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README

Marawacc is a compiler framework for OpenCL Just-In-Time (JIT) that automatically compiles a subset of the Java bytecode into OpenCL, and a runtime system that orchestrates the execution of the GPU program within Java. Marawacc is a research prototype.

Marawacc makes use of the Graal compiler and Truffle DSL (https://github.com/graalvm/graal) to optimise Java and R programs on top of the JVM.

Marawacc integrates an API, called JPAI (Java Parallel Array Interface) [2] to develop GPU and multi-core Java applications using the Function interface in Java 8.

JPAI is a new Java API based on Java 8 Stream for parallel and heterogeneous programming. JPAI uses algorithmic skeletons and the new feature of Java lambda expressions to facilitate the programmability and readability. Parallel operations using map/reduce in JPAI can be composed and reused.

Install Marawacc

See the INSTALL.md in this repository.

Run Marawacc

Once Marawacc is compiled, it runs within the Graal VM. To enable OpenCL JIT compilation you need the following flags:

-jvmci -XX:-BootstrapJVMCI -XX:-UseJVMCIClassLoader -Dmarawacc.printOCLKernel=true

Marawacc Options

See DOCUMENTATION_OPTIONS.md file in this repository.

Example in JPAI

Marawacc is the backend that generates OpenCL code at runtime from the Graal IR and executes the GPU program. JPAI is the interface to program GPUs and multi-core CPUs. For GPU execution, JPAI invokes Marawacc. This section shows a full example in JPAI.

public class Hello {

    public static void main(String[] args) {

        // Main Function in JPAI is the ArrayFunction<T, R>
        // ArrayFunction computes a function from types T to R 
        ArrayFunction<Tuple2<Integer, Integer>, Double> computation = new MapAccelerator<>(vectors -> (2.5 * vectors._1() + vectors._2());

        // Prepare the input data
        int size = 262144;
        PArray<Tuple2<Integer, Integer>> input = new PArray<>(size, TypeFactory.Tuple("Tuple2<Integer, Integer>"));
        for (int i = 0; i < size; ++i) {
            input.put(i, new Tuple2<>((double) i, (double) (i + 2)));
        }

        // Compute on the GPU. The apply method will generate the OpenCL code and execute it on the GPU. 
        PArray<Double> output = computation.apply(input);
    }
}
  • ArrayFunction<T, R>: it is the main class in JPAI. It extends the Function interface in Java 8 with algorithmic skeletons such as map and reduce.
  • PArray: Portable Array (PArray) is a data structure created for avoiding the data transformation between Java and OpenCL (marshalling) and increase the overall performance. Details of the PArray data structure in [1].

Publications

[1] Juan Jos� Fumero, Toomas Remmelg, Michel Steuwer, and Christophe Dubach. 2015. Runtime Code Generation and Data Management for Heterogeneous Computing in Java. In Proceedings of the Principles and Practices of Programming on The Java Platform (PPPJ '15). ACM, New York, NY, USA, 16-26. DOI: http://dx.doi.org/10.1145/2807426.2807428

[2] Juan José Fumero, Michel Steuwer, and Christophe Dubach. 2014. A Composable Array Function Interface for Heterogeneous Computing in Java. In Proceedings of ACM SIGPLAN International Workshop on Libraries, Languages, and Compilers for Array Programming (ARRAY'14). ACM, New York, NY, USA, Pages 44, 6 pages. DOI=http://dx.doi.org/10.1145/2627373.2627381

Marawacc is used as a backend for FastR+GPU project (OpenCL JIT compilation for the R programs using Partial Evaluation in Graal)

[3] Juan Fumero, Michel Steuwer, Lukas Stadler, and Christophe Dubach. 2017. Just-In-Time GPU Compilation for Interpreted Languages with Partial Evaluation. In Proceedings of the 13th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments (VEE '17). ACM, New York, NY, USA, 60-73. DOI: https://doi.org/10.1145/3050748.3050761

[4] Juan Fumero, Michel Steuwer, Lukas Stadler, Christophe Dubach. OpenCL JIT Compilation for Dynamic Programming Language. MoreVMs 2017. http://conf.researchr.org/event/MoreVMs-2017/morevms-2017-papers-opencl-jit-compilation-for-dynamic-programming-languages

[5] Juan Fumero. Accelerating interpreted programming languages on GPUs with just-in-time compilation and runtime optimisations. PhD Dissertation, 30/11/2017 - Link

License

GPL V2

Who do I talk to?

Marawacc project is a part of my PhD at the University of Edinburgh. My PhD has been partially funded by Oracle Labs.

Main Developer

  • Juan Fumero <juan.fumero @ manchester.ac.uk>

Supervisors

  • Christophe Dubach <christophe.dubach @ ed.ac.uk>
  • Michel Steuwer <michel.steuwer @ ed.ac.uk >