activity
20182026
most citedVenice: Improving Solid-State Drive Parallelism at Low Cost via Conflict-Free Accesses

29 citations · 143 across the 52 of their papers we have counts for

collaborators
Showing cs.ARShow all

41 papers · 1 filter

cs.AR2026

CertiFlash: A Formal Verification Framework for Flash Translation Layers in Computational Solid State Drives

Harshita Gupta, Mayank Kabra, Rakesh Nadig +10

Data-intensive applications move large amounts of data from storage to the compute unit, incurring significant data movement overhead. Storage-centric computing reduces this overhe…

cs.AR2026

FLINT: Efficiently Leveraging High Bandwidth Flash for Capacity-Scalable LLM Inference Acceleration

Geraldo F. Oliveira, Arash Tavakkol, Xiangyu Zhu +10

LLM inference is increasingly constrained by accelerator memory capacity rather than compute throughput. This constraint is especially acute in single-accelerator and small-node in…

cs.AR2026

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…

cs.AR2026

Clutch: High Performance Vector-Scalar Comparison using DRAM via Chunked Temporal Coding

Daichi Tokuda, Tatsuya Kubo, Ismail Emir Yuksel +8

Vector-scalar comparison is a fundamental computation primitive that compares each element in a vector against a single scalar value. It is widely used in various data-intensive wo…

cs.AR2026

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…

cs.AR2026

Conduit: Programmer-Transparent Near-Data Processing Using Multiple Compute-Capable Resources in Solid State Drives

Rakesh Nadig, Vamanan Arulchelvan, Mayank Kabra +9

Solid-state drives (SSDs) are well suited for near-data processing (NDP) because they: (1) store large application datasets, and (2) support three NDP paradigms: in-storage process…