README.md

### Dequantization GEMM

An example of implementing a dequantization GEMM:

```python
@T.prim_func
def dequant_matmul(
    A: T.Tensor(A_shape, in_dtype),
    B: T.Tensor(B_shape, storage_dtype),
    Ct: T.Tensor((N, M), out_dtype),
):
    with T.Kernel(T.ceildiv(N, block_N), T.ceildiv(M, block_M), threads=threads) as (bx, by):
        A_shared = T.alloc_shared(A_shared_shape, in_dtype)
        B_shared = T.alloc_shared(B_shared_shape, storage_dtype)
        B_local = T.alloc_fragment(B_shared_shape, storage_dtype)
        B_dequantize_local = T.alloc_fragment(B_dequantize_shared_shape, in_dtype)
        Ct_local = T.alloc_fragment((block_N, block_M), accum_dtype)

        T.clear(Ct_local)
        for k in T.Pipelined(
            T.ceildiv(K, block_K), 
            num_stages=num_stages
        ):
            T.copy(A[by * block_M, k * block_K], A_shared)
            T.copy(B[bx * block_N, k * block_K // num_elems_per_byte], B_shared)
            T.copy(B_shared, B_local)
            for i, j in T.Parallel(block_N, block_K):
                B_dequantize_local[i, j] = _tir_packed_to_unsigned_convert("int", 8)(
                    num_bits,
                    B_local[i, j // 2],
                    j % 2,
                    dtype=in_dtype,
                )
            T.gemm(B_dequantize_local, A_shared, Ct_local, transpose_B=True)
        T.copy(Ct_local, Ct[bx * block_N, by * block_M])
```

**Notes:** Dequantize GEMM with magic layout transformations to get optimal performance can be found at project [BitBLAS](https://github.com/microsoft/BitBLAS), example kernels can be found at `testing/python/kernel/test_tilelang_dequantize_gemm.py`, detailed explanation and examples is coming soon.