20838

Tools for Reduced Precision Computation: A Survey

Stefano Cherubin, Giovanni Agosta
Politecnico di Milano, ITA
ACM Computing Surveys, 33, 2020

@article{cherubin2020tools,

   title={Tools for Reduced Precision Computation: A Survey},

   author={Cherubin, Stefano and Agosta, Giovanni},

   journal={ACM Computing Surveys (CSUR)},

   volume={53},

   number={2},

   pages={1–35},

   year={2020},

   publisher={ACM New York, NY, USA}

}

Download Download (PDF)   View View   Source Source   

427

views

The use of reduced precision to improve performance metrics such as computation latency and power consumption is a common practice in the embedded systems field. This practice is emerging as a new trend in High Performance Computing (HPC), especially when new error-tolerant applications are considered. However, standard compiler frameworks do not support automated precision customization, and manual tuning and code transformation is the approach usually adopted in most domains. In recent years, research have been studying ways to improve the automation of this process. This article surveys this body of work, identifying the critical steps of this process, the most advanced tools available, and the open challenges in this research area. We conclude that, while several mature tools exist, there is still a gap to close, especially for tools based on static analysis rather than profiling, as well as for integration within mainstream, industry-strength compiler frameworks.
Rating: 2.0/5. From 1 vote.
Please wait...

* * *

* * *

HGPU group © 2010-2020 hgpu.org

All rights belong to the respective authors

Contact us: