1. ALICE HLT tracking running on GPU
S. Gorbunov1 and I. Kisel1,2
( for the ALICE Collaboration )
1 Kirchhoff Institute for Physics, University of Heidelberg, Germany
2 Gesellschaft für Schwerionenforschung mbH, Darmstadt, Germany
ALICE/FAIR Workshop
GSI, February 3, 2009

2. TPC reconstruction scheme
TPC slice 0
TPC slice 35
The TPC Slice Tracker is the most
complicated algorithm:
combinatorial search
fit mathematics
the reconstruction time is crucial
Cluster finder
Cluster finder
clusters
clusters
Slice tracker
Slice tracker … … …
slice
tracks
slice
tracks
slice
tracks
TPC Global merger
TPC tracks
3 February 2009, GSI
Sergey Gorbunov, KIP

3. Tracking algorithm: the Cellular Automaton method
Neighbours
finder
2. Composing
of tracklets
For each TPC cluster
find two (up&down)
neighbours which
compose the best line
One-to-one linked
neighbours are grouped
to the track segments
3. Construction
of the track
candidates
4. Final selection
of tracks
Competition between
tracks, no shared clusters
allowed
Fit of trajectories
Search for the
missed parts
3 February 2009, GSI
Sergey Gorbunov, KIP

4. Use of parallel hardware: GPU
NVIDIA GeForce GTX 280:
30x8 general propose processors;
pure calculations can be ~100 times
faster than CPU
very parallel: || execution of branches, || memory access
CUDA language - a little extension of the C++
fast access to the small portion of data (16k) at the time; no memory cache
single precision floating point
ONLY parallel calculations
3 February 2009, GSI
Sergey Gorbunov, KIP

5. Porting HLT tracking code to the GPU
The algorithm evolution:
Maximal parallelisation of the CPU tracker. ( AliRoot )
Stand-alone CPU tracker w/o ROOT ( AliRoot->stand-alone )
Developing of the efficient GPU code ( stand-alone CPU-> stand-alone GPU )
Making hybrid code ( stand-alone GPU -> stand-alone GPU+CPU )
Porting code back to AliRoot (stand-alone GPU+CPU -> AliRoot )
Result - HLT TPC tracker:
Official svn code, compiles and runs offline and in the HLT framework
Satisfies to the ALICE coding rules (almost)
Can use the GPU device (not from AliRoot)
SAME source code for GPU and CPU, same result.
For a moment >10.5 times faster on GPU
Pb-Pb event
in work
1640 ms
156 ms
3 February 2009, GSI
Sergey Gorbunov, KIP

6. Running the ALICE HLT tracker on the GPU cluster at Frankfurt
speed-up: 10.5x
GPU
CPU
same code
same result
CPU
GPU
3 February 2009, GSI
Sergey Gorbunov, KIP

7. Summary and plans Summary:
The ALICE HLT tracking algorithm has been parallelised to use the GPU hardware.
The new tracker is as fast as before on CPU, and shows 10x speed-up on GPU.
The algorithm and the code are universal for GPU and CPU.
Commit to svn, running in the HLT
Plans:
Further speed-up for the GPU
Integration of the GPU tracker to the HLT framework.
3 February 2009, GSI
Sergey Gorbunov, KIP