65 citations · 67 across the 8 of their papers we have counts for
8 papers
GRAINS: Storage-Aware Algorithm-Architecture Co-Design Enabling High-Performance and Low-Cost Graph-Based Genome Analysis
Nika Mansouri Ghiasi, Harun Mustafa, Talu Güloglu +8
Graph-based representations of genome sequences have emerged as a powerful approach for representing massive genomic databases in an expressive and efficient way. Despite their ben…
ASTRA-sim 3.0: Next-Level Distributed Machine Learning Simulations via High-Fidelity GPU and Infrastructure Modeling
William Won, Jinsun Yoo, Tuan Ta +16
Distributed machine learning (ML) is a key paradigm for today's large-scale artificial intelligence applications. As model inference arises as an important use case, faithful model…
No Generation without Representation: Efficient Causal Protein Language Models Enable Zero-Shot Fitness Estimation
Furkan Eris
Protein language models (PLMs) face a fundamental divide: masked language models (MLMs) excel at fitness prediction while causal models enable generation, forcing practitioners to…
RawBench: A Comprehensive Benchmarking Framework for Raw Nanopore Signal Analysis Techniques
Furkan Eris, Ulysse McConnell, Can Firtina +1
Nanopore sequencing technologies continue to advance rapidly, offering critical benefits such as real-time analysis, the ability to sequence extremely long DNA fragments (up to mil…
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).…
Puppeteer: A Random Forest-based Manager for Hardware Prefetchers across the Memory Hierarchy
Furkan Eris, Marcia S. Louis, Kubra Eris +2
Over the years, processor throughput has steadily increased. However, the memory throughput has not increased at the same rate, which has led to the memory wall problem in turn inc…
An Electro-Photonic System for Accelerating Deep Neural Networks
Cansu Demirkiran, Furkan Eris, Gongyu Wang +7
The number of parameters in deep neural networks (DNNs) is scaling at about 5 the rate of Moore's Law. To sustain this growth, photonic computing is a promising avenue, as…
Custom Tailored Suite of Random Forests for Prefetcher Adaptation
Furkan Eris, Sadullah Canakci, Cansu Demirkiran +1
To close the gap between memory and processors, and in turn improve performance, there has been an abundance of work in the area of data/instruction prefetcher designs. Prefetchers…