cuda remote api: cricket

README.md

@@ -45,3 +45,19 @@ A hardweres különbségek miatt, az eszközillesztők elrejtik a GPU multiplexe
 # Források
 # Források
  - Cheol-Ho Hong, Ivor Spence, and Dimitrios S. Nikolopoulos. 2017. GPU Virtualization and Scheduling Methods: A Comprehensive Survey. ACM Comput. Surv. 50, 3, Article 35 (May 2018), 37 pages. https://doi.org/10.1145/3068281
  - Cheol-Ho Hong, Ivor Spence, and Dimitrios S. Nikolopoulos. 2017. GPU Virtualization and Scheduling Methods: A Comprehensive Survey. ACM Comput. Surv. 50, 3, Article 35 (May 2018), 37 pages. https://doi.org/10.1145/3068281
  - Virtual GPU Software Documentation - NVIDIA: https://docs.nvidia.com/grid/14.0/grid-vgpu-user-guide/index.html
  - Virtual GPU Software Documentation - NVIDIA: https://docs.nvidia.com/grid/14.0/grid-vgpu-user-guide/index.html
+
+
+# Remote API megvalósítás CUDA környezethez:
+Kiinduló os: Ubuntu 22.04 server. Szükséges könyvtárak, függőségek telepítése:
+ 
+ - `sudo apt update`
+ - `sudo apt install nvidia-driver-535-server`
+ - `wget https://developer.download.nvidia.com/compute/cuda/12.2.0/local_installers/cuda_12.2.0_535.54.03_linux.run`
+ - `sudo sh cuda_12.2.0_535.54.03_linux.run`
+ - `export PATH=$PATH:/usr/local/cuda-12.2/bin && export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-12.2/lib64:/usr/local/cuda-12.2/lib64`
+ - `sudo apt install build-essential git make rpcbind`
+ - `sudo apt-get install autotools-dev automake libtool`
+ - `sudo apt install qemu-kvm libvirt-daemon-system virt-manager`
+ - `sudo adduser $USER libvirt`
+ - `sudo apt install python3-dev`
+ - `git clone https://github.com/RWTH-ACS/cricket.git`
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