Výsledky vyhledávání - "Information systems Data management systems Data structures Data layout"

The SIMON and SPECK lightweight block ciphers Autor Beaulieu, Ray, Treatman-Clark, Stefan, Shors, Douglas, Weeks, Bryan, Smith, Jason, Wingers, Louis

“…The Simon and Speck families of block ciphers were designed specifically to offer security on constrained devices, where simplicity of design is crucial…”
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Quantum Neural Network Compression Autor Hu, Zhirui, Dong, Peiyan, Wang, Zhepeng, Lin, Youzuo, Wang, Yanzhi, Jiang, Weiwen

“…Model compression, such as pruning and quantization, has been widely applied to optimize neural networks on resource-limited classical devices. Recently, there…”
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Data Reduction Techniques for Simulation, Visualization and Data Analysis Autor Li, S., Marsaglia, N., Garth, C., Woodring, J., Clyne, J., Childs, H.

“…Data reduction is increasingly being applied to scientific data for numerical simulations, scientific visualizations and data analyses. It is most often used…”
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Faster and Stronger Lossless Compression with Optimized Autoregressive Framework Autor Mao, Yu, Li, Jingzong, Cui, Yufei, Xue, Jason Chun

“…Neural AutoRegressive (AR) framework has been applied in general-purpose lossless compression recently to improve compression performance. However, this paper…”
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New Attacks and Defense for Encrypted-Address Cache Autor Qureshi, Moinuddin K.

“…Conflict-based cache attacks can allow an adversary to infer the access pattern of a co-running application by orchestrating evictions via cache conflicts…”
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BLOOM: Bit-Slice Framework for DNN Acceleration with Mixed-Precision Autor Liu, Fangxin, Yang, Ning, Wang, Zongwu, Zhu, Xuanpeng, Yao, Haidong, Xiong, Xiankui, Jiang, Li, Guan, Haibing

“…Deep neural networks (DNNs) have revolutionized numerous AI applications, but their vast model sizes and limited hardware resources present significant…”
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NN-AdderNet: Nonnegative and Sparse Weight Optimization Towards Ultra-Low Bitwidth AdderNet Quantization and Compression Autor Zhang, Yunxiang, Sun, Gengchen, Fang, Lizhi, Sun, Biao, Zhao, Wenfeng

“…Emerging efficient deep neural network (DNN) models, such as AdderNet, have shown great promise in significantly improving hardware efficiency compared to…”
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PacTrain: Pruning and Adaptive Sparse Gradient Compression for Efficient Collective Communication in Distributed Deep Learning Autor Wang, Yisu, Wu, Ruilong, Li, Xinjiao, Kutscher, Dirk

“…Large-scale deep neural networks (DNN) exhibit excellent performance for various tasks. As DNNs and datasets grow, distributed training becomes extremely…”
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BirdMoE: Reducing Communication Costs for Mixture-of-Experts Training Using Load-Aware Bi-random Quantization Autor Wu, Donglei, Yang, Weihao, Zou, Xiangyu, Jia, Jinda, Tao, Dingwen, Xia, Wen, Tian, Zhihong

“…Mixture-of-Experts (MoE) model parallelism is prevalent in training Large Language Models (e.g., ChatGPT). However, the intensive all-to-all collective…”
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MemSens: Significantly Reducing Memory Overhead in Adjoint Sensitivity Analysis Using Novel Error-Bounded Lossy Compression Autor Li, Chenxi, Feng, Yihang, Deng, Fuxing, Tao, Dingwen, Liu, Weifeng, Jin, Zhou

“…Adjoint sensitivity analysis is an exceptionally efficient method for computing the gradient of an objective function with respect to given parameters, playing…”
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DCDiff: Enhancing JPEG Compression via Diffusion-based DC Coefficients Estimation Autor Zhang, Ziyuan, Qiu, Han, Zhang, Tianwei, Chen, Bin, Zhang, Chao

“…JPEG is the most widely-used image compression method on low-cost cameras which cannot support learning-based compressors. One promising approach to enhance…”
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PISA: Efficient Precision-Slice Framework for LLMs with Adaptive Numerical Type Autor Yang, Ning, Wang, Zongwu, Sun, Qingxiao, Lu, Liqiang, Liu, Fangxin

“…Large language models (LLMs) have transformed numerous AI applications, with on-device deployment becoming increasingly important for reducing cloud computing…”
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SNAPPIX: Efficient-Coding-Inspired In-Sensor Compression for Edge Vision Autor Lin, Weikai, Ma, Tianrui, Boloor, Adith, Feng, Yu, Xing, Ruofan, Zhang, Xuan, Zhu, Yuhao

“…Energy-efficient image acquisition on the edge is crucial for enabling remote sensing applications where the sensor node has weak compute capabilities and must…”
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ClusterKV: Manipulating LLM KV Cache in Semantic Space for Recallable Compression Autor Liu, Guangda, Li, Chengwei, Zhao, Jieru, Zhang, Chenqi, Guo, Minyi

“…Large Language Models (LLMs) have been widely deployed in a variety of applications, and the context length is rapidly increasing to handle tasks such as…”
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CognitiveArm: Enabling Real-Time EEG-Controlled Prosthetic Arm Using Embodied Machine Learning Autor Basit, Abdul, Nawaz, Maha, Rehman, Saim, Shafique, Muhammad

“…Efficient control of prosthetic limbs via non-invasive brain-computer interfaces (BCIs) requires advanced EEG processing capabilities-including pre-filtering,…”
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Late Breaking Results: Less Sense Makes More Sense: In-Sensor Compressive Learning for Efficient Machine Vision Autor Liang, Yiwen, Cao, Weidong

“…Integrating deep learning and image sensors has significantly transformed machine vision applications. Yet, conventional highresolution image acquisition…”
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APSQ: Additive Partial Sum Quantization with Algorithm-Hardware Co-Design Autor Tan, Yonghao, Dong, Pingcheng, Wu, Yongkun, Liu, Yu, Liu, Xuejiao, Luo, Peng, Liu, Shih-Yang, Huang, Xijie, Zhang, Dong, Liang, Luhong, Cheng, Kwang-Ting

“…DNN accelerators, significantly advanced by model compression and specialized dataflow techniques, have marked considerable progress. However, the frequent…”
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Easz: An Agile Transformer-based Image Compression Framework for Resource-constrained IoTs Autor Mao, Yu, Li, Jingzong, Wang, Jun, Xu, Hong, Kuo, Tei-Wei, Guan, Nan, Xue, Chun Jason

“…Neural image compression, necessary in various machine-to-machine communication scenarios, suffers from its heavy encode-decode structures and inflexibility in…”
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MILLION: MasterIng Long-Context LLM Inference Via Outlier-Immunized KV Product QuaNtization Autor Wang, Zongwu, Xu, Peng, Liu, Fangxin, Hu, Yiwei, Sun, Qingxiao, Li, Gezi, Li, Cheng, Wang, Xuan, Jiang, Li, Guan, Haibing

“…Large language models (LLMs) are increasingly utilized for complex tasks requiring longer context lengths, with some models supporting up to 128 K or 1 M…”
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KVO-LLM: Boosting Long-Context Generation Throughput for Batched LLM Inference Autor Li, Zhenyu, Lyu, Dongxu, Wang, Gang, Chen, Yuzhou, Chen, Liyan, Li, Wenjie, Jiang, Jianfei, Sun, Yanan, He, Guanghui

“…With the widespread deployment of long-context large language models (LLMs), efficient and high-quality generation is becoming increasingly important. Modern…”
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