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- W4311543031 abstract "We present two high-performance implementations of the convolution operator via the direct algorithm that outperform the so-called lowering approach based on the im2col transform plus the gemm kernel on an ARMv8-based processor. One of our methods presents the additional advantage of zero-memory overhead while the other employs an additional yet rather moderate workspace, substantially smaller than that required by the im2col+gemm solution. In contrast with a previous implementation of a similar zero-memory overhead direct convolution, this work exhibits the key advantage of preserving the conventional NHWC data layout for the input/output activations of the convolution layers." @default.
- W4311543031 created "2022-12-27" @default.
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- W4311543031 date "2023-02-01" @default.
- W4311543031 modified "2023-10-18" @default.
- W4311543031 title "Reformulating the direct convolution for high-performance deep learning inference on ARM processors" @default.
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- W4311543031 doi "https://doi.org/10.1016/j.sysarc.2022.102806" @default.
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