001010228 001__ 1010228
001010228 005__ 20231128201903.0
001010228 0247_ $$2doi$$a10.5281/ZENODO.8233847
001010228 037__ $$aFZJ-2023-03030
001010228 1001_ $$0P:(DE-HGF)0$$aAkar, Nora Abi$$b0
001010228 245__ $$aArbor Library (v0.9.0)
001010228 250__ $$a0.9.0
001010228 260__ $$c2023
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001010228 520__ $$aAfter much more delay than anticipated, we are very happy to present a new Arbor release. Nearly 8 months of work is in it, much of which focussed on speed, optimisation, fixes and build system changes. This release includes Python 3.12 wheels as probably one of the first packages on PyPI.Major new features:(1) External Connectivity: Arbor can now interface with other simulators or processes through MPI. Contexts now accept a second MPI communicator and Recipes can implement a  external_connections_on  method to specify how simulations might be interacting.  See documentation for more. (2) Arbor now supports checkpointing and resume from a previously stored checkpoint. Useful when a certain point in time needs to be explored in multiple directions, when you want to rewind to a previous state, etc.  See documentation for more.(3) More painted parameters are now scalable through  iexpr : temperature, capacitance, resistivity, membrane potential and the following ionic parameters: internal and external concentration, diffusivity, and reversal potential.  See documentation.(4) A set of ANN activation functions for NMODL have been added:  sigmoid(x) ,  relu(x)  and  tanh(x) . Control volume  area  is exposed through NMODL.(5) A revamped backend for ARM CPU's that support Scalable Vector Extension (SVE). Arbor and modcc are now fully compatible, so users who have access to A64FX-based HPC can take full advantage of that hardware.
001010228 536__ $$0G:(DE-HGF)POF4-5111$$a5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)$$cPOF4-511$$fPOF IV$$x0
001010228 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x1
001010228 536__ $$0G:(DE-Juel1)Helmholtz-SLNS$$aSLNS - SimLab Neuroscience (Helmholtz-SLNS)$$cHelmholtz-SLNS$$x2
001010228 588__ $$aDataset connected to DataCite
001010228 650_7 $$2Other$$aneuroscience
001010228 650_7 $$2Other$$acomputational neuroscience
001010228 650_7 $$2Other$$amorpholically detailed simulator
001010228 7001_ $$0P:(DE-HGF)0$$aBiddiscombe, John$$b1
001010228 7001_ $$0P:(DE-HGF)0$$aCumming, Benjamin$$b2
001010228 7001_ $$0P:(DE-HGF)0$$aKabic, Marko$$b3
001010228 7001_ $$0P:(DE-HGF)0$$aKarakasis, Vasileios$$b4
001010228 7001_ $$0P:(DE-Juel1)168169$$aKlijn, Wouter$$b5$$ufzj
001010228 7001_ $$0P:(DE-Juel1)166193$$aKüsters, Anne$$b6
001010228 7001_ $$0P:(DE-Juel1)161525$$aPeyser, Alexander$$b7
001010228 7001_ $$0P:(DE-HGF)0$$aYates, Stuart$$b8
001010228 7001_ $$0P:(DE-Juel1)176815$$aHater, Thorsten$$b9$$ufzj
001010228 7001_ $$0P:(DE-Juel1)175163$$aHuisman, Brent$$b10$$eCorresponding author
001010228 7001_ $$0P:(DE-Juel1)164166$$aHagen, Espen$$b11
001010228 7001_ $$0P:(DE-HGF)0$$aSchepper, Robin De$$b12
001010228 7001_ $$0P:(DE-Juel1)176305$$aLinssen, Charl$$b13$$ufzj
001010228 7001_ $$0P:(DE-HGF)0$$aStoppels, Harmen$$b14
001010228 7001_ $$0P:(DE-Juel1)161557$$aSchmitt, Sebastian$$b15
001010228 7001_ $$0P:(DE-Juel1)176143$$aHuber, Felix$$b16
001010228 7001_ $$0P:(DE-Juel1)188863$$aEngelen, Max$$b17
001010228 7001_ $$0P:(DE-HGF)0$$aBösch, Fabian$$b18
001010228 7001_ $$0P:(DE-HGF)0$$aLuboeinski, Jannik$$b19
001010228 7001_ $$0P:(DE-HGF)0$$aFrasch, Simon$$b20
001010228 7001_ $$0P:(DE-HGF)0$$aDrescher, Lukas$$b21
001010228 7001_ $$0P:(DE-Juel1)184553$$aLandsmeer, Lennart$$b22
001010228 773__ $$a10.5281/ZENODO.8233847
001010228 8564_ $$uhttps://zenodo.org/record/8233847
001010228 8564_ $$uhttps://juser.fz-juelich.de/record/1010228/files/arbor-v0.9.0-full.tar.gz$$yRestricted
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001010228 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)168169$$aForschungszentrum Jülich$$b5$$kFZJ
001010228 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)166193$$aForschungszentrum Jülich$$b6$$kFZJ
001010228 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)161525$$aForschungszentrum Jülich$$b7$$kFZJ
001010228 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)176815$$aForschungszentrum Jülich$$b9$$kFZJ
001010228 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)175163$$aForschungszentrum Jülich$$b10$$kFZJ
001010228 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)176305$$aForschungszentrum Jülich$$b13$$kFZJ
001010228 9131_ $$0G:(DE-HGF)POF4-511$$1G:(DE-HGF)POF4-510$$2G:(DE-HGF)POF4-500$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$9G:(DE-HGF)POF4-5111$$aDE-HGF$$bKey Technologies$$lEngineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action$$vEnabling Computational- & Data-Intensive Science and Engineering$$x0
001010228 9141_ $$y2023
001010228 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
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001010228 980__ $$aUNRESTRICTED