[DOCS] Documentation Addition (Readme updates) (#2495)

* GH-2368 Adding a basic glossary GH-2368 Minor edits GH-2368 Adding missing READMEs and standardization. resolving readme updates GH-2368 Minor improvements to documentation. Improving some readmes. Further improvement for readmes. Cleaned up the documentation in 'client_example' (#2468) Update for PR Update ACRONYMS.md to remove trivial terms Update ACRONYMS.md to provide detailed explanations for BF16 and BF8 formats Apply suggestion from @spolifroni-amd Co-authored-by: spolifroni-amd <Sandra.Polifroni@amd.com> Apply suggestion from @spolifroni-amd Co-authored-by: spolifroni-amd <Sandra.Polifroni@amd.com> Update README.md to clarify CK Tile API description and remove outdated references to the Tile Engine. revise 37_transpose readme revise 36_copy readme Remove references to the Tile Engine in README files for 19_gemm_multi_d and 35_batched_transpose, and update distribution links for clarity. Remove references to the Tile Engine in multiple README files and update distribution links for consistency and clarity. Remove references to the Tile Engine in README files across multiple examples * GH-2368 Adding a basic glossary GH-2368 Minor edits GH-2368 Adding missing READMEs and standardization. resolving readme updates GH-2368 Minor improvements to documentation. Improving some readmes. Further improvement for readmes. Cleaned up the documentation in 'client_example' (#2468) Update for PR Update ACRONYMS.md to remove trivial terms Update ACRONYMS.md to provide detailed explanations for BF16 and BF8 formats Apply suggestion from @spolifroni-amd Co-authored-by: spolifroni-amd <Sandra.Polifroni@amd.com> Apply suggestion from @spolifroni-amd Co-authored-by: spolifroni-amd <Sandra.Polifroni@amd.com> Update README.md to clarify CK Tile API description and remove outdated references to the Tile Engine. revise 37_transpose readme revise 36_copy readme Remove references to the Tile Engine in README files for 19_gemm_multi_d and 35_batched_transpose, and update distribution links for clarity. Remove references to the Tile Engine in multiple README files and update distribution links for consistency and clarity. Remove references to the Tile Engine in README files across multiple examples Refine README files by removing outdated references to the Tile Engine * Updates based on PR feedback 1 * Updates based on PR feedback 2 * Updates based on PR feedback 3 * Updates based on PR feedback 4 * Updates based on PR feedback 5 * Updates based on PR feedback 6 * Updates based on PR feedback 7 * Updates based on PR feedback 8 * Content Modification of CK Tile Example * Modify the ck_tile gemm config --------- Co-authored-by: AviralGoelAMD <aviral.goel@amd.com> Co-authored-by: ThomasNing <thomas.ning@amd.com>
2026-04-20 14:59:17 +00:00 · 2025-10-16 03:10:57 -07:00
parent 013ba3c737
commit 92c67a824f
120 changed files with 8188 additions and 221 deletions
--- a/example/09_convnd_fwd/README.md
+++ b/example/09_convnd_fwd/README.md
@@ -1,6 +1,42 @@
-# Instructions for ```example_convnd_fwd_xdl```
+# N-Dimensional Convolution Forward
+
+## Theory
+
+This example demonstrates the **N-dimensional convolution forward pass** using Composable Kernel. Convolution is a fundamental operation in deep learning, especially in convolutional neural networks (CNNs) for images, audio, and volumetric data.
+
+**Mathematical Formulation:**
+Given:
+- Input tensor: $X[N, C_{in}, D_1, D_2, ..., D_n]$
+- Weight tensor: $W[C_{out}, C_{in}, K_1, K_2, ..., K_n]$
+- Output tensor: $Y[N, C_{out}, O_1, O_2, ..., O_n]$
+
+The convolution computes:
+$$
+Y[n, c_{out}, o_1, ..., o_n] = \sum_{c_{in}} \sum_{k_1} ... \sum_{k_n} X[n, c_{in}, o_1 + k_1, ..., o_n + k_n] \cdot W[c_{out}, c_{in}, k_1, ..., k_n]
+$$
+
+Stride, padding, and dilation parameters control the mapping between input and output indices.
+
+**Algorithmic Background:**
+- Composable Kernel implements convolution as an implicit GEMM (matrix multiplication) for efficiency.
+- The input and weight tensors are transformed into matrices, and the convolution is performed as a GEMM.
+
+## How to Run
+
+### Prerequisites
+
+Please follow the instructions in the main [Build Guide](../../README.md#building-ck) section as a prerequisite to building and running this example.
+
+### Build and run
+```bash
+cd composable_kernel/example/09_convnd_fwd
+mkdir build && cd build
+cmake -DCMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc ..
+make -j
+```
+
+### Run ```example_convnd_fwd_xdl```

-## Run ```example_convnd_fwd_xdl```
 ```bash
 #arg1: verification (0=no, 1=yes)
 #arg2: initialization (0=no init, 1=integer value, 2=decimal value)
@@ -16,3 +52,29 @@
 # <right padding>, (ie RightPy, RightPx for 2D)
 ./bin/example_convnd_fwd_xdl 0 1 100
 ```
+## Source Code Structure
+
+### Directory Layout
+```
+example/09_convnd_fwd/
+├── convnd_fwd_xdl.cpp         # Main example: sets up, runs, and verifies N-D convolution
+include/ck/tensor_operation/gpu/device/
+│   └── device_convnd_fwd.hpp       # Device-level convolution API
+include/ck/tensor_operation/gpu/device/impl/
+│   └── device_convnd_fwd_xdl.hpp   # XDL-based convolution implementation
+include/ck/tensor_operation/gpu/grid/
+│   └── gridwise_convnd_fwd_xdl.hpp # Grid-level convolution kernel
+include/ck/tensor_operation/gpu/block/
+    └── blockwise_convnd_fwd_xdl.hpp # Block-level convolution
+```
+
+### Key Classes and Functions
+
+- **DeviceConvNdFwd** (in `device_convnd_fwd.hpp`):  
+  Device API for N-dimensional convolution.
+- **gridwise_convnd_fwd_xdl** (in `gridwise_convnd_fwd_xdl.hpp`):  
+  Implements the tiled/blocking convolution kernel.
+- **blockwise_convnd_fwd_xdl** (in `blockwise_convnd_fwd_xdl.hpp`):  
+  Handles block-level computation and shared memory tiling.
+
+This example demonstrates how Composable Kernel implements efficient N-dimensional convolution using implicit GEMM, supporting a wide range of deep learning applications.