首页> 外文会议>2014 International Conference on Advances in Engineering and Technology Research >Implementing adaptive and dynamic data structures using CUDA parallelism
【24h】

Implementing adaptive and dynamic data structures using CUDA parallelism

机译:使用CUDA并行性实现自适应和动态数据结构

获取原文
获取原文并翻译 | 示例

摘要

Dynamic data structures are the key to many highly efficient and optimized implementations. On CPU, dynamic data structures can grow and shrink at run time by allocating and de-allocating memory from a place called heap and link those blocks using pointers. Adaptive data structure means changing the internal properties and structures of the data structure at run time according to requirement for various purposes, known as adaptive use of data structure. When we consider parallelism on GPUs using CUDA, there are many limitations on what can be used as data structure on GPU's global and shared memory. Generally simple arrays are handled on the GPU memory. Programmers need to find ways to present different data structures in terms of multiple arrays. In this paper, we have studied and implemented dynamic data structures & adaptive methodologies on GPU. We majorly explore the concept dynamic parallelism available in latest CUDA devices by implementing and analyzing quick sort and kernel call wise break down on latest NVIDIA's Kepler Architecture GPU. We also experimented with basic array operations on GPU by implementing minimum number finding. Implementation using CUDA results in very high performance gain.
机译:动态数据结构是许多高效和优化实现的关键。在CPU上,动态数据结构可以在运行时通过在称为堆的位置分配和取消分配内存并使用指针链接这些块来在运行时增长和收缩。自适应数据结构是指在运行时根据各种目的的要求更改数据结构的内部属性和结构,称为数据结构的自适应使用。当我们考虑使用CUDA的GPU上的并行性时,对于可以用作GPU全局和共享内存上的数据结构的东西有很多限制。通常,简单的数组在GPU内存中处理。程序员需要找到以多个数组表示不同数据结构的方法。在本文中,我们已经研究并在GPU上实现了动态数据结构和自适应方法。我们主要通过在最新的NVIDIA的Kepler Architecture GPU上实现和分析快速排序和内核调用明智分解,来探索最新CUDA设备中可用的概念动态并行性。我们还通过实现最小数量查找,对GPU上的基本阵列操作进行了实验。使用CUDA的实现可带来非常高的性能提升。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号