显卡绘图器

Autonomys utilizes your drive storage, specifically SSD or NVMe drives, to store farms. After the plotting or replotting process is finished, your CPU then uses these farms to prove challenges. Farming is not particularly demanding on the CPU, enabling most modern processors to manage a substantial farm size. However, the farm creation process is highly resource intensive, which makes CPU plotting the main bottleneck.

Utilizing GPU plotting allows you to harness the power of compatible GPUs for farm generation and replotting, either in conjunction with or as a substitute for CPU processing. While many modern CPUs can complete the plotting of a sector in less than two minutes, a single high performance GPU can accomplish the same task in under five seconds, greatly improving efficiency and speed.

虽然显卡绘图不是强制性的，但与单纯依靠处理器相比，它提供了更高的能效和速度。

平台兼容性

平台	Ubuntu	Windows	Nvidia	AMD	Intel
CLI
Space Acres

Supported   |   Limited Support   |   Possible Future Support

Limited AMD Support for Ubuntu only is available in recent test builds. The most recent test builds are linked on the forum

See Discord farmer-chat channel for limited support.

支持的显卡

Nvidia
AMD
Intel

系列/型号	支持
RTX 20xx 和更新的
GTX 16 系列

Nvidia drivers version 550 or later are required. Installing the CUDA Toolkit is not required.

在AMD ROCm 支持方面有许多挑战需要克服。在论坛上有关于这个话题的更多信息

您必须使用最新的测试版本以支持AMD。

系列/型号	Ubuntu	Windows
RX 7900 XTX
RX 7600 XT
RX 7600
RX 6800
RX 6700 XT
RX 6700 XT
RX 6600
RX 5700 XT
RX 5700
RX 5600
AMD BC-250

Ubuntu
Windows
Docker

subspace-farmer-rocm-* 二进制文件提供ROCm 支持，并提供与 CUDA类似的命令行选项，并以--rocm为前缀。

为了安装必要的库，请到 Ubuntu 本机安装 — ROCm install (Linux)，并在您的 Ubuntu 版本中按照这些步骤进行：
- 包签名密钥
- Register ROCm packages You don't need a custom driver or full ROCm toolchain to use already compiled application, so skip all other steps.

接下来安装一个带ROCm 运行时的软件包：

sudo apt-get install --no-install-recommends hip-runtime-amd

注册库，以便农民可执行程序和其他应用能够找到它：

echo "/opt/rocm/lib" | sudo tee /etc/ld.so.conf.d/rocm.conf > /dev/null
sudo ldconfig

然后，为了充许用户使用显卡用于计算，你需要把你的用户加入 render 用户组 (请永远不要使用sudo以root身份运行农民二进制程序 🙏 ):
```
sudo usermod -a -G render $LOGNAME
```
Now you'll need to log out of your user profile and log back in or simply reboot for group changes to take effect and you're ready to go.

交叉编译不再需要单独的 Dockerfiles(因此它们被删除)，一个文件同时支持本地和交叉编译

容器镜像现在构建为多平台，意味着没有-aarch64后缀和与之相关的麻烦

Aarch64 农民容器镜像现在编译时即支持 CUDA (但常规可执行文件不是)

容器图像现在提供第二个可执行的/subspace-farmer-rocm (见上文关于为何需要第二个二进制文件的解释)。以后是如何在 Docker Compose 下使用的演示, 你可以将它作为其他使用案例的灵感：

services:
  famer:
    image: ghcr.io/autonomys/farmer:TAG
    # Beginning of ROCm-specific options
    devices:
      - /dev/kfd:/dev/kfd
      # This will make all GPUs accessible, you can also limit this
      # to individual devices like `/dev/dri/renderD128`
      - /dev/dri:/dev/dri
    security_opt:
      - seccomp:unconfined
    # `root` user can be replaced with ID of the user on the host system
    # that is in `render` group, needed to access `/dev/kfd` device
    user: root
    entrypoint: /subspace-farmer-rocm
    # End of ROCm-specific options
    ...the rest of typical options you'd normally use

常见绘图参数

启用显卡绘图

When a compatible GPU is detected, CPU plotting is automatically disabled by default, but can be re-enabled if needed by specifying number of concurrently encoded sectors: --cpu-sector-encoding-concurrency <SECTORS>

--cpu-sector-encoding-concurrency 2

禁用显卡绘图

Ubuntu
Windows

--cuda-gpus ""

--cuda-gpus 99

指定具体显卡

Specify particular GPUs for plotting rather than using all available GPUs (the default configuration employs all compatible GPUs): --cuda-gpus <GPU_IDS>

--cuda-gpus 0,1,3

耕种集群

When utilizing Farming Cluster, particularly with multiple or fast GPUs, you might encounter limitations due to your network's bandwidth. High performance GPUs can easily surpass the capacity of a 1G connection. While this won't cause the process to fail, it may result in your GPU idling as it waits for data to transfer. To optimize performance in such scenarios, consider upgrading to networking solutions of 2.5G, 10G, or higher.

平台兼容性​

支持的显卡​

常见绘图参数​

耕种集群​

平台兼容性

支持的显卡

常见绘图参数

耕种集群