An Adaptive Block-Based Histogram Packing for Improving the Compression Performance of JPEG-LS for Images with Sparse and Locally Sparse Histograms

Jallouli, Souha; Zouari, Sonia; Nouri, Mohammad; Masmoudi, Afif

doi:10.1007/978-3-319-94211-7_8

Lecture Notes in Computer Science

2018

DOI: 10.1007/978-3-319-94211-7_8

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An Adaptive Block-Based Histogram Packing for Improving the Compression Performance of JPEG-LS for Images with Sparse and Locally Sparse Histograms

Souha Jallouli

Sonia Zouari

Mohammad Nouri

et al.

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2024

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Improved JPEG Lossless Compression for Compression of Intermediate Layers in Neural Networks Based on Compute-In-Memory

Hua,

Xu,

et al. 2024

Electronics

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With the development of Convolutional Neural Networks (CNNs), there is a growing requirement for their deployment on edge devices. At the same time, Compute-In-Memory (CIM) technology has gained significant attention in edge CNN applications due to its ability to minimize data movement between memory and computing units. However, the deployment of complex deep neural network models on edge devices with restricted hardware resources continues to be challenged by a lack of adequate storage for intermediate layer data. In this article, we propose an optimized JPEG Lossless Compression (JPEG-LS) algorithm that implements serial context parameter updating alongside parallel encoding. This method is designed for the global prediction and efficient compression of intermediate data layers in neural networks employing CIM techniques. The results indicate average compression ratios of 6.44× for VGG16, 3.62× for ResNet34, 1.67× for MobileNetV2, and 2.31× for InceptionV3. Moreover, the implementation achieves a data throughput of 32 bits per cycle at 600 MHz on the TSMC 28 nm, with a hardware cost of 122 K Gate Count.

show abstract

Improved JPEG Lossless Compression for Compression of Intermediate Layers in Neural Networks Based on Compute-In-Memory

Hua,

Xu,

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

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An Adaptive Block-Based Histogram Packing for Improving the Compression Performance of JPEG-LS for Images with Sparse and Locally Sparse Histograms

Cited by 1 publication

References 14 publications

Improved JPEG Lossless Compression for Compression of Intermediate Layers in Neural Networks Based on Compute-In-Memory

Improved JPEG Lossless Compression for Compression of Intermediate Layers in Neural Networks Based on Compute-In-Memory

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