65 citations · 376 across the 32 of their papers we have counts for
10 papers · 1 filter
CiMBA: Accelerating Genome Sequencing through On-Device Basecalling via Compute-in-Memory
William Andrew Simon, Irem Boybat, Riselda Kodra +8
As genome sequencing is finding utility in a wide variety of domains beyond the confines of traditional medical settings, its computational pipeline faces two significant challenge…
Swordfish: A Framework for Evaluating Deep Neural Network-based Basecalling using Computation-In-Memory with Non-Ideal Memristors
Taha Shahroodi, Gagandeep Singh, Mahdi Zahedi +6
Basecalling, an essential step in many genome analysis studies, relies on large Deep Neural Networks (DNNs) to achieve high accuracy. Unfortunately, these DNNs are computationally…
MetaStore: High-Performance Metagenomic Analysis via In-Storage Computing
Nika Mansouri Ghiasi, Mohammad Sadrosadati, Harun Mustafa +9
Metagenomics has led to significant advancements in many fields. Metagenomic analysis commonly involves the key tasks of determining the species present in a sample and their relat…
An In-Memory Architecture for High-Performance Long-Read Pre-Alignment Filtering
Taha Shahroodi, Michael Miao, Joel Lindegger +3
With the recent move towards sequencing of accurate long reads, finding solutions that support efficient analysis of these reads becomes more necessary. The long execution time req…
Victima: Drastically Increasing Address Translation Reach by Leveraging Underutilized Cache Resources
Konstantinos Kanellopoulos, Hong Chul Nam, F. Nisa Bostanci +5
Address translation is a performance bottleneck in data-intensive workloads due to large datasets and irregular access patterns that lead to frequent high-latency page table walks…
GateSeeder: Near-memory CPU-FPGA Acceleration of Short and Long Read Mapping
Julien Eudine, Mohammed Alser, Gagandeep Singh +2
Motivation: Read mapping is a computationally expensive process and a major bottleneck in genomics analyses. The performance of read mapping is mainly limited by the performance of…
Accelerating Genome Analysis via Algorithm-Architecture Co-Design
Onur Mutlu, Can Firtina
High-throughput sequencing (HTS) technologies have revolutionized the field of genomics, enabling rapid and cost-effective genome analysis for various applications. However, the in…
RUBICON: A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers
Gagandeep Singh, Mohammed Alser, Kristof Denolf +5
Nanopore sequencing generates noisy electrical signals that need to be converted into a standard string of DNA nucleotide bases using a computational step called basecalling. The a…
GenPIP: In-Memory Acceleration of Genome Analysis via Tight Integration of Basecalling and Read Mapping
Haiyu Mao, Mohammed Alser, Mohammad Sadrosadati +6
Nanopore sequencing is a widely-used high-throughput genome sequencing technology that can sequence long fragments of a genome into raw electrical signals at low cost. Nanopore seq…
ApHMM: Accelerating Profile Hidden Markov Models for Fast and Energy-Efficient Genome Analysis
Can Firtina, Kamlesh Pillai, Gurpreet S. Kalsi +10
Profile hidden Markov models (pHMMs) are widely employed in various bioinformatics applications to identify similarities between biological sequences, such as DNA or protein sequen…