首页> 外文会议>International Symposium on Parallel and Distributed Computing >Heuristic Optimization Methods for Improving Performance of Recursive General Purpose Applications on GPUs
【24h】

Heuristic Optimization Methods for Improving Performance of Recursive General Purpose Applications on GPUs

机译:提高GPU递归通用应用性能的启发式优化方法

获取原文

摘要

Due to the demand of high definition graphics presentation in gaming and video market, Graphics Processing Units (GPUs) have drastically increased their computational capacities. General-Purpose computation on GPUs uses the fragment shader multicore of these processing units to concurrently process data streams. However, the I/O overheads in recursive GPGPU applications have a negative impact in the performance of those systems. This paper proposes the remap method to improve the performance of general purpose recursive applications on GPUs, by decreasing the I/O overheads imposed by the VRAM/GPU interface. It is shown that significant performance improvements are achieved by applying the remap method to realistic recursive applications.
机译:由于游戏和视频市场中高定义图形演示的需求,图形处理单元(GPU)急剧增加了它们的计算能力。 GPU上的通用计算使用这些处理单元的片段着色器多核来同时处理数据流。然而,递归GPGPU应用中的I / O开销在这些系统的性能方面具有负面影响。本文提出了remap方法,以通过减少VRAM / GPU接口施加的I / O开销来提高GPU上通用递归应用的性能。结果表明,通过将REMAP方法应用于现实递归应用来实现显着的性能改进。

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