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统一冯诺依曼HPC与神经形态计算的EBRAINS工作流框架 - 透明跨平台执行SNN，支持异构架构无缝切换。
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| name | unifying-von-neumann-hpc-neuromorphic-ebbrains |
| description | 统一冯诺依曼HPC与神经形态计算的EBRAINS工作流框架 - 透明跨平台执行SNN，支持异构架构无缝切换。 |
| version | 1.0.0 |
| author | arXiv:2606.08515 (Krishna Kant Singh et al.) |
| date | 2026-06-13T00:00:00.000Z |
| arxiv_id | 2606.08515 |
| activation_keywords | ["neuromorphic computing","von neumann hpc","ebbrains","heterogeneous architecture","snn acceleration","workflow orchestration","brain-inspired computing","transparent execution"] |
arXiv:2606.08515 - Submitted 7 June 2026
Authors: Krishna Kant Singh, Charl Linssen, Eric Müller, Eleni Mathioulaki, Wouter Klijn, Lena Oden
Categories: cs.DC
提出EBRAINS研究基础设施上的统一框架，实现冯诺依曼HPC与神经形态加速器的无缝集成，支持单一科学工作流在异构架构间透明执行。
现代科学工作流日益跨越多样计算架构:
EBRAINS统一框架:
Workflow Definition
├── Task Graph (DAG)
│ ├── HPC Tasks (传统计算)
│ ├── Neuromorphic Tasks (SNN推理)
│ └── Hybrid Tasks (混合执行)
└── Resource Mapping
├── CPU/GPU Clusters (HPC)
├── SpiNNaker/BrainScaleS (神经形态)
└── Dynamic Allocation
# Conceptual workflow
workflow = EBRAINSWorkflow()
# Define SNN model (architecture-agnostic)
snn = SpikingModel(...)
# Transparent execution
workflow.run(
model=snn,
backend='auto', # Auto-select: HPC/neuromorphic
optimization='power', # 或 'speed', 'accuracy'
)