9647

A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels

Paul Rosen
Scientific Computing and Imaging Institute, University of Utah
Computer Graphics Forum (EuroVis), 2013

@article{preim2013visual,

   title={A Visual Approach to Investigating Shared and Global Memory Behavior of CUDA Kernels},

   author={Preim, B and Rheingans, P and Theisel, H},

   year={2013}

}

Download Download (PDF)   View View   Source Source   

1330

views

We present an approach to investigate the memory behavior of a parallel kernel executing on thousands of threads simultaneously within the CUDA architecture. Our top-down approach allows for quickly identifying any significant differences between the execution of the many blocks and warps. As interesting warps are identified, we allow further investigation of memory behavior by visualizing the shared memory bank conflicts and global memory coalescence, first with an overview of a single warp with many operations and, subsequently, with a detailed view of a single warp and a single operation. We demonstrate the strength of our approach in the context of a parallel matrix transpose kernel and a parallel 1D Haar Wavelet transform kernel.
No votes yet.
Please wait...

* * *

* * *

HGPU group © 2010-2017 hgpu.org

All rights belong to the respective authors

Contact us: