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+# CUTLASS API
+
+**NOTE: This is an experimental/early-access version of the CUTLASS API. All APIs, names, and paths are subject to change.**
+
+The CUTLASS API provides high-level, universal interfaces to discover, compile,
+ and execute GEMMs (including grouped GEMMs and scaled GEMMs) targeting NVIDIA GPUs.
+It allows GEMM kernels written in different DSLs to be integrated and discovered under
+a uniform API.
+
+```python
+import cutlass_api
+import torch
+
+A, B, out = (torch.randn(128, 128, device="cuda", dtype=torch.float16) for _ in range(3))
+
+# Create arguments for the GEMM operation
+args = cutlass_api.arguments.GemmArguments(A, B, out, accumulator_type=torch.float32)
+
+# Query for kernels that support our provided arguments on SM100
+kernels = cutlass_api.get_kernels(args, cc=100)
+
+# JIT compile and execute one of the returned kernels
+kernels[0].run(args)
+```
+
+## Deep dive
+
+To learn more about the API, follow the in-depth tutorials in the [examples directory](./examples).
+
+## Directory structure
+* [cutlass_api](./cutlass_api/): source for the CUTLASS API
+* [examples](./examples/): examples of using the CUTLASS API
+* [test](./test/): tests of the CUTLASS API
+
+## Installation
+There is currently no wheel for the CUTLASS API.
+Install in editable mode from the `python/cutlass_api` directory of the CUTLASS repository:
+```bash
+# From the root of this README file
+
+# Install required dependencies
+pip install -e .
+
+# Install required dependencies for use with torch
+pip install -e ".[torch]"
+
+# To install all dependencies to develop, run tests, etc.
+pip install -e ".[dev]"
+```
+
+## Running examples and tests
+[Tests](./test/) use [pytest](https://docs.pytest.org/en/stable/). An example of running a test is:
+```bash
+pytest test/integration/test_gemm.py
+```
+
+[Examples](./examples/) are [Jupyter notebooks](https://jupyter.org/). They can be launched via:
+```bash
+cd examples
+jupyter notebook
+```
+
+## Requirements, compatibility, and current support
+Please see [pyproject.toml](pyproject.toml) for dependencies.
+
+**Compatibility:** CUTLASS API has the same compatibility requirements as the CUTLASS project.
+See CUTLASS's [Compatibility section](https://github.com/NVIDIA/cutlass?tab=readme-ov-file#compatibility).
+
+### Current support
+
+* Dense GEMM: `out = A @ B`
+    - Compute capabilities: 100, 103
+    - Input precisions (A and B must be of same type): F16, BF16, TF32, INT8
+    - Output precisions: F32, F16, BF16, INT32
+    - Epilogue operations:
+        - Auxiliary load of tensors equal in rank and shape of `out`
+        - Auxiliary store of tensors equal in rank and shape of `out`
+        - Auxiliary load of scalar
+        - Tensor-tensor elementwise or tensor-scalar addition, multiplication, subtraction, division
+        - Elementwise tensor exponent, relu, sigmoid, tanh
+
+* Planned additions
+    * Block-scaled GEMMs
+    * Grouped GEMMs
+    * Additional epilogue operations
+        * Reductions
+        * Row/column broadcasts
+    * SM90 kernels
+    * Convolutions