RASSA: Resistive Pre-Alignment Accelerator for Approximate DNA Long Read Mapping
DNA read mapping is a computationally expensive bioinformatics task, required for genome assembly and consensus polishing. It requires to find the best-fitting location for each DNA read on a long reference sequence. A novel resistive approximate similarity search accelerator, RASSA, exploits charge distribution and parallel in-memory processing to reflect a mismatch count between DNA sequences. RASSA implementation of DNA long read pre-alignment outperforms the state-of-art solution, minimap2, by 16-77x with comparable accuracy and provides two orders of magnitude higher throughput than GateKeeper, a short-read pre-alignment hardware architecture implemented in FPGA.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Zero-shifting Technique for Deep Neural Network Training on Resistive Cross-point Arrays
A resistive memory device-based computing architecture is one of the promising platforms for energy-efficient Deep Neural Network (DNN) training accelerators. The key technical challenge in realizing such accelerators is…
Multiscale Co-Design Analysis of Energy, Latency, Area, and Accuracy of a ReRAM Analog Neural Training Accelerator
Neural networks are an increasingly attractive algorithm for natural language processing and pattern recognition. Deep networks with >50M parameters are made possible by modern GPU clusters operating at <50 pJ per op and…
GPURED: A ReRAM-based Deconvolution Accelerator
Deconvolution has been widespread in neural networks. For example, it is essential for performing unsupervised learning in generative adversarial networks or constructing fully convolutional networks for semantic segment…
Semantic SegmentationNeural-PIM: Efficient Processing-In-Memory with Neural Approximation of Peripherals
Processing-in-memory (PIM) architectures have demonstrated great potential in accelerating numerous deep learning tasks. Particularly, resistive random-access memory (RRAM) devices provide a promising hardware substrate …
Quantization