68,7 +68,7 @@ Check [spconv 2.x algorithm introduction](docs/spconv2_algo.pdf) to understand s
 * faster fp16 kernels (~10-30%) in ampere GPUs (tested in RTX 3090)
 * greatly faster int8 kernels (~1.2x~2.7x) in ampere GPUs (tested in RTX 3090)
 * no python 3.6 support
-* no CUDA 10.2 support
+* nvrtc support: kernel in old GPUs will be compiled in runtime.
 
 ## Spconv 2.x Development and Roadmap
 
@@ -94,16 +94,12 @@ You need at least CUDA 11.0 to build and run spconv 2.x. We won't offer any supp
 
 ### Prebuilt
 
-We offer python 3.7-3.10 and cuda 11.1/11.3/11.4/12.0 prebuilt binaries for linux (manylinux).
+We offer python 3.7-3.11 and cuda 10.2/11.1/11.3/11.4/12.0 prebuilt binaries for linux (manylinux).
 
-We offer python 3.7-3.10 and cuda 11.1/11.4/12.0 prebuilt binaries for windows 10/11.
-
-We will provide prebuilts for CUDA versions supported by latest pytorch release. For example, pytorch 1.10 provide cuda 10.2 and 11.3 prebuilts, so we provide them too.
+We offer python 3.7-3.11 and cuda 10.2/11.1/11.4/12.0 prebuilt binaries for windows 10/11.
 
 For Linux users, you need to install pip >= 20.3 first to install prebuilt.
 
-CUDA 11.1 will be removed in spconv 2.2 because pytorch 1.10 don't provide prebuilts for it.
-
 ```pip install spconv``` for CPU only (**Linux Only**). you should only use this for debug usage, the performance isn't optimized due to manylinux limit (no omp support).
 
 ```pip install spconv-cu111``` for CUDA 11.1
@@ -176,6 +172,10 @@ You need to rebuild ```cumm``` first if you are build along a CUDA version that
 5. run ```pip install pccm cumm wheel```
 6. run ```python setup.py bdist_wheel```+```pip install dists/xxx.whl```
 
+## Contributers
+
+* [EvernightAurora](https://github.com/EvernightAurora): add ampere feature.
+
 ## Note
 
 The work is done when the author is an employee at [Tusimple](https://www.tusimple.com/).