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https://github.com/aws-samples/aws-batch-efa
https://github.com/aws-samples/aws-batch-efa
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/aws-samples/aws-batch-efa
- Owner: aws-samples
- License: mit-0
- Created: 2019-10-10T14:09:41.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2021-10-04T20:42:38.000Z (about 3 years ago)
- Last Synced: 2024-08-01T19:43:32.864Z (4 months ago)
- Language: Shell
- Size: 20.5 KB
- Stars: 4
- Watchers: 4
- Forks: 6
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
Awesome Lists containing this project
- awesome-aws-research - AWS Batch with Elastic Fabric Adapter (EFA)
README
## Sample code to setup NAS Parallel Benchmark using EFA and AWS Batch
This is the sample code for the AWS Batch Blog: Run High Performance Computing Workloads using AWS Batch MultiNode Jobs with Elastic Fabric Adapter
## License
This library is licensed under the MIT-0 License. See the LICENSE file.
# AWS Batch + EFA
To get started, clone this repo locally:
```bash
git clone https://github.com/aws-samples/aws-batch-efa.git
cd aws-batch-efa-blogpost/
```
### AWS Batch Resources
In part 1, we'll create all the necessary AWS Batch resources.
```bash
cd batch-resources/
```
First we'll create a launch template, this launch template installs EFA on the instance and configures the network interface to use EFA. In the `launch_template.json` file substitute ``, ``, `` and `` with your your information.
Now create the launch template:
```bash
aws ec2 create-launch-template --cli-input-json file://launch_template.json
```
To ensure optimal physical locality of instances, we create a [placement group](https://docs.aws.amazon.com/AWSEC2/latest/WindowsGuide/placement-groups.html#placement-groups-cluster), with strategy `cluster`.
```bash
aws ec2 create-placement-group --group-name "efa" --strategy "cluster" --region [your_region]
```
Next, we'll create the compute environment, this defines the instance type, subnet and IAM role to be used. Edit the `` and `` sections with the pertinent information. Then create the compute environment:
```bash
aws batch create-compute-environment --cli-input-json file://compute_environment.json
```
Finally we need a job queue to point to the compute environment:
```bash
aws batch create-job-queue --cli-input-json file://job_queue.json
```
### Dockerfile
In part 2, we build the docker image and upload it to Elastic Container Registery (ECR), so we can use it in our job.
```bash
cd ..
pwd # you should be in the aws-batch-efa-blogpost/ directory
```
First we'll build the docker image, to help with this, we included a `Makefile`, simply run:
```bash
make
```
Then you can push the docker image to ECR, first modify the top of the `Makefile` with your region and account id:
```bash
AWS_REGION=[your region]
ACCOUNT_ID=[your account id]
```
Next, push to ECR, note the `Makefile` assumes you have an ECR repo named `aws-batch-efa`:
```bash
make push # logs in, tags, and pushes to ECR
```
### Job Definition
```bash
cd batch-resources/
```
Now we need a job definition, this defines which docker image to use for the job, edit the `job_definition.json` file and substitute `` and ``. Then create the job definition:
```
aws batch register-job-definition --cli-input-json file://job_definition.json
{
"jobDefinitionArn": "arn:aws:batch:us-east-1::job-definition/EFA-MPI-JobDefinition:1",
"jobDefinitionName": "EFA-MPI-JobDefinition",
"revision": 1
}
```
### Submit a job
Go back to the main directory:
```bash
cd ..
```
Finally we can submit a job!
```bash
make submit
```
### Credit
* Arya Hezarkhani, Software Development Engineer, AWS Batch
* Jason Rupard, Principal Systems Development Engineer, AWS Batch
* Sean Smith, Software Development Engineer II, AWS HPC