0g-chain/simulations/README.md
rhuairahrighairigh a3108dcccb fix typo
2019-09-26 15:37:03 -04:00

44 lines
1.8 KiB
Markdown

# How To Run Sims In The Cloud
Sims run with AWS batch, with results uploaded to S3
## AWS Batch
In AWS batch you define:
- a "compute environment"--just how many machines you want (and of what kind)
- a "job queue"--just a place to put jobs (pairs them with a compute environment)
- a "job definition"--a template for jobs
Then to run stuff you create "jobs" and submit them to a job queue.
The number of machines running auto-scales to match the number of jobs. When there are no jobs there are no machines, so you don't pay for anything.
Jobs are defined as a docker image (assumed hosted on dockerhub) and a command string.
>e.g. `kava/kava-sim:version1`, `go test ./app`
This can run sims but doesn't collect the results. This is handled by a custom script.
## Running sims and uploading to S3
The dockerfile in this repo defines the docker image to run sims. It's just a normal app, but with the aws cli included, and the custom script.
The custom script reads some input args, runs a sim and uploads the stdout and stderr to a S3 bucket.
AWS Batch allows for "array jobs" which are a way of specifying many duplicates of a job, each with a different index passed in as an env var.
### Steps
- create and submit a new array job (based of the job definition) with
- image `kava/kava-sim:<some-version>`
- command `run-then-upload.sh <starting-seed> <num-blocks> <block-size>`
- array size of how many sims you want to run
- any changes needed to the code or script necessitates a rebuild:
- `docker build -f simulations/Dockerfile -t kava/kava-sim:<some-version> .`
- `docker push kava/kava-sim:<some-version>`
### Tips
- click on the compute environment name, to get details, then click the link ECS Cluster Name to get details on the actual machines running
- for array jobs, click the job name to get details of the individual jobs