Repository: pytorch
Issue: GEMM with int8 datatype throws RuntimeError on GPU
Labels: triaged,module: linear algebra,needs design,function request

## 🐛 Bug
## To Reproduce

```
import torch

def gemm(CPU):
  if CPU == True:
    A = torch.randint(1,10,[3,3]).type(torch.int8)
    B = torch.randint(1,10,[3,3]).type(torch.int8)
    C = A@B

  else:
    A = torch.randint(1,10,[3,3]).type(torch.int8).cuda()
    B = torch.randint(1,10,[3,3]).type(torch.int8).cuda()
    C = A@B

gemm(True)
gemm(False)
```

Simply run `python3 gemm.py` will cause the following RuntimeError:
```
Traceback (most recent call last):
  File "gemm.py", line 15, in <module>
    gemm(False)
  File "gemm.py", line 12, in gemm
    C = A@B
RuntimeError: "addmm_cuda" not implemented for 'Char
```
`gemm(True)` passes, namely running **GEMM** with with data **int8** on CPU is fine.
## Expected behavior
**GEMM** with data **int8** on GPU should be supported.

## Environment
PyTorch version: 1.7.0+cu101
Is debug build: True
CUDA used to build PyTorch: 10.1
ROCM used to build PyTorch: N/A

OS: CentOS Linux release 7.7.1908 (Core) (x86_64)
GCC version: (GCC) 7.2.0
Clang version: 9.0.0 (tags/RELEASE_900/final)
CMake version: version 3.12.2

Python version: 3.6 (64-bit runtime)
Is CUDA available: True
CUDA runtime version: Could not collect
GPU models and configuration: 
GPU 0: Tesla V100-PCIE-16GB

Nvidia driver version: 455.45.01
cuDNN version: Probably one of the following:
/usr/lib64/libcudnn.so.7.5.0
/usr/lib64/libcudnn.so.8.0.5
/usr/local/cuda-10.1/targets/x86_64-linux/lib/libcudnn.so.7.5.0
HIP runtime version: N/A
MIOpen runtime version: N/A

Versions of relevant libraries:
[pip3] numpy==1.18.0
[pip3] numpydoc==0.7.0
[pip3] pytorch-sublstm==0.0.2
[pip3] torch==1.7.0+cu101
[pip3] torch-tvm==0.0.1
[pip3] torchaudio==0.7.0
[pip3] torchfile==0.1.0
[pip3] torchnet==0.0.4
[pip3] torchvision==0.8.1+cu101
[conda] blas                      1.0                         mkl  
[conda] cuda100                   1.0                           0    pytorch
[conda] cudatoolkit               10.1.243             h6bb024c_0  
[conda] magma-cuda101             2.5.2                         1    pytorch
[conda] mkl                       2020.0                      166  
[conda] mkl-include               2020.0                      166  
[conda] mkl-service               2.3.0            py36he904b0f_0  
[conda] mkl_fft                   1.0.15           py36ha843d7b_0  
[conda] mkl_random                1.1.0            py36hd6b4f25_0  
[conda] numpy                     1.18.0                   pypi_0    pypi
[conda] numpydoc                  0.7.0            py36h18f165f_0  
[conda] pytorch-sublstm           0.0.2                    pypi_0    pypi
[conda] torch                     1.7.0+cu101              pypi_0    pypi
[conda] torch-tvm                 0.0.1                    pypi_0    pypi
[conda] torchaudio                0.7.0                    pypi_0    pypi
[conda] torchfile                 0.1.0                    pypi_0    pypi
[conda] torchnet                  0.0.4                    pypi_0    pypi
[conda] torchvision               0.8.1+cu101              pypi_0    pypi

cc @jianyuh @nikitaved @pearu @mruberry @heitorschueroff @walterddr