14247

Characterizing and Optimizing Irregular Applications on Graphics Processing Units

Tao Zhang
The University of New Mexico, Albuquerque, New Mexico
The University of New Mexico, 2015

@article{zhang2015characterizing,

   title={Characterizing and Optimizing Irregular Applications on Graphics Processing Units},

   author={Zhang, Tao},

   year={2015}

}

Download Download (PDF)   View View   Source Source   

842

views

In recent years, GPGPUs have experienced tremendous growth as general-purpose and high-throughput computing devices. Applications from various domains achieve significant speedups using GPGPUs. However, irregular applications do not perform well due to the mismatches between irregular problem structures and SIMD-like GPU architectures. The lack of in-depth characterization and quantifying the ways in which irregular applications differ from regular ones on GPGPUs has prevented users from effectively making use of the hardware resource. To characterize the performance aspects and analyze the bottlenecks, a suite of representative irregular applications are examined on a cycle-accurate GPU simulator as well as a real GPU. The experimental results identify control-flow divergences, irregular memory accesses and load imbalances as major issues degrading performance. Therefore, software and hardware approaches are proposed to improve the performance of irregular applications on GPUs. Specifically, a task-pool software approach is designed to load balancing irregular applications. To facilitate the application of this approach, an open-source library called CUIRRE is proposed which can characterize and load balance general irregular applications through convenient APIs. CUIRRE performs online load balancing & profiling and offline analyzing for the tradeoff of performance and accuracy. In addition, a gGraph platform for graph processing is designed and implemented based on the task-pool approach. GGraph can handle the irregularity of graph data and/or graph algorithms on GPUs, and exploits full parallelism and full overlap of CPU processing and I/O processing as much as possible. Finally, several general irregular applications and three graph algorithms are optimized using the CUIRRE library and the gGraph platform respectively, achieving remarkable speedups.
Rating: 2.5/5. From 1 vote.
Please wait...

* * *

* * *

Featured events

2018
November
27-30
Hida Takayama, Japan

The Third International Workshop on GPU Computing and AI (GCA), 2018

2018
September
19-21
Nagoya University, Japan

The 5th International Conference on Power and Energy Systems Engineering (CPESE), 2018

2018
September
22-24
MediaCityUK, Salford Quays, Greater Manchester, England

The 10th International Conference on Information Management and Engineering (ICIME), 2018

2018
August
21-23
No. 1037, Luoyu Road, Hongshan District, Wuhan, China

The 4th International Conference on Control Science and Systems Engineering (ICCSSE), 2018

2018
October
29-31
Nanyang Executive Centre in Nanyang Technological University, Singapore

The 2018 International Conference on Cloud Computing and Internet of Things (CCIOT’18), 2018

HGPU group © 2010-2018 hgpu.org

All rights belong to the respective authors

Contact us: