| Age | Commit message (Collapse) | Author |
|---|
|
to speed up likelihood evaluation.
When generating a likelihood, the DAQ can be run many times in parallel
by the GPU, creating a large block of channel hit information in memory.
The PDF accumulator processes that entire block in two passes:
* First update the channel hit count, and the count of channel hits
falling into the bin around the channel hit time being evaluated.
Add any channel hits that should also be included in the n-th
nearest neighbor calculation to a channel-specific work queue.
* Process all the work queues for each channel and update the
list of nearest neighbors.
This is hugely faster than what we were doing before. Kernel
estimation (or some kind of orthogonal function expansion of the PDF)
should be better ultimately, but for now the nearest neighbor approach
to PDF estimation seems to be working the best.
|
|
still look off, but this is an improvement.
|
|
|
|
geometry, like the mapping from solid IDs to channels, and the time
and charge distributions.
Detector is a subclass of Geometry, so that a Detector can be used
wherever a Geometry is used. Only code (like the DAQ stuff) that
needs to know how PMT solids map to channels should look for a
Detector object.
There is a corresponding GPUDetector class as well, with its own
device side struct to hold PMT channel information.
The GPU code now can sample an arbitrary time and charge PDF, but
on the host side, the only interface exposed right now creates
a Gaussian distribution.
|
|
A little rough around the edges, and still needs some development work.
|
|
|
