1. A Novel Approach for Online-Monitoring for High Data-Rate Image-Based Instrumentation
Suren Chilingaryan, Andreas Kopmann
Forschungszentrum Karlsruhe, Germany
Goal: Processing of large data sets
Data set 10-50GB
Speed up hours → < 1 minute
Solution:
Standard graphic adapter
Universal programming (CUDA, OpenCL)
Teraflop performance
High bandwidth
Benefit:
Improve experiment quality
Experiment control
Tomographic reconstruction
3D Imaging applications produce large data sets. Several pictures from different angles or during manipulation are taken and the 3D object needs to be reconstructed from the image sequence. The size of the data sets is typically in the order of 10-50GB. Regular PCs need for this task several hours up to one day of computation time – this is too long for direct feed back (quality of the probe, control of the experiment). Even the transport of the data set takes too long too come to close real time results.
Utilizing standard graphics adapters can provide a solution. Actual graphic adapters provide a multiple of the computation power of actual desktop CPUs. The adapter is connect with high bandwidth (PCI Express). And all manufactures offer general purpose libraries that allow to use the graphics adapters also for non graphics purposes. In order to have a general programming interface with OpenCL a new standard for GPU, DSP and CPU systems is developed.
The first results for image processing applications show that quite large performance increase can be reached. It seems to be possible to come in the desired regions of realtime or near-realtime monitoring. Of course depending on the application and the resolution of the images.
Further planned applications are online-simulation for partical physics. Here simulations are more and more needed in parallel with the experiments. Examples: Fieldline simulations for KATRIN neutrino experiment or cosmic ray simulations. +
Graphic co-processors offer
multi teraflops in a single PC
KIT – The cooperation of Forschungszentrum Karlsruhe GmbH and Universität Karlsruhe (TH) 1 1

2. Application: Strain Measurement
Data Set:
Number of Images: (521)
Resolution: x3000
Total size: MB (10GB)
Results:
CPU reconstruction: ~10 hours (16 cores)
GPU reconstruction: min
Image corr / All
Unoptimized
Software Optimization
CUDA/FFT plugin
FULL CUDA support 9 45
Parallel Memory Transfers 6 42
Parallel Computations 6 25
Nvidia Tesla S

3. Application: X-ray Tomography
PyHST - High Speed Tomography Reconstruction
ESRF (European Synchrotron Radiation Facility)
Polygone Scientifique Louis Néel, 6 rue Jules Horowitz,
38000 GRENOBLE
Data Set:
Number of Images:
Resolution: x1707
Total size: GB
Results:
CPU reconstruction: ~10 hours (16 cores)
GPU reconstruction: min
Porose polyethylene grains
in a conical plastic holder
3 | Dr. Andreas Kopmann | PNI Bonus Programm