fqzhang42/jvbench

Performance analysis benchmark suite for the Java Vector API

JVBench Benchmark Suite

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.

List of benchmarks

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

Prerequisites

• OpenJDK HotSpot JDK 16 or above

Obtaining the suite

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 package

Running the suite

To 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

🤝 Contributing

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!