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Configurable Multi-directional Systolic Array Architecture for Convolutional Neural Networks
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Maestro: A Memory-on-Logic Architecture for Coordinated Parallel Use of Many Systolic Arrays
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ImageNet: A large-scale hierarchical image database
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Deep Residual Learning for Image Recognition
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Xception: Deep Learning with Depthwise Separable Convolutions
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FlexFlow: A Flexible Dataflow Accelerator Architecture for Convolutional Neural Networks
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SIGMA: A Sparse and Irregular GEMM Accelerator with Flexible Interconnects for DNN Training
inferredcites →https://doi.org/10.1109/iscas45731.2020.9180403openalex-snapshot
A Systolic Dataflow Based Accelerator for CNNs
inferredcites →https://doi.org/10.1109/ispass48437.2020.00016openalex-snapshot
A Systematic Methodology for Characterizing Scalability of DNN Accelerators using SCALE-Sim
inferredcites →https://doi.org/10.1109/isvlsi49217.2020.00088openalex-snapshot
DRACO: Co-Optimizing Hardware Utilization, and Performance of DNNs on Systolic Accelerator
inferredcites →https://doi.org/10.1109/jetcas.2019.2910232openalex-snapshot
Eyeriss v2: A Flexible Accelerator for Emerging Deep Neural Networks on Mobile Devices
inferredcites →https://doi.org/10.1109/jssc.2016.2616357openalex-snapshot
Eyeriss: An Energy-Efficient Reconfigurable Accelerator for Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/lca.2019.2924007openalex-snapshot
SMT-SA: Simultaneous Multithreading in Systolic Arrays
inferredcites →https://doi.org/10.1109/lca.2020.2979965openalex-snapshot
Systolic Tensor Array: An Efficient Structured-Sparse GEMM Accelerator for Mobile CNN Inference
inferredcites →https://doi.org/10.1109/mwscas.2012.6292202openalex-snapshot
NeuFlow: Dataflow vision processing system-on-a-chip
inferredcites →https://doi.org/10.1145/3061639.3062207openalex-snapshot
Automated Systolic Array Architecture Synthesis for High Throughput CNN Inference on FPGAs
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
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In-Datacenter Performance Analysis of a Tensor Processing Unit
inferredcites →https://doi.org/10.1145/3297858.3304028openalex-snapshot
Packing Sparse Convolutional Neural Networks for Efficient Systolic Array Implementations
inferredcites →https://doi.org/10.1145/3307650.3322255openalex-snapshot
Laconic deep learning inference acceleration
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Understanding Reuse, Performance, and Hardware Cost of DNN Dataflow
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EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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A Survey of Design and Optimization for Systolic Array-based DNN Accelerators
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