Intelligent-Computing-Lab-Panda / SATALinks
An energy simulation framework for BPTT-based SNN inference and training.
☆17Updated 2 years ago
Alternatives and similar repositories for SATA
Users that are interested in SATA are comparing it to the libraries listed below
Sorting:
- SATA_Sim is an energy estimation framework for Backpropagation-Through-Time (BPTT) based Spiking Neural Networks (SNNs) training and infe…☆28Updated last year
- ☆43Updated 2 years ago
- I will share some useful or interesting papers about neuromorphic processor☆28Updated last year
- Framework for radix encoded SNN on FPGA☆18Updated 4 years ago
- LoAS: Fully Temporal-Parallel Dataflow for Dual-Sparse Spiking Neural Networks, MICRO 2024.☆17Updated 10 months ago
- MINT, Multiplier-less INTeger Quantization for Energy Efficient Spiking Neural Networks, ASP-DAC 2024, Nominated for Best Paper Award☆16Updated last year
- Code for the ISCAS23 paper "The Hardware Impact of Quantization and Pruning for Weights in Spiking Neural Networks"☆11Updated 2 years ago
- The official implementation of HPCA 2025 paper, Prosperity: Accelerating Spiking Neural Networks via Product Sparsity☆37Updated 5 months ago
- ReckOn: A Spiking RNN Processor Enabling On-Chip Learning over Second-Long Timescales - HDL source code and documentation.☆92Updated 3 years ago
- [NeurIPS 2024] Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation☆19Updated last year
- Pytorch implementation of SEENN (Spiking Early Exit Neural Networks) (NeurIPS 2023)☆19Updated last year
- Modeling of memristors in LTSpise environment☆38Updated last month
- NeuroSync: A Scalable and Accurate Brain Simulation System using Safe and Efficient Speculation (HPCA 2022)☆13Updated 3 years ago
- Benchmark framework of compute-in-memory based accelerators for deep neural network (on-chip training chip focused)☆53Updated 4 years ago
- SNN on FPGA☆11Updated 3 years ago
- ☆20Updated 4 years ago
- Quantization-aware training with spiking neural networks☆51Updated 3 years ago
- Energy-efficient Event-driven Spiking Neural Network accelerator for FPGA with PyTorch integration☆106Updated 2 weeks ago
- [FPL 2021] SyncNN: Evaluating and Accelerating Spiking Neural Networks on FPGAs.☆64Updated 4 years ago
- STBP is a way to train SNN with datasets by Backward propagation.Using this Repositories allows you to train SNNS with STBP and quantize …☆29Updated 4 years ago
- ReRAM implementation on CNN☆18Updated 7 years ago
- FPGA acceleration of a Spike-Timing-Dependent Plasticity learning algorithm for Spiking Neural Networks☆40Updated 5 years ago
- CORDIC-SNN, followed with "Unsupervised learning of digital recognition using STDP" published in 2015, frontiers☆25Updated 5 years ago
- Benchmark framework of synaptic device technologies for a simple neural network☆226Updated 4 years ago
- This repository contains the models and training scripts used in the papers: "Quantizing Spiking Neural Networks with Integers" (ICONS 20…☆13Updated 5 years ago
- ☆18Updated last year
- ☆11Updated 6 years ago
- SSTDP is a efficient spiking neural network training framework, which is contributed by Fangxin Liu and Wenbo Zhao.☆37Updated 4 years ago
- Spiking Neural Network RTL Implementation☆64Updated 4 years ago
- CS4362 - Hardware Description Languages. Implemented SNN on an FPGA for real-time image processing using VHDL☆23Updated 2 years ago