Bio-inspired massively parallel architectures for nanotechnologies
| Autor: | Jäger, Björn, Porrmann, Mario, Rückert, Ulrich, ARRAY(0xab4b8f8) |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2006 |
| Předmět: |
Multi-core processor
Hardware_MEMORYSTRUCTURES Artificial neural network nanotechnology Computer science Distributed computing Parallel algorithm biological systems parallel algorithms parallel architectures Energy consumption ComputerSystemsOrganization_PROCESSORARCHITECTURES processor cores neural networks bio-inspired massively parallel architectures GigaNetIC architecture multiprocessing systems Computer architecture massively parallel single-chip multiprocessors energy consumption circuit technologies Algorithm design nanotechnologies Massively parallel overall performance |
| Zdroj: | ISCAS |
| Popis: | Massively parallel single-chip multiprocessors (CMP) share a number of traits with biological systems such as neural networks. These biological systems have therefore inspired a number of concepts that may help to overcome some of the problems that will come up in future circuit technologies. In this work we present a first comparison of CMPs based on processor cores of different complexity and estimate the efficiency of CMPs with regards to overall performance and energy consumption. The analysis is based on an analytical model of chip multiprocessing that can help to estimate the runtime and energy consumption of different parallel algorithms. As in previous work we will use the GigaNetIC architecture as a basis for the different CMP architectures. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|