rachmad's repositories
netadapt
This repo contains the official Pytorch reimplementation of the paper "NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Applications".
torchneuromorphic
Datasets recorded from Neuromorphic Sensors or Conversions using Simulations of Sensors
stonne
STONNE: A Simulation Tool for Neural Networks Engines
SpykeTorch
High-speed simulator of convolutional spiking neural networks with at most one spike per neuron.
SNN_BPengendersSTDP
What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.
snntoolbox_applications
Collection of Spiking Neural Network applications for SNN Toolbox.
snn_toolbox
Toolbox for converting analog to spiking neural networks (ANN to SNN), and running them in a spiking neuron simulator.
slayerPytorch
PyTorch implementation of SLAYER for training Spiking Neural Networks
ramulator-pim
A fast and flexible simulation infrastructure for exploring general-purpose processing-in-memory (PIM) architectures. Ramulator-PIM combines a widely-used simulator for out-of-order and in-order processors (ZSim) with Ramulator, a DRAM simulator with memory models for DDRx, LPDDRx, GDDRx, WIOx, HBMx, and HMCx. Ramulator is described in the IEEE CAL 2015 paper by Kim et al. at https://people.inf.ethz.ch/omutlu/pub/ramulator_dram_simulator-ieee-cal15.pdf Ramulator-PIM is used in the DAC 2019 paper by Singh et al. at https://people.inf.ethz.ch/omutlu/pub/NAPEL-near-memory-computing-performance-prediction-via-ML_dac19.pdf
ramulator
A Fast and Extensible DRAM Simulator, with built-in support for modeling many different DRAM technologies including DDRx, LPDDRx, GDDRx, WIOx, HBMx, and various academic proposals. Described in the IEEE CAL 2015 paper by Kim et al. at http://users.ece.cmu.edu/~omutlu/pub/ramulator_dram_simulator-ieee-cal15.pdf
PiDRAM
PiDRAM is the first flexible end-to-end framework that enables system integration studies and evaluation of real Processing-using-Memory techniques. Prototype on a RISC-V rocket chip system implemented on an FPGA. Described in our preprint: https://arxiv.org/abs/2111.00082
ParametricLIF
Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks
ParallelSpikeSim
GPU accelerated spiking neural network simulator
overcoming-catastrophic
Implementation of "Overcoming catastrophic forgetting in neural networks" in Tensorflow
hybrid-snn-conversion
Training spiking networks with hybrid ann-snn conversion and spike-based backpropagation
gem5
This is an read-only mirror of the gem5 simulator. The upstream repository is stored in https://gem5.googlesource.com, code reviews should be submitted to https://gem5-review.googlesource.com/. The mirrors are synchronized every 15 minutes.
evoapproxlib
Library of approximate arithmetic circuits
DRAMSpec
A High-Level DRAM Timing, Power and Area Exploration Tool
ANN_continual_learning
PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, GR, GR+distill, RtF, ER, A-GEM, iCaRL).
CNNergy
An Analytical CNN Energy Model
brain-inspired-replay
A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).
STBPforSNN
Spatio-temporal BackPropagation (STBP) for SNNs