An Implementation of the algorithms from Jansen & Land and Grage & Jansen, building upon an algorithm from Mounié, Rapine and Trystram.
- Algorithms for machine scheduling with malleable jobs
- Quick Start
- Execution with docker-compose
- Building docker images
- Configuration for testing
- A couple of Maven commands
Build the docker image and run it. The Dockerfile contains reasonable default values for all variables.
docker build -t malleable . && docker run malleable
docker build -t malleable . && docker run -e TEST_FILE_PATH=/testfiles -v $(pwd)/TestInstances:/testfiles:ro malleable
Output:
ohnesorge@DESKTOP-FELIX:/mnt/d/workspace/CPU-GPU-Scheduling$ docker build -t malleable . && docker run -e TEST_FILE_PATH=/testfiles -v $(pwd)/TestInstances:/testfiles:ro malleable
[+] Building 50.9s (12/12) FINISHED
...
=> => naming to docker.io/library/malleable:latest
12:12:35.857 [main] INFO de.ohnes.App - Starting Algorithm!
12:12:36.397 [main] INFO de.ohnes.App - Reading test file from /testfiles/TestInstance copy 2.json
12:12:36.398 [main] INFO de.ohnes.DualApproximationFramework - Starting dual approximation Framework with shelvesAlgo: CpuGpuApproach
12:12:36.434 [main] INFO de.ohnes.App - Ran instance with 3 machines and 8 jobs in 36 milliseconds.
12:12:36.437 [main] INFO de.ohnes.App - Computed Schedule:
///////////////////////////////////////////0002///////////////////////////////////////////###########################################0001###########################################/////////////////////////////////////////////////////0007/////////////////////////////////////////////////////#####################################################0006#####################################################
/////////////////////////////////////////////////////0005/////////////////////////////////////////////////////#####################################################0004#####################################################///////////////////////////////////////////0003///////////////////////////////////////////###########################################0000###########################################
12:12:36.557 [main] DEBUG de.ohnes.logger.MyElasticsearchClient - Trying to push test result to Elasticsearch...
12:12:36.684 [main] WARN de.ohnes.logger.MyElasticsearchClient - Couldn't reach ES Server. Saving data locally until next try.
12:12:36.692 [main] INFO de.ohnes.App - Reading test file from /testfiles/TestInstance copy 3.json
12:12:36.692 [main] INFO de.ohnes.DualApproximationFramework - Starting dual approximation Framework with shelvesAlgo: CpuGpuApproach
12:12:36.707 [main] INFO de.ohnes.App - Ran instance with 3 machines and 5 jobs in 15 milliseconds.
12:12:36.707 [main] INFO de.ohnes.App - Computed Schedule:
////////////////////////////0000////////////////////////////
///////////////////////0001///////////////////////
/////////////////////////////////0002/////////////////////////////////##################0004##################
/////////////////////////////////0002/////////////////////////////////
////////////////////////////0003////////////////////////////
...Hint: before execution docker-compose the images need to be build using docker. For this see section Docker.
Docker-compose can be started with the following command:
docker-compose up -d
The logs of each container should look something like this:
19:33:00.888 [main] INFO de.ohnes.App - Starting Algorithm!
19:33:01.337 [main] INFO de.ohnes.DualApproximationFramework - Starting dual approximation Framework with shelvesAlgo: KilianApproach
19:33:04.141 [main] INFO de.ohnes.App - Ran instance with 90 machines and 81 jobs in 2 seconds.
19:33:04.142 [main] INFO de.ohnes.DualApproximationFramework - Starting dual approximation Framework with shelvesAlgo: KilianApproach
The docker image can be build with the following command.
docker build -t malleable .
The dockerfile is written as a multi-stage dockerfile. Therefore there is no need to build the maven project first or making sure you have the correct maven/java version. Just build the docker container and go!
All parameters are tunable via the environment variables. Note that the code does support randomly generated instances but also allows reading in user-specified .json files containing an instance. (format as in ./TestInstances/).
| Parameter (Env variable) | Description | Default |
|---|---|---|
| NB_TESTS | Number of tests to run. | 10 |
| EPSILON | Epsilon (primarily for the disired accuracy) | 0.1 |
| INSTANCE_MINJOBS | Minimum number of jobs in the test instance. | 10 |
| INSTANCE_MAXJOBS | Maximum number of jobs in the test instance. | 10 |
| INSTANCE_MINMACHINES | Minimum number of malleable machines in the test instance. | 10 |
| INSTANCE_MAXMACHINES | Maximum number of malleable machines in the test instance. | 20 |
| INSTANCE_SEQMACHINES | The number of sequential machine in relation to the malleable machines. | 0.2 |
| INSTANCE_MAX_SEQUENTIAL_TIME | The maximum sequential processing time of any job, also the malleable processing time on a single machine. | 100 |
| ES_HOST | Elasticsearch host. | localhost |
| ES_PORT | Elasticsearch port. | 9200 |
| ES_INDEX | Elasticsearch index. | results |
Once you have configured your project in your IDE you can build it from there. However if you prefer you can use maven from the command line. In that case you could be interested in this short list of commands:
mvn compile: it will just compile the code of your application and tell you if there are errorsmvn test: it will compile the code of your application and your tests. It will then run your tests (if you wrote any) and let you know if some failsmvn install: it will do everythingmvn testdoes and then if everything looks file it will install the library or the application into your local maven repository (typically under /.m2). In this way you could use this library from other projects you want to build on the same machine
If you need more information please take a look at this quick tutorial.