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高效架构上的高效模型.pdf

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1、AI Hardware&SystemsaiandsystemsSteven Brightfield Efficient Models on Efficient ArchitecturesChief Marketing Officer2024 BrainChip Inc.1AI Hardware&Systemsaiandsystems4 Elementsof AIDataSoftwareHardwareElectricitySoftwareDataEnergyHardwareDatasets growing exponentially and the resulting model parame

2、tersPower costs rising in cloud,hard limits on power on the edge4 Elements of AI2024 BrainChip Inc.2AI Hardware&SystemsaiandsystemsModel Execution PowerNeural Model Complexity(operations/model)Neural Model Execution(operations/watt)=The Model Efficiency Equation4 Elementsof AIDataSoftwareHardwareEle

3、ctricitySoftwareDataEnergyHardware2024 BrainChip Inc.3AI Hardware&SystemsaiandsystemsUsing Foundation ModelsPruning and distillationFine tuningTrade off quality versus model sizeUse smaller context windowsRAG AssistanceMore efficient trainingIncremental trainingRelevant Subset trainingNew Foundation

4、 ModelsNew models suited for edge use casesNeural Model Complexity4 Elementsof AIDataSoftwareHardwareElectricitySoftwareDataEnergyHardware2024 BrainChip Inc.4AI Hardware&SystemsaiandsystemsAlgorithmic Compute Efficiency=Model Metric(PESQ,Perplexity,mAP)MACs/inference(power+area)Algorithmic Memory Ef

5、ficiency=Model MetricParameters(memory movement)The Neural Model Efficiency2024 BrainChip Inc.5AI Hardware&SystemsaiandsystemsNew NPU chip architecturesReduced precisionIn-memory computeAnalog computeHigh sparsity executionEfficient scheduling compilersDedicated Transformer acceleratorsOpticalQuantu

6、mNew siliconSmaller process nodesLower voltagesBetter heat dissipationNeural Model Execution4 Elementsof AIDataSoftwareHardwareElectricitySoftwareDataEnergyHardware2024 BrainChip Inc.6AI Hardware&SystemsaiandsystemsCompute Efficiency=Actual MACs/sec ComputedTotal MACs/sec PossibleWhat percentage of

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本文主要探讨了AI硬件与系统领域中,如何在数据、软件、硬件和电力四个方面提高AI模型效率。首先,介绍了模型执行效率、神经模型复杂性、数据软件硬件电力等四个要素。其次,文章提出了使用基础模型、剪枝和蒸馏、细调等方法来提高模型效率,并介绍了适用于边缘计算的新一代基础模型。然后,文章探讨了如何通过算法、计算效率、内存效率等手段提高AI硬件效率,包括新的NPU芯片架构、降低精度、内存计算、模拟计算等。最后,文章介绍了Akida事件驱动计算平台,以及TENN和Mamba等新型网络模型,这些模型在边缘计算应用中表现出极高的效率。
如何提高模型效率?" TENN模型如何简化解决方案?" 如何实现极低功耗的边缘计算?"
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