H
Haiyu Mao
Researcher at Tsinghua University
Publications - 15
Citations - 174
Haiyu Mao is an academic researcher from Tsinghua University. The author has contributed to research in topics: Computer science & Biology. The author has an hindex of 4, co-authored 6 publications receiving 65 citations.
Papers
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Proceedings ArticleDOI
LerGAN: a zero-free, low data movement and PIM-based GAN architecture
TL;DR: LerGAN, a PIM-based GAN accelerator to address the challenges of training GAN is proposed, with a zero-free data reshaping scheme for ReRAM-based PIM and a 3D-connected PIM, which can reconfigure connections inside PIM dynamically according to dataflows of propagation and updating.
Proceedings ArticleDOI
Exploring data placement in racetrack memory based scratchpad memory
TL;DR: This paper explored data allocation in SPM based on racetrack memory (RM), which is an emerging NVM with ultra-high storage density and fast access speed and addressed how to leverage genetic algorithm to achieve near-optimal data allocation.
Proceedings ArticleDOI
GenStore: a high-performance in-storage processing system for genome sequence analysis
Nika Mansouri Ghiasi,Ji-Soo Park,Harun Mustafa,Jeremie S. Kim,Ataberk Olgun,Arvid Gollwitzer,Damla Senol Cali,Can Fırtına,Haiyu Mao,N. Alserr,Rachata Ausavarungnirun,Nandita Vijaykumar,Mohammed Alser,Onur Mutlu +13 more
TL;DR: GenStore is proposed, the first in-storage processing system designed for genome sequence analysis that greatly reduces both data movement and computational overheads of genome sequenceAnalysis by exploiting low-cost and accurate in- storage filters.
Proceedings ArticleDOI
No Compromises: Secure NVM with Crash Consistency, Write-Efficiency and High-Performance
TL;DR: The proposed cc-NVM proposes an epoch-based mechanism to aggressively cache the security metadata in CPU cache while retaining the consistency of them in NVM, and deferred spreading is also introduced to reduce the calculating overhead for data authentication.
Journal Article
GenStore: A High-Performance and Energy-Efficient In-Storage Computing System for Genome Sequence Analysis
Nika Mansouri Ghiasi,Ji-Soo Park,Harun Mustafa,Jeremie S. Kim,Ataberk Olgun,Arvid Gollwitzer,Damla Senol Cali,Can Fırtına,Haiyu Mao,N. Alserr,Rachata Ausavarungnirun,Nandita Vijaykumar,Mohammed Alser,Onur Mutlu +13 more
TL;DR: Through rigorous analysis of read mapping processes of reads with different properties and degrees of genetic variation, this work meticulously design low-cost hardware accelerators and data/computation flows inside a NAND flashbased solid-state drive (SSD).