ITK/Release 4/GPU Acceleration/Tcon-2010-11-22: Difference between revisions
From KitwarePublic
< ITK | Release 4 | GPU Acceleration
Jump to navigationJump to search
| Line 20: | Line 20: | ||
*** Expose the interactions with the GPU | *** Expose the interactions with the GPU | ||
*** Most GPU programmers do things synchronously (so they unfortunately do too many data transfers, and don't get full benefit from the GPU). | *** Most GPU programmers do things synchronously (so they unfortunately do too many data transfers, and don't get full benefit from the GPU). | ||
* Joe asked for typical Use Cases | |||
** We listed: | |||
*** Radiology : 100Mb per image (512x512x200) | |||
*** Microscopy : 10Gb | |||
*** Video : 10Mb images, 30~100 frames per second. | |||
* CUDA vs OpenCL ? | * CUDA vs OpenCL ? | ||
Revision as of 18:22, 22 November 2010
Attendees
- Won Ki - Harvard University
- Joe Stem - NVIDIA
- Kimberly Powell - NVIDIA
- Dennis Sessanna - NVIDIA
- Luis Ibanez - Kitware Inc.
Topics
Overview
- Quick summary of ITKv4 effort (Luis Ibanez)
- Summary of ITK-GPU approach (Won Ki)
Questions
- Level of abstraction ?
- Joe suggests to look at OpenCV
- Expose the interactions with the GPU
- Most GPU programmers do things synchronously (so they unfortunately do too many data transfers, and don't get full benefit from the GPU).
- Joe suggests to look at OpenCV
- Joe asked for typical Use Cases
- We listed:
- Radiology : 100Mb per image (512x512x200)
- Microscopy : 10Gb
- Video : 10Mb images, 30~100 frames per second.
- We listed:
- CUDA vs OpenCL ?
