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Hardware Acceleration Implementation of Sparse Coding Algorithm with Spintronic Devices

机译:自旋电子器件的稀疏编码算法的硬件加速实现

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In this paper, we explore the possibility of hardware acceleration implementation of sparse coding algorithm with spintronic devices by a series of design optimizations across the architecture, circuit and device. Firstly, a domain wall motion (DWM) based compound spintronic device (CSD) is engineered and modelled, which is envisioned to achieve multiple conductance states. Sequentially, a parallel architecture is presented based on a dense cross-point array of the proposed DWM based CSD, where each dictionary (D) value can be mapped into the conductance of the proposed DWM based CSD at the corresponding cross-point. Benefitting from its massively parallel read and write operation, such proposed parallel architecture can accelerate the selected sparse coding algorithm using a designed dedicated periphery read and write circuit. Experimental results show that the selected sparse coding algorithm can be accelerated by 1400× with the proposed parallel architecture in comparison with software implementation. Moreover, its energy dissipation is 8 orders of magnitude smaller than that with software implementation.
机译:在本文中,我们通过在体系结构,电路和设备上进行了一系列设计优化,探索了用自旋电子设备实现稀疏编码算法的硬件加速实现的可能性。首先,对基于畴壁运动(DWM)的复合自旋电子器件(CSD)进行了工程设计和建模,可以实现多种电导状态。依次,提出了一个基于建议的基于DWM的CSD的密集交叉点数组的并行体系结构,其中每个字典(D)值可以映射到建议的基于DWM的CSD在相应交叉点处的电导。受益于其大规模的并行读写操作,这种拟议的并行体系结构可以使用设计的专用外围读写电路来加速所选的稀疏编码算法。实验结果表明,与软件实现相比,所提出的并行体系结构可以将所选的稀疏编码算法加速1400倍。此外,它的能耗比软件实现的能耗小8个数量级。

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