% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@INPROCEEDINGS{Villamar:908613,
author = {Villamar, Jose and Gianmarco, Tiddia and Linssen, Charl and
Babu, Pooja and Pastorelli, Elena and Paolucci, Pier
Stanislao and Morrison, Abigail and Diesmann, Markus and
Golosio, Bruno and Senk, Johanna},
title = {{NEST} is on the road to {GPU} integration},
reportid = {FZJ-2022-02722},
year = {2022},
abstract = {Most of the Top500 computer systems and all of the upcoming
exascale machines employ GPUs alongside CPUs. To get the
most performance out of these architectures, simulation
software requires efficient support for both processor
types. Decades of simulator development enable the routine
simulation of large-scale neuronal network models on
thousands of many-core CPUs in parallel [1]; recent GPU
implementations show highly competitive results [2, 3].
Here, we present our project to integrate NEST GPU (formerly
NeuronGPU [3]) into the ecosystem of the CPU-based simulator
NEST [4]. NEST GPU, written in CUDA-C++, lends itself to
this integration due to a similar interface and a modular
structure. The development will continue within the NEST
Initiative under the same GitHub organization [5], although
the codes themselves are still separate. We pursue the
unified, community-centered workflow already pioneered by
NEST: build processes, model development (NESTML [6]),
documentation standards along with quality assurance through
continuous integration. We are looking forward to a fruitful
exchange between NEST and NEST GPU, enabling the
optimization of simulator performance under the hood while
providing a common frontend for users to seamlessly harness
both CPUs and GPUs in the future.},
month = {Jun},
date = {2022-06-23},
organization = {NEST Conference 2022, Online
(Germany), 23 Jun 2022 - 24 Jun 2022},
subtyp = {After Call},
cin = {INM-6 / INM-10 / IAS-6 / JSC},
cid = {I:(DE-Juel1)INM-6-20090406 / I:(DE-Juel1)INM-10-20170113 /
I:(DE-Juel1)IAS-6-20130828 / I:(DE-Juel1)JSC-20090406},
pnm = {5235 - Digitization of Neuroscience and User-Community
Building (POF4-523) / 5111 - Domain-Specific Simulation $\&$
Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) /
PhD no Grant - Doktorand ohne besondere Förderung
(PHD-NO-GRANT-20170405) / HBP SGA3 - Human Brain Project
Specific Grant Agreement 3 (945539) / MetaMoSim - Generic
metadata management for reproducible
high-performance-computing simulation workflows - MetaMoSim
(ZT-I-PF-3-026) / JL SMHB - Joint Lab Supercomputing and
Modeling for the Human Brain (JL SMHB-2021-2027) /
BMBF-03ZU1106CB - NeuroSys: Algorithm-Hardware Co-Design
(Projekt C) - B (BMBF-03ZU1106CB) / ACA - Advanced Computing
Architectures (SO-092) / Brain-Scale Simulations
$(jinb33_20191101)$ / Brain-Scale Simulations
$(jinb33_20220812)$},
pid = {G:(DE-HGF)POF4-5235 / G:(DE-HGF)POF4-5111 /
G:(DE-Juel1)PHD-NO-GRANT-20170405 / G:(EU-Grant)945539 /
G:(DE-Juel-1)ZT-I-PF-3-026 / G:(DE-Juel1)JL SMHB-2021-2027 /
G:(DE-Juel1)BMBF-03ZU1106CB / G:(DE-HGF)SO-092 /
$G:(DE-Juel1)jinb33_20191101$ /
$G:(DE-Juel1)jinb33_20220812$},
typ = {PUB:(DE-HGF)24},
url = {https://juser.fz-juelich.de/record/908613},
}