![]() ![]() This is because the primary container is typically used only for running the steps and not for its ENTRYPOINT, and an ENTRYPOINT may consume significant resources or exit prematurely. ![]() The environment settings apply to the entrypoint/command run by the docker container, not the job steps.Īuthentication for registries using standard docker login credentialsĪuthentication for AWS Elastic Container Registry (ECR)įor a primary container (the first container in the list) if neither command nor entrypoint is specified in the config, then any ENTRYPOINT and COMMAND in the image are ignored. Which user to run commands as within the Docker containerĪ map of environment variable names and values. It will be used as arguments to the image ENTRYPOINT if it has one, or as the executable if the image has no ENTRYPOINT. The command used as pid 1 (or args for entrypoint) when launching the container. entrypoint overrides the image’s ENTRYPOINT. The command used as executable when launching the container. This field is useful if you would rather have a different hostname instead of localhost, for example, if you are starting multiple versions of the same service. By default, all services are exposed directly on localhost. Name defines the the hostname for the container (the default is localhost), which is used for reaching secondary (service) containers. The first image listed under a job defines the job’s own primary container image where all steps will run. The name of a custom docker image to use. If more than one is set you will receive an error.Ĭonfigured by docker key which takes a list of maps: Key (1) One executor type should be specified per job. See Workflows for configuring branch execution for jobs in a workflow or 2.1 config.Īmount of CPU and RAM allocated to each container in a job. Number of parallel instances of this job to run (default: 1)Ī map of environment variable names and values.Ī map defining rules to allow/block execution of specific branches for a single job that is not in a workflow or a 2.1 config (default: all allowed). working_directory will be created automatically if it doesn’t exist. Note: Paths written in your YAML configuration file will not be expanded if your store_test_results.path is $CIRCLE_WORKING_DIRECTORY/tests, then CircleCI will attempt to store the test subdirectory of the directory literally named $CIRCLE_WORKING_DIRECTORY, dollar sign $ and all. Processes run during the job can use the $CIRCLE_WORKING_DIRECTORY environment variable to refer to this directory. Default: ~/project (where project is a literal string, not the name of your specific project). Parameters for making a job explicitly configurable in a workflow. ![]() Can be overridden by shell in each step (default: See Default Shell Options) Shell to use for execution command in all steps. The value map has the following attributes: Key A name should be case insensitive unique within a current jobs list. Excluding sets of parameters from a matrixĮach job consists of the job’s name as a key and a map as a value.Available Windows machine images on server.Available Linux machine images on server.We describe some of these innovative feature introductions with more detail in a new blog Enhancing Memory Allocation with New NVIDIA CUDA 11.2 Features, and we will publish additional blogs on compiler enhancements shortly. ![]() This new 11.2 release also delivers programming model updates to CUDA Graphs and Cooperative Groups, as well as expanding support for latest generation operating systems and compilers. Today, CUDA 11.2 is introducing improved user experience and application performance through a combination of driver/toolkit compatibility enhancements, new memory suballocator feature, and compiler enhancements including an LLVM upgrade. CUDA Toolkit is a complete, fully-featured software development platform for building GPU-accelerated applications, providing all the components needed to develop apps targeting every NVIDIA GPU platform.ĬUDA 11 announced support for the new NVIDIA A100 based on the NVIDIA Ampere architecture, and CUDA 11.1 delivered support for NVIDIA GeForce RTX 30 Series and Quadro RTX Series GPU platforms. ![]()
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