update

Dockerfile

@@ -3,8 +3,8 @@
 
 
 # xxx move from cudagl to cuda, for runtime?
-ARG CUDA_DEVEL="11.0.3-devel-ubuntu20.04"
+ARG CUDA_DEVEL="12.1.1-devel-ubuntu22.04"
-ARG CUDA_RUNTIME="11.0.3-runtime-ubuntu20.04"
+ARG CUDA_RUNTIME="12.1.1-runtime-ubuntu22.04"
 
 # runtime starts as 2.3GB image
 # devel is runtime+ and is 4.2GB image
@@ -16,7 +16,7 @@ FROM nvidia/cuda:$CUDA_DEVEL AS builder
 ARG CUDA_ARCH_75=75
 ARG CUDA_ARCH_61=61
 
-ARG FFMPEG_TGZ=https://ffmpeg.org/releases/ffmpeg-5.0.tar.gz
+ARG FFMPEG_TGZ=https://ffmpeg.org/releases/ffmpeg-5.1.3.tar.gz
 
 
 # create an ffmpeg (w/ shared libs) that can utilize nvidia GPU
@@ -41,7 +41,7 @@ RUN apt-get -yqq update  &&  apt-get -yqq install  \
 
 # install nvidia headers (got moved out of ffmpeg)
 RUN git clone https://git.videolan.org/git/ffmpeg/nv-codec-headers  && \
-    cd nv-codec-headers  && git checkout origin/sdk/11.0 && \
+    cd nv-codec-headers  && git checkout n12.0.16.0 && \
     sudo make install  && \
     cd ..
 
@@ -69,7 +69,8 @@ RUN sed -i -e "s/gencode arch=compute_..,code=sm_../gencode arch=compute_${CUDA_
       --enable-cuda --enable-cuda-sdk --enable-cuda-nvcc --enable-nvenc --enable-cuvid --enable-libnpp \
       --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64  && \
     make -j4  && \
-    cp ffmpeg /tmp/ffmpeg-turing
+    cp ffmpeg /tmp/ffmpeg-turing && \
+    cp ffplay /tmp/ffplay-turing
 
 RUN sed -i -e "s/gencode arch=compute_..,code=sm_../gencode arch=compute_${CUDA_ARCH_61},code=sm_${CUDA_ARCH_61}/" ./configure\
     &&  make distclean || echo  &&  \
@@ -85,7 +86,8 @@ RUN sed -i -e "s/gencode arch=compute_..,code=sm_../gencode arch=compute_${CUDA_
       --enable-cuda --enable-cuda-sdk --enable-cuda-nvcc --enable-nvenc --enable-cuvid --enable-libnpp \
       --extra-cflags=-I/usr/local/cuda/include --extra-ldflags=-L/usr/local/cuda/lib64  && \
     make -j4  && \
-    cp ffmpeg /tmp/ffmpeg-pascal
+    cp ffmpeg /tmp/ffmpeg-pascal && \
+    cp ffplay /tmp/ffplay-pascal
 
 # now collect up all the .so files we'll need for the runtime, into new lib/ subdir
 RUN BIN=ffmpeg  &&  mkdir lib  &&  ( \
@@ -96,9 +98,11 @@ RUN BIN=ffmpeg  &&  mkdir lib  &&  ( \
 
 # switch to the smaller "runtime" baseline.
 # now we just keep the executable(s) and .so files they need and chuck everything else above.
-FROM nvidia/cudagl:$CUDA_RUNTIME
+FROM nvidia/cuda:$CUDA_RUNTIME
 COPY --from=builder /tmp/ffmpeg-pascal /ffmpeg-pascal
 COPY --from=builder /tmp/ffmpeg-turing /ffmpeg
+COPY --from=builder /tmp/ffplay-pascal /ffplay-pascal
+COPY --from=builder /tmp/ffplay-turing /ffplay
 COPY --from=builder /tmp/ffmpeg/lib/   /fflib
 
 # @see cuda-runtime.sh for where this small image of three cuda runtime .so files came from

docker-compose.yml

@@ -1,4 +1,4 @@
-version: '2'
+version: '3'
 
 services:
   nvidia-ffmpeg:
@@ -6,19 +6,18 @@ services:
     image: nvidia-ffmpeg
     container_name: nvidia-ffmpeg
     restart: "no"
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              capabilities: [gpu]
+    environment:
+      - NVIDIA_VISIBLE_DEVICES=all
     entrypoint:
       - /bin/sleep
       - infinity
     volumes:
-      - /usr/lib/x86_64-linux-gnu/nvidia/current:/cuda:ro
       - ./folder:/folder
-    environment:
+      - /usr/lib/x86_64-linux-gnu/nvidia/current:/cuda:ro
-      - NVIDIA_VISIBLE_DEVICES=all
+    network_mode: host
-    devices:
-      - /dev/nvidia0
-      - /dev/nvidiactl
-      - /dev/nvidia-uvm
-      - /dev/nvidia-uvm-tools
-    cap_add:
-      - IPC_LOCK
-    network_mode: host