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SUMMARY:Accurate Reaction-Diffusion Operator Splitting on Tetrahedral Mesh
 es for Parallel Stochastic Molecular Simulations - Erik De Schutter (Okina
 wa Institute of Science and Technology)
DTSTART:20160622T104500Z
DTEND:20160622T113000Z
UID:TALK66544@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:<span>Co-authors: Hepburn\, Iain (OIST)\, Chen\, Weiliang  (OI
 ST) <br></span> <br>Spatial stochastic molecular simulations in biology ar
 e limited by the  intense computation required to track molecules in space
  either by particle  tracking or voxel-based methods\, meaning that the se
 rial limit has already been  reached in sub-cellular models. This calls fo
 r parallel simulations that can  take advantage of the power of modern sup
 ercomputers. GPU parallel  implementations have been described for particl
 e tracking methods [1\,2] and for  voxel-based methods [3]\, where good pa
 rallel performance gain up to 2 order of  magnitude have been demonstrated
  but this depends strongly on model specificity.  MPI parallel implementat
 ions have gained less attention than GPU implementations  to date but offe
 r several advantages including a greater range of platform  support from p
 ersonal computers to advanced supercomputer clusters. An initial  MPI impl
 ementation for irregular grids has been described and almost ideal  speedu
 p demonstrated but only up to 4 cores [4]\, which indicates the potential 
  for good scalability of such implementations. <br> <br>We describe an ope
 rator splitting implementation for irregular grids with a  novel method to
  improve accuracy over Lie-Trotter splitting that is somewhat  comparable 
 to tau-reduction but without the performance cost. We systematically  inve
 stigate parallel performance for a range of models and mesh partitionings 
  using the STEPS simulation platform [5]. Finally we introduce a whole cel
 l  parallel simulation of a published reaction-diffusion model [6] within 
 a  detailed\, complete neuron morphology and demonstrate a speedup of 3 or
 ders of  magnitude over serial computations.&nbsp\; <br> <br>[1] L Dematte
  2012. IEEE/ACM Trans. Comput. Biol. Bioinf. 9: 655-667 [2] DV  Gladkov et
  al. 2011. Proc. 19th High Perf. Comp. Symp. 151-158 [3]&nbsp\;E&nbsp\;Rob
 erts\, JE  Stone\, Z Luthey-Schulten 2013. J. Comp. Chem. 34: 245&ndash\;2
 55 [4] A Hellander et al.  2014. J. Comput. Phys. 266: 89-100 [5] I Hepbur
 n et al. 2012. BMC Syst. Biol.  6:36 [6]&nbsp\;H Anwar et al. 2013. J. Neu
 rosci. 33: 15848-15867 <br><br>Related Links <ul> <li><a target="_blank" r
 el="nofollow">http://steps.sourceforge.net/</a> -  Software site&nbsp\;</l
 i></ul>
LOCATION:Seminar Room 1\, Newton Institute
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