Gast ::
| Hauptseite > Publikationsdatenbank > Interfacing Neuromorphic Hardware with Machine Learning Frameworks - A Review > print |
| Hauptseite > Publikationsdatenbank > Interfacing Neuromorphic Hardware with Machine Learning Frameworks - A Review > print |
| 001 | 1016966 | ||
| 005 | 20250203103223.0 | ||
| 024 | 7 | _ | |a 10.1145/3589737.3605967 |2 doi |
| 037 | _ | _ | |a FZJ-2023-03873 |
| 041 | _ | _ | |a English |
| 100 | 1 | _ | |a Lohoff, Jamie |0 P:(DE-Juel1)192147 |b 0 |
| 111 | 2 | _ | |a International Conference on Neuromorphic Systems |g ICONS |c Santa Fe |d 2023-08-03 - 2023-08-05 |w USA |
| 245 | _ | _ | |a Interfacing Neuromorphic Hardware with Machine Learning Frameworks - A Review |
| 260 | _ | _ | |c 2023 |b ACM New York, NY, USA |
| 336 | 7 | _ | |a conferenceObject |2 DRIVER |
| 336 | 7 | _ | |a Proceedings |b proc |m proc |0 PUB:(DE-HGF)26 |s 1710249458_19742 |2 PUB:(DE-HGF) |
| 336 | 7 | _ | |a Output Types/Book |2 DataCite |
| 336 | 7 | _ | |a BOOK |2 ORCID |
| 336 | 7 | _ | |a Conference Proceedings |0 3 |2 EndNote |
| 336 | 7 | _ | |a PROCEEDINGS |2 BibTeX |
| 520 | _ | _ | |a With the emergence of neuromorphic hardware as a promising low-power parallel computing platform, the need for tools that allowresearchers and engineers to efficiently interact with such hardwareis rapidly growing. Machine learning frameworks like Tensorflow,PyTorch and JAX have been instrumental for the success of machinelearning in recent years as they enable seamless interaction withtraditional machine learning accelerators such as GPUs and TPUs.In stark contrast, interfacing with neuromorphic hardware remainsdifficult since the aforementioned frameworks do not address thechallenges associated with mapping neural network models and al-gorithms to physical hardware. In this paper, we review the variousstrategies employed throughout the neuromorphic computing com-munity to tackle these challenges and categorize them according totheir methodologies and implementation effort. This classificationserves as a guideline for device engineers and software developersalike to enable them to choose the best-fit solution in regard of theirdemands and available resources. Finally, we provide a JAX-basedproof-of-concept implementation of a compilation pipeline tailoredto the needs of researchers in the early stages of device develop-ment, where parts of the computational graph can be mapped ontocustom hardware via operations exposed through a C++ or Pythoninterface. The code is available at https://github.com/PGI15/xbarax. |
| 536 | _ | _ | |a 5234 - Emerging NC Architectures (POF4-523) |0 G:(DE-HGF)POF4-5234 |c POF4-523 |f POF IV |x 0 |
| 536 | _ | _ | |a BMBF 16ME0398K - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0398K) |0 G:(DE-82)BMBF-16ME0398K |c BMBF-16ME0398K |x 1 |
| 536 | _ | _ | |a BMBF 16ME0399 - Verbundprojekt: Neuro-inspirierte Technologien der künstlichen Intelligenz für die Elektronik der Zukunft - NEUROTEC II - (BMBF-16ME0399) |0 G:(DE-82)BMBF-16ME0399 |c BMBF-16ME0399 |x 2 |
| 588 | _ | _ | |a Dataset connected to CrossRef Conference |
| 700 | 1 | _ | |a Yu, Zhenming |0 P:(DE-Juel1)190500 |b 1 |u fzj |
| 700 | 1 | _ | |a Finkbeiner, Jan Robert |0 P:(DE-Juel1)190112 |b 2 |
| 700 | 1 | _ | |a Kaya, Anil |0 P:(DE-Juel1)192456 |b 3 |
| 700 | 1 | _ | |a Stewart, Kenneth |0 P:(DE-Juel1)195754 |b 4 |
| 700 | 1 | _ | |a Wai Lui, Hin |0 0000-0002-7637-7168 |b 5 |
| 700 | 1 | _ | |a Neftci, Emre |0 P:(DE-Juel1)188273 |b 6 |
| 773 | _ | _ | |a 10.1145/3589737.3605967 |
| 909 | C | O | |o oai:juser.fz-juelich.de:1016966 |p VDB |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 0 |6 P:(DE-Juel1)192147 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 1 |6 P:(DE-Juel1)190500 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 2 |6 P:(DE-Juel1)190112 |
| 910 | 1 | _ | |a Forschungszentrum Jülich |0 I:(DE-588b)5008462-8 |k FZJ |b 6 |6 P:(DE-Juel1)188273 |
| 913 | 1 | _ | |a DE-HGF |b Key Technologies |l Natural, Artificial and Cognitive Information Processing |1 G:(DE-HGF)POF4-520 |0 G:(DE-HGF)POF4-523 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-500 |4 G:(DE-HGF)POF |v Neuromorphic Computing and Network Dynamics |9 G:(DE-HGF)POF4-5234 |x 0 |
| 914 | 1 | _ | |y 2024 |
| 920 | _ | _ | |l yes |
| 920 | 1 | _ | |0 I:(DE-Juel1)PGI-15-20210701 |k PGI-15 |l Neuromorphic Software Eco System |x 0 |
| 980 | _ | _ | |a proc |
| 980 | _ | _ | |a VDB |
| 980 | _ | _ | |a I:(DE-Juel1)PGI-15-20210701 |
| 980 | _ | _ | |a UNRESTRICTED |
| Library | Collection | CLSMajor | CLSMinor | Language | Author |
|---|