% 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}, }