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Nanopore Base Calling on the Edge

2020-11-09 · Peter Perešíni, Vladimír Boža, Broňa Brejová, Tomáš Vinař

We developed a new base caller DeepNano-coral for nanopore sequencing, which is optimized to run on the Coral Edge Tensor Processing Unit, a small USB-attached hardware accelerator. To achieve this goal, we have designed new versions of two key components used in convolutional neural networks for speech recognition and base calling. In our components, we propose a new way of factorization of a full convolution into smaller operations, which decreases memory access operations, memory access being a bottleneck on this device. DeepNano-coral achieves real-time base calling during sequencing with the accuracy slightly better than the fast mode of the Guppy base caller and is extremely energy efficient, using only 10W of power. Availability: https://github.com/fmfi-compbio/coral-basecaller

📄 PDF Abstract BibTeX arXiv:2011.04312

Code (1)

fmfi-compbio/coral-basecaller 공식 구현 tf

Tasks

speech-recognitionSpeech Recognition

Methods 이 논문이 사용한 방법론

CORAL 설명 없음
Convolution A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the…

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