74 citations · 76 across the 4 of their papers we have counts for
7 papers
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…
Accelerating Genome Sequence Analysis via Efficient Hardware/Algorithm Co-Design
Damla Senol Cali
Genome sequence analysis plays a pivotal role in enabling many medical and scientific advancements in personalized medicine, outbreak tracing, and forensics. However, the analysis…
FPGA-Based Near-Memory Acceleration of Modern Data-Intensive Applications
Gagandeep Singh, Mohammed Alser, Damla Senol Cali +4
Modern data-intensive applications demand high computation capabilities with strict power constraints. Unfortunately, such applications suffer from a significant waste of both exec…
Accelerating Genome Analysis: A Primer on an Ongoing Journey
Mohammed Alser, Zülal Bingöl, Damla Senol Cali +4
Genome analysis fundamentally starts with a process known as read mapping, where sequenced fragments of an organism's genome are compared against a reference genome. Read mapping i…
GenASM: A High-Performance, Low-Power Approximate String Matching Acceleration Framework for Genome Sequence Analysis
Damla Senol Cali, Gurpreet S. Kalsi, Zülal Bingöl +13
Genome sequence analysis has enabled significant advancements in medical and scientific areas such as personalized medicine, outbreak tracing, and the understanding of evolution. U…
Understanding the Interactions of Workloads and DRAM Types: A Comprehensive Experimental Study
Saugata Ghose, Tianshi Li, Nastaran Hajinazar +2
It has become increasingly difficult to understand the complex interaction between modern applications and main memory, composed of DRAM chips. Manufacturers are now selling and pr…