8 papers
GenPairX: A Hardware-Algorithm Co-Designed Accelerator for Paired-End Read Mapping
Julien Eudine, Chu Li, Zhuo Cheng +11
Genome sequencing has become a central focus in computational biology. A genome study typically begins with sequencing, which produces millions to billions of short DNA fragments k…
SAGe: A Lightweight Algorithm-Architecture Co-Design for Mitigating the Data Preparation Bottleneck in Large-Scale Genome Sequence Analysis
Nika Mansouri Ghiasi, Talu Güloglu, Harun Mustafa +8
Genome sequence analysis, which examines the DNA sequences of organisms, drives advances in many critical medical and biotechnological fields. Given its importance and the exponent…
REIS: A High-Performance and Energy-Efficient Retrieval System with In-Storage Processing
Kangqi Chen, Andreas Kosmas Kakolyris, Rakesh Nadig +7
Large Language Models (LLMs) face an inherent challenge: their knowledge is confined to the data that they have been trained on. To overcome this issue, Retrieval-Augmented Generat…
MARS: Processing-In-Memory Acceleration of Raw Signal Genome Analysis Inside the Storage Subsystem
Melina Soysal, Konstantina Koliogeorgi, Can Firtina +8
Raw signal genome analysis (RSGA) has emerged as a promising approach to enable real-time genome analysis by directly analyzing raw electrical signals. However, rapid advancements…
CIPHERMATCH: Accelerating Homomorphic Encryption-Based String Matching via Memory-Efficient Data Packing and In-Flash Processing
Mayank Kabra, Rakesh Nadig, Harshita Gupta +7
Homomorphic encryption (HE) allows secure computation on encrypted data without revealing the original data, providing significant benefits for privacy-sensitive applications. Many…
PAPI: Exploiting Dynamic Parallelism in Large Language Model Decoding with a Processing-In-Memory-Enabled Computing System
Yintao He, Haiyu Mao, Christina Giannoula +6
Large language models (LLMs) are widely used for natural language understanding and text generation. An LLM model relies on a time-consuming step called LLM decoding to generate ou…