论文标题
Kleslesydra-t：设计多线程边缘核心的矢量协处理器
Klessydra-T: Designing Vector Coprocessors for Multi-Threaded Edge-Computing Cores
论文作者
论文摘要
计算密集型内核，例如卷积，矩阵乘法和傅立叶变换，是边缘计算AI，信号处理和加密应用的基础。相互交织的杂种线程（IMT）处理器内核很有趣，可以追求能源效率和低硬件成本以进行边缘计算，但是他们需要硬件加速方案来运行大量的计算工作负载。遵循矢量加速计算的方法，本研究探讨了在RISC-V内核中实现向量调查单元的可能替代方法，显示了目标工作负载中IMT和数据级并行性之间的协同作用。
Computation intensive kernels, such as convolutions, matrix multiplication and Fourier transform, are fundamental to edge-computing AI, signal processing and cryptographic applications. Interleaved-Multi-Threading (IMT) processor cores are interesting to pursue energy efficiency and low hardware cost for edge-computing, yet they need hardware acceleration schemes to run heavy computational workloads. Following a vector approach to accelerate computations, this study explores possible alternatives to implement vector coprocessing units in RISC-V cores, showing the synergy between IMT and data-level parallelism in the target workloads.
