JVBench is a collection of diverse benchmarks that exercise the Java Vector API on typical SIMD workloads.
This benchmark suite includes a version of the workloads of the RIVEC suite after recasting them in Java and expressing vector operations with the Java Vector API.
The following table is a complete list of benchmarks included in JVBench in alphabetical order:
| Application Name | Application Domain | Algorithmic Model | Taken From |
|---|---|---|---|
| Axpy | High Performance Computing | BLAS | RIVEC |
| Blackscholes | Financial Analysis | Dense Linear Algebra | PARSEC |
| Canneal | Engineering | Unstructured Grids | PARSEC |
| Jacobi-2D | Engineering | Dense Linear Algebra | PolyBench |
| LavaMD | Molecular Dynamics | N-Body | Rodinia |
| Particlefilter | Medical Imaging | Structured Grids | Rodinia |
| Pathfinder | Grid Traversal | Dynamic Programming | Rodinia |
| Somier | Physics Simulation | Dense Linear Algebra | RIVEC |
| Streamcluster | Data Mining | Dense Linear Algebra | PARSEC |
| Swaptions | Financial Analysis | MapReduce Regular | PARSEC |
- OpenJDK HotSpot JDK 16 or above
To run the suite, you can download the suite JAR here. Alternatively, you can build it yourself. To do so, you will need Maven version 3.8 or above. To build an executable JAR, use the following command:
$ mvn clean packageTo run a JVBench benchmark, execute the following java command:
$ java --add-modules jdk.incubator.vector -jar JVBench-1.0.1.jar "<benchmarks>"where is the benchmark name that you wish to run. Please append the word "Benchmark" to the benchmark name. For example, to run benchmark Axpy, specify AxpyBenchmark as the benchmark.
By default, the suite executes each benchmark operation for a specific number of times. For thorough experimental evaluation, the benchmarks should be repeated for a large number of times or executed for a long time. The number of repetitions and the execution time can be set for all benchmarks using the -f, -wi, and -i options. For a complete description, please refer to JHM tutorial
Moreover, it is possible to override the default benchmark input with the following command:
$ java --add-modules jdk.incubator.vector <inputs> -jar JVBench-1.0.1.jar "<benchmarks>"For example, to specify an input size of 70k elements to Axpy, you can run the following command:
$ java --add-modules jdk.incubator.vector -Dsize=70000 -jar JVBench-1.0.1.jar "AxpyBenchmark"The default input (expressed as different system properties) for each benchmark is listed in the table below:
| Application Name | Default Input |
|---|---|
| Axpy | -Dsize=70000 |
| Blackscholes | -Dinput=/blackscholes/input/in_512K.input |
| Canneal | -Dnswaps=10000 -DTEMP=2000 -Dnetlist=canneal/input/2500000.nets -Dnsteps=300 |
| Jacobi-2D | -Dsize=10000 -Dtsteps=14 |
| LavaMD | -Dinput=/lavaMD/input/lavaMD_127776.input |
| Particlefilter | -Dx=128 -Dy=128 -Dz=24 -Dnp=32768 |
| Pathfinder | -Dinput=/pathfinder/input/pathfinder_5000_5000.input |
| Somier | -Dsteps=10 -Dn=128 |
| Streamcluster | -Dk1=3 -Dk2=10 -Ddim=128 -Dchunksize=128 -Dclustersize=10 -Dinput=/streamcluster/input/streamcluster_128_128.input |
| Swaptions | -Dms=64 -Dns=16384 |
You are welcome to contribute to this open-source benchmark suite. If you want to add or modify the code, feel free to fork the repo, create issues and finally a pull request to review your code!