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Found 2 papers, 1 papers with code
Beyond Inference: Performance Analysis of DNN Server Overheads for Computer Vision
Our results consistently demonstrate that end-to-end application performance can easily be dominated by data processing and data movement functions (up to 56% of end-to-end latency in a medium-sized image, and $\sim$ 80% impact on system throughput in a large image), even though these functions have been conventionally overlooked in deep learning system design.
PQA: Exploring the Potential of Product Quantization in DNN Hardware Acceleration
We identify PQ configurations that improve performance-per-area for ResNet20 by up to 3. 1$\times$, even when compared to a highly optimized conventional DNN accelerator, with similar improvements on two additional compact DNNs.
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