jack-willturner / nas-as-program-transformation-explorationView external linksLinks
The code for our paper "Neural Architecture Search as Program Transformation Exploration"
☆16Apr 28, 2021Updated 4 years ago
Alternatives and similar repositories for nas-as-program-transformation-exploration
Users that are interested in nas-as-program-transformation-exploration are comparing it to the libraries listed below
Sorting:
- This is the implementation for paper: AdaTune: Adaptive Tensor Program CompilationMade Efficient (NeurIPS 2020).☆14May 16, 2021Updated 4 years ago
- A reference implementation of the Mind Mappings Framework.☆30Dec 2, 2021Updated 4 years ago
- ☆22Feb 18, 2025Updated 11 months ago
- This is the pytorch implementation for the paper: Generalizable Mixed-Precision Quantization via Attribution Rank Preservation, which is…☆24Aug 17, 2021Updated 4 years ago
- [MLSys 2021] IOS: Inter-Operator Scheduler for CNN Acceleration☆199Apr 27, 2022Updated 3 years ago
- ☆11Feb 24, 2025Updated 11 months ago
- Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation☆27Nov 7, 2019Updated 6 years ago
- System for automated integration of deep learning backends.☆47Aug 15, 2022Updated 3 years ago
- The official implementation of "NAS-BNN: Neural Architecture Search for Binary Neural Networks"☆13Aug 30, 2024Updated last year
- Dual-way gradient sparsification approach for async DNN training, based on PyTorch.☆11Dec 8, 2022Updated 3 years ago
- Code for Depth-wise Separable Convolutions: Performance Investigations☆19Jan 28, 2020Updated 6 years ago
- ☆32Mar 31, 2025Updated 10 months ago
- BitSplit Post-trining Quantization☆50Dec 20, 2021Updated 4 years ago
- [ICML 2022] ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks☆15May 18, 2022Updated 3 years ago
- ☆95Nov 4, 2022Updated 3 years ago
- An external memory allocator example for PyTorch.☆16Aug 10, 2025Updated 6 months ago
- [ICML 2021] "Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators" by Yonggan Fu, Yonga…☆16Jan 3, 2022Updated 4 years ago
- Improving Post Training Neural Quantization: Layer-wise Calibration and Integer Programming☆35Jun 29, 2023Updated 2 years ago
- ☆14May 19, 2023Updated 2 years ago
- source code of the paper: Robust Quantization: One Model to Rule Them All☆41Mar 24, 2023Updated 2 years ago
- [ECCV 2022] SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning☆20Jul 7, 2022Updated 3 years ago
- Benchmark scripts for TVM☆74Mar 15, 2022Updated 3 years ago
- dMazeRunner: Dataflow acceleration optimization infrastructure for coarse-grained programmable accelerators☆47Apr 4, 2022Updated 3 years ago
- Paper List for In-context Learning 🌷☆20Jan 3, 2023Updated 3 years ago
- SparseTIR: Sparse Tensor Compiler for Deep Learning☆142Mar 31, 2023Updated 2 years ago
- An experimental ahead of time compiler for Relay.☆49Apr 21, 2020Updated 5 years ago
- Domain-Specific Architecture Generator 2☆22Oct 2, 2022Updated 3 years ago
- [CVPR 2020] APQ: Joint Search for Network Architecture, Pruning and Quantization Policy☆159Jun 16, 2020Updated 5 years ago
- DAC System Design Contest 2020☆29Jun 11, 2020Updated 5 years ago
- [ICLR 2024] This is the official PyTorch implementation of "QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Mod…☆31Mar 12, 2024Updated last year
- FracBNN: Accurate and FPGA-Efficient Binary Neural Networks with Fractional Activations☆97Oct 2, 2021Updated 4 years ago
- Official PyTorch Implementation of HELP: Hardware-adaptive Efficient Latency Prediction for NAS via Meta-Learning (NeurIPS 2021 Spotlight…☆64Aug 5, 2024Updated last year
- [ICLR 2021] "Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective" by Wuyang Chen, Xinyu Gong, …☆169Dec 30, 2021Updated 4 years ago
- Automatic Mapping Generation, Verification, and Exploration for ISA-based Spatial Accelerators☆121Oct 26, 2022Updated 3 years ago
- Code for our paper at ECCV 2020: Post-Training Piecewise Linear Quantization for Deep Neural Networks☆68Nov 4, 2021Updated 4 years ago
- [ICLR 2021 Spotlight] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yinin…☆31Mar 2, 2024Updated last year
- Benchmark for matrix multiplications between dense and block sparse (BSR) matrix in TVM, blocksparse (Gray et al.) and cuSparse.☆23Aug 21, 2020Updated 5 years ago
- DietCode Code Release☆65Jul 21, 2022Updated 3 years ago
- ☆71Mar 22, 2020Updated 5 years ago