Browse > Article
http://dx.doi.org/10.7236/JIIBC.2018.18.6.201

A Study of The GPGPU Performance  

Lee, Jongbok (Dept of Electronics and Information Eng., Hansung University)
Publication Information
The Journal of the Institute of Internet, Broadcasting and Communication / v.18, no.6, 2018 , pp. 201-206 More about this Journal
Abstract
As the artificial intelligence and big data technology has been developed recently, the importance of GPGPU, which is a general purpose graphics processing unit, is emphasized. In addition, by the demand for mining equipment to obtain bit coins, which is a block chain application technology, the price of GPGPU has increased sharply with scarcity. If a GPGPU can be precisely simulated, it is possible to conduct experiments on various GPGPU types and analyze performance without purchasing expensive ones. In this paper, we investigate the configuration of a GPGPU simulator and measure the performance of various benchmark programs using GPGPU-Sim.
Keywords
GPGPU; GPGPU-Sim; performance;
Citations & Related Records
연도 인용수 순위
  • Reference
1 A. Bakhoda, G. L. Yuan, W. W. L. Fung, H. Wong, and T. M. Aamodt, "Analyzing CUDA Workloads Using a Detailed GPU Simulator," 2009 International Symposium on Performance Analysis of Systems and Software, pp.163-174, May. 2009.
2 A. Lshagar, A Baniasadi, "Performance in GPU Architectures : Potentials and Distances," 9th Annual Workshop on Duplicating, 2001.
3 W. W. L. Fung, I. Sham, G. Yuan, and T. M. Aamodt. Dynamic warp formation and scheduling for efficient GPU control flow. In Proc. 40th IEEE/ACM Int'l Symp. on Microarchitecture, 2007.
4 S. Ryoo, C. I. Rodrigues, S. S. Baghsorkhi, S. S. Stone, D. B. Kirk, and W. W. Hwu. Optimization principles and application performance evaluation of a multithreaded GPU using CUDA. In Proc. 13th ACM SIGPLAN Symp. on Principles and Practice of Parallel Programming, pages 73-82, 2008.
5 Z. S. Hakura and A. Gupta. The design and analysis of a cache architecture for texture mapping. In Proc. 24th Int'l Symp. on Computer Architecture, pages 108-120, 1997.
6 W. W. L. Fung, I. Sham, G. Yuan, and T. M. Aamodt. Dynamic warp formation and scheduling for efficient GPU control flow. In Proc. 40th IEEE/ACM Int'l Symp. on Microarchitecture, 2007.
7 NVIDIA Corporation. NVIDIA CUDA Programming Guide, 1.1 edition, 2007.
8 P. Harish and P. J. Narayanan. Accelerating Large Graph Algorithms on the GPU Using CUDA. In HiPC, pages 197-208, 2007.
9 M. Giles. Jacobi iteration for a Laplace discretisation on a 3D structured grid. http://people.maths.ox.ac.uk/gilesm/hpc/NVIDIA/laplace3d.pdf.
10 J. Michalakes and M. Vachharajani. GPU acceleration of numerical weather prediction. IPDPS 2008: IEEE Int'l Symp. on Parallel and Distributed Processing, pages 1-7, April 2008.