SAFARI Live Seminar: Haiyu Mao, March 29 2023

Join us for our upcoming SAFARI Live Seminar

Speaker:  Haiyu Mao, SAFARI Research Group, ETH Zurich
Where: Livestream on YouTube Link & HG D 5.3
Date:  Wednesday, March 29 2023, ​​13:00 Zurich time (CEST)

Title: GenPIP: In-Memory Acceleration of Genome Analysis via Tight Integration of Basecalling and Read Mapping

[Talk Slides (pptx) (pdf)]

Nanopore sequencing is a widely-used high-throughput genome sequencing technology that can sequence long fragments of a genome into raw electrical signals at a low cost. Nanopore sequencing requires two computationally-costly processing steps for accurate downstream genome analysis. The first step, basecalling, translates the raw electrical signals into nucleotide bases (i.e., A, C, G, T). The second step, read mapping, finds the correct location of a read in a reference genome. In existing genome analysis pipelines, basecalling and read mapping are executed separately. We observe in this work that such separate execution of the two most time-consuming steps inherently leads to (1) significant data movement and (2) redundant computations on the data, slowing down the genome analysis pipeline.

In this talk, I introduce GenPIP, an in-memory genome analysis accelerator that tightly integrates basecalling and read mapping. GenPIP improves the performance of the genome analysis pipeline with two key mechanisms: (1) in-memory fine-grained collaborative execution of the major genome analysis steps in parallel; (2) a new technique for early-rejection of low-quality and unmapped reads to timely stop the execution of genome analysis for such reads, reducing inefficient computation. Our experiments show that, for the execution of the genome analysis pipeline, GenPIP provides 41.6× (8.4×) speedup and 32.8× (20.8×) energy savings with negligible accuracy loss compared to the state-of-the-art software genome analysis tools executed on a state-of-the-art CPU (GPU). Compared to a design that combines state-of-the-art in-memory basecalling and read mapping accelerators, GenPIP provides 1.39× speedup and 1.37× energy savings.

Speaker Bio:
Haiyu Mao is a Senior Researcher in the SAFARI Research group at ETH Zurich, Switzerland. In July 2020, she received her Ph.D. degree from Tsinghua University, China. Her research interests include non-volatile memory, processing in memory, memory security, bioinformatics, and machine learning accelerators.  Visit Haiyu’s personal website for more info:

Related Paper: 

Haiyu Mao, Mohammed Alser, Mohammad Sadrosadati, Can Firtina, Akanksha Baranwal, Damla Senol Cali, Aditya Manglik, Nour Almadhoun Alserr, and Onur Mutlu. “GenPIP: In-Memory Acceleration of Genome Analysis via Tight Integration of Basecalling and Read Mapping.” Proceedings of the 2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO), Chicago, October 2022.
[Slides pptx pdf]
[arXiv version]
[Short Talk (10 minutes)] (last 15 minutes in the lecture)


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