Name
Title | ||
|---|---|---|
NeuroXplorer 1.0 - An Extensible Framework for Architectural Exploration with Spiking Neural Networks. |
Abstract | ||
|---|---|---|
Recently, both industry and academia have proposed many different neuromorphic architectures to execute applications that are designed with Spiking Neural Network (SNN). Consequently, there is a growing need for an extensible simulation framework that can perform architectural explorations with SNNs, including both platform-based design of today's hardware, and hardware-software co-design and design-technology co-optimization of the future. We present NeuroXplorer, a fast and extensible framework that is based on a generalized template for modeling a neuromorphic architecture that can be infused with the specific details of a given hardware and/or technology. NeuroXplorer can perform both low-level cycle-accurate architectural simulations and high-level analysis with data-flow abstractions. NeuroXplorer's optimization engine can incorporate hardware-oriented metrics such as energy, throughput, and latency, as well as SNN-oriented metrics such as inter-spike interval distortion and spike disorder, which directly impact SNN performance. We demonstrate the architectural exploration capabilities of NeuroXplorer through case studies with many state-of-the-art machine learning models. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3477145.3477156 | ICONS |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adarsha Balaji | 1 | 15 | 4.27 |
| Shihao Song | 2 | 1 | 2.03 |
| Twisha Titirsha | 3 | 0 | 1.35 |
| Anup Das 0001 | 4 | 367 | 33.35 |
| Jeffrey Krichmar | 5 | 0 | 0.34 |
| Nikil Dutt | 6 | 4960 | 421.49 |
| James A. Shackleford | 7 | 0 | 1.69 |
| Nagarajan Kandasamy | 8 | 615 | 54.83 |
| Francky Catthoor | 9 | 2 | 1.75 |