DLPlib: A Library for Deep Learning Processor
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Summary
DLPlib is proposed, a tensor-filter based library designed specific for deep learning processors which contains two major data structures, tensor and filter, and a set of operators including basic neural network primitives and matrix/vector operations.
- Type
- article
- Published
- 2017-03-13
- Cited by
- 5
- References
- 22
- OpenAlex
- https://openalex.org/W2593773834
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:32488813
Keywords
Computer science, Deep learning, Generality, Artificial intelligence, Programming paradigm
References
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- cuDNN: Efficient Primitives for Deep Learning
- Very Deep Convolutional Networks for Large-Scale Image Recognition
- CNP: An FPGA-based processor for Convolutional Networks
- A dynamically configurable coprocessor for convolutional neural networks
- DaDianNao: A Machine-Learning Supercomputer
- Optimizing FPGA-based Accelerator Design for Deep Convolutional Neural Networks
- Going deeper with convolutions
- Gradient-based learning applied to document recognition
- DeepID3: Face Recognition with Very Deep Neural Networks
- DianNao: a small-footprint high-throughput accelerator for ubiquitous machine-learning
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition
- Cambricon: An Instruction Set Architecture for Neural Networks
- ISAAC: A Convolutional Neural Network Accelerator with In-Situ Analog Arithmetic in Crossbars
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
- Tree-to-Sequence Attentional Neural Machine Translation
- Cambricon-X: An accelerator for sparse neural networks
- ShiDianNao
- Cambricon: An Instruction Set Architecture for Neural Networks
Cited by
- Various Frameworks and Libraries of Machine Learning and Deep Learning: A Survey
- Research on the Big Data Intelligent Application
- FlexPDA: A Flexible Programming Framework for Deep Learning Accelerators
- Tetris: A Heuristic Static Memory Management Framework for Uniform Memory Multicore Neural Network Accelerators
- ZhuQue: A Neural Network Programming Model Based on Labeled Data Layout
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