46 citations · 139 across the 15 of their papers we have counts for
16 papers
Rawsamble: Overlapping and Assembling Raw Nanopore Signals using a Hash-based Seeding Mechanism
Can Firtina, Maximilian Mordig, Harun Mustafa +7
Raw nanopore signal analysis is a common approach in genomics to provide fast and resource-efficient analysis without translating the signals to bases (i.e., without basecalling).…
MegIS: High-Performance, Energy-Efficient, and Low-Cost Metagenomic Analysis with In-Storage Processing
Nika Mansouri Ghiasi, Mohammad Sadrosadati, Harun Mustafa +9
Metagenomics has led to significant advances in many fields. Metagenomic analysis commonly involves the key tasks of determining the species present in a sample and their relative…
RowPress Vulnerability in Modern DRAM Chips
Haocong Luo, Ataberk Olgun, A. Giray Yağlıkçı +6
Memory isolation is a critical property for system reliability, security, and safety. We demonstrate RowPress, a DRAM read disturbance phenomenon different from the well-known RowH…
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…
MetaTrinity: Enabling Fast Metagenomic Classification via Seed Counting and Edit Distance Approximation
Arvid E. Gollwitzer, Mohammed Alser, Joel Bergtholdt +5
Metagenomics, the study of genome sequences of diverse organisms cohabiting in a shared environment, has experienced significant advancements across various medical and biological…
RawAlign: Accurate, Fast, and Scalable Raw Nanopore Signal Mapping via Combining Seeding and Alignment
Joël Lindegger, Can Firtina, Nika Mansouri Ghiasi +3
Nanopore sequencers generate raw electrical signals representing the contents of a biological sequence molecule passing through the nanopore. These signals can be analyzed directly…
RawHash2: Mapping Raw Nanopore Signals Using Hash-Based Seeding and Adaptive Quantization
Can Firtina, Melina Soysal, Joël Lindegger +1
Summary: Raw nanopore signals can be analyzed while they are being generated, a process known as real-time analysis. Real-time analysis of raw signals is essential to utilize the u…
RowPress: Amplifying Read Disturbance in Modern DRAM Chips
Haocong Luo, Ataberk Olgun, A. Giray Yağlıkçı +6
Memory isolation is critical for system reliability, security, and safety. Unfortunately, read disturbance can break memory isolation in modern DRAM chips. For example, RowHammer i…
RawHash: Enabling Fast and Accurate Real-Time Analysis of Raw Nanopore Signals for Large Genomes
Can Firtina, Nika Mansouri Ghiasi, Joel Lindegger +4
Nanopore sequencers generate electrical raw signals in real-time while sequencing long genomic strands. These raw signals can be analyzed as they are generated, providing an opport…
TargetCall: Eliminating the Wasted Computation in Basecalling via Pre-Basecalling Filtering
Meryem Banu Cavlak, Gagandeep Singh, Mohammed Alser +6
Basecalling is an essential step in nanopore sequencing analysis where the raw signals of nanopore sequencers are converted into nucleotide sequences, i.e., reads. State-of-the-art…
Morpheus: Extending the Last Level Cache Capacity in GPU Systems Using Idle GPU Core Resources
Sina Darabi, Mohammad Sadrosadati, Joël Lindegger +6
Graphics Processing Units (GPUs) are widely-used accelerators for data-parallel applications. In many GPU applications, GPU memory bandwidth bottlenecks performance, causing underu…
Scrooge: A Fast and Memory-Frugal Genomic Sequence Aligner for CPUs, GPUs, and ASICs
Joël Lindegger, Damla Senol Cali, Mohammed Alser +3
Pairwise sequence alignment is a very time-consuming step in common bioinformatics pipelines. Speeding up this step requires heuristics, efficient implementations, and/or hardware…
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…
SeGraM: A Universal Hardware Accelerator for Genomic Sequence-to-Graph and Sequence-to-Sequence Mapping
Damla Senol Cali, Konstantinos Kanellopoulos, Joel Lindegger +15
A critical step of genome sequence analysis is the mapping of sequenced DNA fragments (i.e., reads) collected from an individual to a known linear reference genome sequence (i.e.,…
Algorithmic Improvement and GPU Acceleration of the GenASM Algorithm
Joël Lindegger, Damla Senol Cali, Mohammed Alser +2
We improve on GenASM, a recent algorithm for genomic sequence alignment, by significantly reducing its memory footprint and bandwidth requirement. Our algorithmic improvements redu…