Analysis of Impact of Correlation Between Hardware Configuration and Branch Handling Methods Executing General Purpose Applications

범용 응용프로그램 실행 시 하드웨어 구성과 분기 처리 기법에 따른 GPU 성능 분석

  • 최홍준 (전남대학교 전자컴퓨터공학부) ;
  • 김철홍 (전남대학교 전자컴퓨터공학부)
  • Received : 2013.01.07
  • Accepted : 2013.03.07
  • Published : 2013.03.28


Due to increased computing power and flexibility of GPU, recent GPUs execute general purpose parallel applications as well as graphics applications. Programmers can use GPGPU by using the APIs from GPU vendors. Unfortunately, computational resources of GPU are not fully utilized when executing general purpose applications because of frequent branch instructions. To handle the branch problem, several warp formations have been proposed. Intuitively, we expect that the warp formations providing higher computational resource utilization show higher performance. Contrary to our expectations, according to simulation results, the performance of the warp formation providing better utilization is lower than that of the warp formation providing worse utilization. This is because warp formation providing high utilization causes serious memory bottleneck due to increased memory request. Therefore, warp formation providing high computation utilization cannot guarantee high performance without proper hardware resources. For this reason, we will analyze the correlation between hardware configuration and warp formation. Our simulation results present the guideline to solve the underutilization problem due to branch instructions when designing recent GPU.


GPU;GGPPU;General-purpose Application;Branch Instruction;Warp Formation


Supported by : 한국연구재단, 정보통신산업진흥원


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