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https://github.com/jjfumero/marawacc
Parallel programming framework for accelerating Java programs on GPUs and multi-core CPUs.
https://github.com/jjfumero/marawacc
acceleleration code-generation gpus graal graalvm java jit jvm opencl phd-thesis
Last synced: about 2 months ago
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Parallel programming framework for accelerating Java programs on GPUs and multi-core CPUs.
- Host: GitHub
- URL: https://github.com/jjfumero/marawacc
- Owner: jjfumero
- License: gpl-2.0
- Created: 2020-12-07T08:34:37.000Z (about 4 years ago)
- Default Branch: master
- Last Pushed: 2021-04-11T06:32:35.000Z (over 3 years ago)
- Last Synced: 2023-10-03T20:53:55.005Z (about 1 year ago)
- Topics: acceleleration, code-generation, gpus, graal, graalvm, java, jit, jvm, opencl, phd-thesis
- Language: Java
- Homepage:
- Size: 802 KB
- Stars: 3
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# 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](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](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:
```bash
-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.
```java
public class Hello {
public static void main(String[] args) {
// Main Function in JPAI is the ArrayFunction
// ArrayFunction computes a function from types T to R
ArrayFunction, Double> computation = new MapAccelerator<>(vectors -> (2.5 * vectors._1() + vectors._2());
// Prepare the input data
int size = 262144;
PArray> input = new PArray<>(size, TypeFactory.Tuple("Tuple2"));
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 output = computation.apply(input);
}
}
```
* ArrayFunction: 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](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](https://era.ed.ac.uk/handle/1842/28718)
### 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
#### Supervisors
* Christophe Dubach
* Michel Steuwer