Reinventing the tuning and debugging tools for multi-thousand cores computer systems

重新发明数千核​​计算机系统的调优和调试工具

• 批准号: RGPIN-2017-05634
• 负责人: Dagenais, Michel
• 金额: $ 2.04万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=637715
• 关键词: Reinventing; tuning; debugging; tools; multi

The top supercomputers in recent years owe much of their power to the number-crunching ability of Graphical Processing Units (GPU) used for General Purpose computation (GPGPU). However, GPGPUs are also frequently used in smaller clusters and individual workstations for demanding tasks. Even in mobile phones and embedded systems, GPGPUs are an efficient medium to accomplish specialised tasks such as image processing. Furthermore, GPGPUs are at the forefront of a wider trend towards heterogeneous system architecture (HSA), where specialised co-procesors are used for a number of tasks beyond graphics and video, such as signal processing and network packet processing.

近年来的顶级超级计算机在很大程度上归功于用于通用计算（GPGPU）的图形处理单元（GPU）的数字运算能力。然而，GPGPU也经常用于较小的集群和单个工作站，以完成要求苛刻的任务。即使在移动的电话和嵌入式系统中，GPGPU也是完成图像处理等专门任务的有效媒介。此外，GPGPU处于异构系统架构（HSA）更广泛趋势的最前沿，其中专用协处理器用于图形和视频之外的许多任务，例如信号处理和网络数据包处理。