Algorithm for automatic loop parallelization for graphics processing units
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-perfor...
Збережено в:
| Дата: | 2018 |
|---|---|
| Автори: | , |
| Формат: | Стаття |
| Мова: | Ukrainian |
| Опубліковано: |
Інститут програмних систем НАН України
2018
|
| Теми: | |
| Онлайн доступ: | https://pp.isofts.kiev.ua/index.php/ojs1/article/view/236 |
| Теги: |
Додати тег
Немає тегів, Будьте першим, хто поставить тег для цього запису!
|
| Назва журналу: | Problems in programming |
| Завантажити файл: |  |
Репозитарії
Problems in programming| Резюме: | 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 |
|---|