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Soot class loading in the rootbeer GPU compiler
2013
Proceedings of the 2nd ACM SIGPLAN International Workshop on State Of the Art in Java Program analysis - SOAP '13
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This enables us to load significantly less information in memory to enable program analyses. We implemented our approach for loading Java bytecode in the Soot-based ROOTBEER compiler. ...
One of the first activities of the Soot program analysis framework is to load the classes for analysis. With the current class loader, more classes are loaded than necessary. ...
ROOTBEER-Specific Overrides The ROOTBEER GPU Compiler needs additional information in the loaded Scene that would not be present in the classes loaded previously. ...
doi:10.1145/2487568.2487573
dblp:conf/pldi/Pratt-SzeligaLMFW13
fatcat:jjitkpy65fdttmkaq6uwvgvhsu
D4.1 Programming Language And Runtime System: Requirements
2016
Zenodo
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One of the components in the VINEYARD is the programming model and runtime system support, which is developed in Work Package 4. ...
This document elaborates the requirements for the VINEYARD programming model and runtime system. ...
RootBeer Rootbeer 23 allows programmers to express GPU kernels in Java code. The programmer defines a base class that kernels need to specialise. ...
doi:10.5281/zenodo.898162
fatcat:h4qoibk26vfzdao5badtj6fdie
Boosting Java Performance using GPGPUs
[article]
2015
arXiv
pre-print
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The compiler, in turn, exploits this information in order to automatically generate code without requiring additional code refactoring. ...
Currently, significant engineering efforts are undertaken in order to enable existing programming languages to perform heterogeneous execution mainly on GPUs. ...
Acknowledgments This work is supported by the AnyScale Apps and PAMELA projects funded by EPSRC EP/L000725/1 and EP/K008730/1. Dr Luján is supported by a Royal Society University Research Fellowship. ...
arXiv:1508.06791v1
fatcat:y5cf4sexrfe7zn3ry7xwntpavm
Boosting Java Performance Using GPGPUs
[chapter]
2017
Lecture Notes in Computer Science
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Experimental results show an average performance speedup of 19x, using NVIDIA Tesla K20m GPU, and a 4x decrease in code complexity when compared with writing multi-threaded Java code across eight evaluated ...
We demonstrate the advantages of Jacc, both in terms of programmability and performance, by evaluating it against existing Java frameworks. ...
(JNI)
GPU Code
@Jacc enabled
Java Applications
Jacc Compiler
Jacc Compiler
Front End
Soot
Kernel Prep
ISA Bridge
PTX Conversion
Back End
PTX Emitter
Mid End
Optimizations
iaload ...
doi:10.1007/978-3-319-54999-6_5
fatcat:ns5erd4sfrdixiqpuek5ssusyu
Accelerating Java on Embedded GPU
2014
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The existing solutions in literature address various techniques and benefits of offloading Java on desktop or server grade GPUs and not on embedded GPUs. ...
To the best of our knowledge, this is the first work done on accelerating Java on an embedded GPU. ...
Rootbeer Static Transformer reads the .class file from the input jar and, using Soot [36] , it converts the .class file to an intermediate three component representation called Jimple [2] . ...
doi:10.20381/ruor-3583
fatcat:42db6jqmobbc5e3p544o6ge56m