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[README](/README.md#documentation) > **Functionality** [README](/README.md#documentation) > **Functionality**
# Functionality
## Device-level GEMM
The following table summarizes device-level GEMM kernels in CUTLASS, organized by opcode class, data type, and layout.
Hyperlinks to relevant unit tests demonstrate how specific template instances may be defined.
- N - Column Major Matrix - N - Column Major Matrix
- T - Row Major matrix - T - Row Major matrix
- {N,T} x {N,T} - All combinations, i.e. NN, NT, TN, TT - {N,T} x {N,T} - All combinations, i.e. NN, NT, TN, TT
@ -25,6 +18,12 @@ Hyperlinks to relevant unit tests demonstrate how specific template instances ma
- SpTensorOp - Use Sparse Tensor Core MMA - SpTensorOp - Use Sparse Tensor Core MMA
- WmmaTensorOp - Use WMMA abstraction to use Tensor Core MMA - WmmaTensorOp - Use WMMA abstraction to use Tensor Core MMA
# Functionality
## Device-level GEMM
The following table summarizes device-level GEMM kernels in CUTLASS, organized by opcode class, data type, and layout.
Hyperlinks to relevant unit tests demonstrate how specific template instances may be defined.
|**Opcode Class** | **Compute Capability** | **CUDA Toolkit** | **Data Type** | **Layouts** | **Unit Test** | |**Opcode Class** | **Compute Capability** | **CUDA Toolkit** | **Data Type** | **Layouts** | **Unit Test** |
|-----------------|------------------------|------------------|--------------------------------|------------------------|------------------| |-----------------|------------------------|------------------|--------------------------------|------------------------|------------------|