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doc/en/ROCm.md

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+# ROCm Support for ktransformers (Beta)
+
+## Introduction
+
+### Overview
+In our effort to expand GPU architecture support beyond NVIDIA, we are excited to introduce **AMD GPU support through ROCm** in ktransformers (Beta release). This implementation has been tested and developed using EPYC 9274F processors and AMD Radeon 7900xtx GPUs.
+
+## Installation Guide
+
+### 1. Install ROCm Driver
+Begin by installing the ROCm drivers for your AMD GPU:
+- [Official ROCm Installation Guide for Radeon GPUs](https://rocm.docs.amd.com/projects/radeon/en/latest/docs/install/native_linux/install-radeon.html)
+
+### 2. Set Up Conda Environment
+We recommend using Miniconda3/Anaconda3 for environment management:
+
+```bash
+# Download Miniconda
+wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
+
+# Create environment
+conda create --name ktransformers python=3.11
+conda activate ktransformers
+
+# Install required libraries
+conda install -c conda-forge libstdcxx-ng
+
+# Verify GLIBCXX version (should include 3.4.32)
+strings ~/anaconda3/envs/ktransformers/lib/libstdc++.so.6 | grep GLIBCXX
+```
+
+> **Note:** Adjust the Anaconda path if your installation directory differs from `~/anaconda3`
+
+### 3. Install PyTorch for ROCm
+Install PyTorch with ROCm 6.2.4 support:
+
+```bash
+pip3 install torch torchvision torchaudio \
+  --index-url https://download.pytorch.org/whl/rocm6.2.4
+pip3 install packaging ninja cpufeature numpy
+```
+
+> **Tip:** For other ROCm versions, visit [PyTorch Previous Versions](https://pytorch.org/get-started/previous-versions/)
+
+### 4. Build ktransformers
+
+```bash
+# Clone repository
+git clone https://github.com/kvcache-ai/ktransformers.git
+cd ktransformers
+git submodule update --init
+
+# Optional: Compile web interface
+# See: api/server/website.md
+
+# Install dependencies
+bash install.sh
+```
+
+## Running DeepSeek-R1 Models
+
+### Configuration for 24GB VRAM GPUs
+Use our optimized configuration for constrained VRAM:
+
+```bash
+python ktransformers/local_chat.py \
+  --model_path deepseek-ai/DeepSeek-R1 \
+  --gguf_path <path_to_gguf_files> \
+  --optimize_config_path ktransformers/optimize/optimize_rules/rocm/DeepSeek-V3-Chat.yaml \
+  --cpu_infer <cpu_cores + 1>
+```
+
+> **Beta Note:** Current Q8 linear implementation (Marlin alternative) shows suboptimal performance. Expect optimizations in future releases.
+
+### Configuration for 40GB+ VRAM GPUs
+For better performance on high-VRAM GPUs:
+
+1. Modify `DeepSeek-V3-Chat.yaml`:
+   ```yaml
+   # Replace all instances of:
+   KLinearMarlin → KLinearTorch
+   ```
+
+2. Execute with:
+   ```bash
+   python ktransformers/local_chat.py \
+     --model_path deepseek-ai/DeepSeek-R1 \
+     --gguf_path <path_to_gguf_files> \
+     --optimize_config_path <modified_yaml_path> \
+     --cpu_infer <cpu_cores + 1>
+   ```
+> **Tip:** If you got 2 * 24GB AMD GPUS, you may also do the same modify and run `ktransformers/optimize/optimize_rules/DeepSeek-V3-Chat-multi-gpu.yaml` instead.
+
+## Known Limitations
+- Marlin operations not supported on ROCm platform
+- Current Q8 linear implementation shows reduced performance (Beta limitation)