Contributions to NEST-C are welcomed and encouraged! We are proud to collaborate with the following companies on our open-source project:
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We appreciate their support and contributions to our project. Click on the logos to learn more about each partner and their involvement with our project.
The NEST Compiler (NEST-C) is an open source project led by ETRI, which is based on [GLOW project] (https://github.com/pytorch/glow).
Glow is a machine learning compiler and execution engine for hardware accelerators. It is designed to be used as a backend for high-level machine learning frameworks. The compiler is designed to allow state of the art compiler optimizations and code generation of neural network graphs.
The objective of NEST-C is to generate optimized code for various kinds of Neural-network Processing Uints (NPUs). Therefore, NEST-C provides automatic tuning functionalities and tools for each optimization step.
Optimization modules and tools of NEST-Compiler
- NPU HW backend supporting EVTA series
- Automatic backend parameter tuning (under development)
- Profile-based dyanamic quantization for supporting various NPU backends
- C/C++ code generation for embedded HWs supporting gcc/llvm compilers
- Profile-based graph partitioning
- Installation
- Docker Setting
- Testing and Running
- EVTA
- Quantization
- Profile-based Graph Partitioning
- C/C++ code generator
- PartitionTuner: An operator scheduler for deep-learning compilers supporting multiple heterogeneous processing units
- ETRI Journal Vol. 45 No. 2 (JCR21 IF: 1.622) ISSN: 1225-6463, doi: https://doi.org/10.4218/etrij.2021-0446, Apr 2023.
- Quantune: Post-training quantization of convolutional neural networks using extreme gradient boosting for fast deployment
- Future Generation Computer Systems Vol. 132, 2022, pp. 124-135, July 01, 2022 (JCR21 IF: 7.307, Top 9.09%), Jul 2022
- 범용 AI 컴파일러의 비공개 NPU 코드생성을 위한 공통 인터페이스 설계 및 검증
- 전자공학회논문지, v.60 no.10, pp.29-31, 2023.10.25, 우수등재지
NEST-C is licensed under the Apache 2.0 License.