enyac-group / NeuralPowerLinks
The code for paper: Neuralpower: Predict and deploy energy-efficient convolutional neural networks
☆21Updated 6 years ago
Alternatives and similar repositories for NeuralPower
Users that are interested in NeuralPower are comparing it to the libraries listed below
Sorting:
- Simulator for BitFusion☆102Updated 5 years ago
- Official implementation of "Searching for Winograd-aware Quantized Networks" (MLSys'20)☆27Updated 2 years ago
- BSQ: Exploring Bit-Level Sparsity for Mixed-Precision Neural Network Quantization (ICLR 2021)☆42Updated 4 years ago
- ☆36Updated 6 years ago
- ☆71Updated 5 years ago
- Static Block Floating Point Quantization for CNN☆37Updated 4 years ago
- Linux docker for the DNN accelerator exploration infrastructure composed of Accelergy and Timeloop☆59Updated last month
- Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation☆27Updated 6 years ago
- [ICASSP'20] DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architecture…☆25Updated 3 years ago
- Implementation of "NITI: Training Integer Neural Networks Using Integer-only Arithmetic" on arxiv☆86Updated 3 years ago
- DAC System Design Contest 2020☆29Updated 5 years ago
- ☆35Updated 5 years ago
- Tool for optimize CNN blocking☆93Updated 5 years ago
- HW/SW co-design of sentence-level energy optimizations for latency-aware multi-task NLP inference☆52Updated last year
- This is the implementation for paper: AdaTune: Adaptive Tensor Program CompilationMade Efficient (NeurIPS 2020).☆14Updated 4 years ago
- ☆14Updated 4 years ago
- ☆32Updated 4 years ago
- MICRO22 artifact evaluation for Sparseloop☆44Updated 3 years ago
- [ICML 2021] "Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators" by Yonggan Fu, Yonga…☆15Updated 3 years ago
- pytorch fixed point training tool/framework☆34Updated 5 years ago
- Approximate layers - TensorFlow extension☆26Updated 7 months ago
- Ares: A framework for quantifying the resilience of deep neural networks☆38Updated 5 years ago
- Benchmark for matrix multiplications between dense and block sparse (BSR) matrix in TVM, blocksparse (Gray et al.) and cuSparse.☆23Updated 5 years ago
- DNN quantization with outlier channel splitting (ICML'19)☆113Updated 5 years ago
- Training with Block Minifloat number representation☆17Updated 4 years ago
- ☆42Updated last year
- A collection of research papers on efficient training of DNNs☆70Updated 3 years ago
- agile hardware-software co-design☆52Updated 3 years ago
- Post-training sparsity-aware quantization☆34Updated 2 years ago
- ☆19Updated 4 years ago