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Algorithm for automatic loop parallelization for graphics processing units

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Titel: Algorithm for automatic loop parallelization for graphics processing units
Autoren: Doroshenko, A.Yu., Achour, I.Z.
Verlagsinformationen: Інститут програмних систем НАН України
Publikationsjahr: 2018
Schlagwörter: Android NDK, Android SDK, JDK, JVM, JNI, OpenGL ES, Java, affine transformations, UDC 681.3
Beschreibung: This work contains description of high-performance batched affine matrices multiplication approach in scope of An-droid NDK and JNI. Approach is based on combination of separate technics and practices. Android Native Development Kit and Java Native Interfaces were used to develop and run high-performance code via Java Virtual Machine. This approach overhead was minimized with input data batching for computation. Compile-time optimization approaches were used to speed-up C/C++/Java based solutions. As a development, analysis and research result precise performance benchmarks were made. Output solution was compared with analogues, which are using limited sets of applied techniques, features and approaches. Charts were built on top of that results. Appropriate decisions were made.Problems in programming 2018; 1: 36-45
Publikationsart: other/unknown material
Sprache: Ukrainian
Verfügbarkeit: https://harvester.nas.gov.ua/Record/pp_isofts_kiev_ua-article-236
Dokumentencode: edsbas.EADD9ACC
Datenbank: BASE
Beschreibung
Abstract:This work contains description of high-performance batched affine matrices multiplication approach in scope of An-droid NDK and JNI. Approach is based on combination of separate technics and practices. Android Native Development Kit and Java Native Interfaces were used to develop and run high-performance code via Java Virtual Machine. This approach overhead was minimized with input data batching for computation. Compile-time optimization approaches were used to speed-up C/C++/Java based solutions. As a development, analysis and research result precise performance benchmarks were made. Output solution was compared with analogues, which are using limited sets of applied techniques, features and approaches. Charts were built on top of that results. Appropriate decisions were made.Problems in programming 2018; 1: 36-45