review docker run command

doc/Grobid-docker.md

@@ -32,23 +32,25 @@ Current latest version:
 - Run the container:
 
 ```bash
-> docker run --rm --gpus --init all -p 8070:8070 grobid/grobid:0.7.3
+> docker run --rm --gpus all --init --ulimit core=0 -p 8070:8070 grobid/grobid:0.7.3
 ```
 
-The image will automatically uses the GPU and CUDA version available on your host machine, but only on Linux. GPU usage via a container on Windows and MacOS machine is currently not supported by Docker. If no GPU are available, CPU will be used.  
+The image will automatically uses the GPU and CUDA version available on your host machine, but only on Linux. GPU usage via a container on Windows and MacOS machine is currently not supported by Docker. If no GPU are available, CPU will be used. 
+
+Note that starting the container with option `--ulimit core=0` avoids having possible core dumped inside the container, which can happen overwise due to the crash of the PDF parsing C++ component. 
 
 To specify to use only certain GPUs (see the [nvidia container toolkit user guide](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/user-guide.html#gpu-enumeration) for more details):
 
 ```bash
-> docker run --rm --gpus '"device=1,2"' --init -p 8070:8070 -p 8081:8071 grobid/grobid:${latest_grobid_version}
+> docker run --rm --gpus '"device=1,2"' --init --ulimit core=0 -p 8070:8070 -p 8081:8071 grobid/grobid:${latest_grobid_version}
 ```
 
 You can run the image on CPU by omitting the `-gpus` parameters. 
 
 Note the default version is running on port `8070`, however it can be mapped on the more traditional port `8080` of your host with the following command:
 
 ```bash
-> docker run -t --rm --gpus all --init -p 8080:8070 grobid/grobid:${latest_grobid_version}
+> docker run --rm --gpus all --init --ulimit core=0 -p 8080:8070 grobid/grobid:${latest_grobid_version}
 ```
 
 Access the service:
@@ -90,19 +92,19 @@ Latest version:
 - Run the container:
 
 ```bash
-> docker run -t --rm --init -p 8070:8070 lfoppiano/grobid:${latest_grobid_version}
+> docker run --rm --init --ulimit core=0 -p 8070:8070 lfoppiano/grobid:${latest_grobid_version}
 ```
 
 Latest version:
 
 ```bash
-> docker run -t --rm --init -p 8070:8070 lfoppiano/grobid:0.7.3
+> docker run --rm --init --ulimit core=0 -p 8070:8070 lfoppiano/grobid:0.7.3
 ```
 
 Note the default version is running on port `8070`, however it can be mapped on the more traditional port `8080` of your host with the following command:
 
 ```bash
-> docker run -t --rm --init -p 8080:8070 -p 8081:8071 lfoppiano/grobid:${latest_grobid_version}
+> docker run --rm --init --ulimit core=0 -p 8080:8070 -p 8081:8071 lfoppiano/grobid:${latest_grobid_version}
 ```
 
 Access the service:
@@ -117,7 +119,7 @@ Grobid web services are then available as described in the [service documentatio
 The simplest way to pass a modified configuration to the docker image is to mount the yaml GROBID config file `grobid.yaml` when running the image. Modify the config file `grobid/grobid-home/config/grobid.yaml` according to your requirements on the host machine and mount it when running the image as follow: 
 
 ```bash
-docker run --rm --gpus all --init -p 8080:8070 -p 8081:8071 -v /home/lopez/grobid/grobid-home/config/grobid.yaml:/opt/grobid/grobid-home/config/grobid.yaml:ro  grobid/grobid:0.7.3
+docker run --rm --gpus all --init --ulimit core=0 -p 8080:8070 -p 8081:8071 -v /home/lopez/grobid/grobid-home/config/grobid.yaml:/opt/grobid/grobid-home/config/grobid.yaml:ro  grobid/grobid:0.7.3
 ```
 
 You need to use an absolute path to specify your modified `grobid.yaml` file.
@@ -230,13 +232,13 @@ docker build -t grobid/grobid:0.8.0-SNAPSHOT --build-arg GROBID_VERSION=0.8.0-SN
 In order to run the container of the newly created image, for example for the development version `0.8.0-SNAPSHOT`, using all GPU available:
 
 ```bash
-> docker run --rm --gpus all --init -p 8080:8070 -p 8081:8071 grobid/grobid:0.8.0-SNAPSHOT
+> docker run --rm --gpus all --init --ulimit core=0 -p 8080:8070 -p 8081:8071 grobid/grobid:0.8.0-SNAPSHOT
 ```
 
 In practice, you need to indicate which models should use a Deep Learning model implementation and which ones can remain with a faster CRF model implementation, which is done currently in the `grobid.yaml` file. Modify the config file `grobid/grobid-home/config/grobid.yaml` accordingly on the host machine and mount it when running the image as follow: 
 
 ```bash
-docker run --rm --gpus all --init -p 8080:8070 -p 8081:8071 -v /home/lopez/grobid/grobid-home/config/grobid.yaml:/opt/grobid/grobid-home/config/grobid.yaml:ro  grobid/grobid:0.8.0-SNAPSHOT
+docker run --rm --gpus all --init --ulimit core=0 -p 8080:8070 -p 8081:8071 -v /home/lopez/grobid/grobid-home/config/grobid.yaml:/opt/grobid/grobid-home/config/grobid.yaml:ro grobid/grobid:0.8.0-SNAPSHOT
 ```
 
 You need to use an absolute path to specify your modified `grobid.yaml` file.
@@ -270,7 +272,7 @@ Similarly, if you want to create a docker image from the current master, develop
 In order to run the container of the newly created image, for example for version `0.7.3`:
 
 ```bash
-> docker run -t --rm --init -p 8080:8070 -p 8081:8071 grobid/grobid:0.7.3
+> docker run --rm --init --ulimit core=0 -p 8080:8070 -p 8081:8071 grobid/grobid:0.7.3
 ```
 
 For testing or debugging purposes, you can connect to the container with a bash shell (logs are under `/opt/grobid/logs/`):