activity
20242026
most citedAn Analog and Digital Hybrid Attention Accelerator for Transformers with Charge-based In-memory Computing

9 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AR2026

Cross-Domain Acceleration of Open Modification Search: From Commodity Platforms to Emerging Memory and Storage Devices

Sumukh Pinge, Chang Eun Song, Po-Kai Hsu +10

Open modification search (OMS) in mass spectrometry (MS) is a data-intensive workload whose performance is dominantly limited by reference data movement rather than computation. Pr…

cs.LG2026

STAR-KV: Low-Rank KV Cache Compression via Soft Thresholding for Adaptive Rank Control

Priyansh Bhatnagar, Ashkan Moradifirouzabadi, Se-Hyun Yang +3

Low-rank projection has emerged as a promising approach for compressing the KV cache by exploiting hidden-dimension redundancy. However, prior methods rely on fixed or heuristic ra…

cs.AR2025

FeNOMS: Enhancing Open Modification Spectral Library Search with In-Storage Processing on Ferroelectric NAND (FeNAND) Flash

Sumukh Pinge, Ashkan Moradifirouzabadi, Keming Fan +29

The rapid expansion of mass spectrometry (MS) data, now exceeding hundreds of terabytes, poses significant challenges for efficient, large-scale library search - a critical compone…

cs.AR2024

SpecPCM: A Low-power PCM-based In-Memory Computing Accelerator for Full-stack Mass Spectrometry Analysis

Keming Fan, Ashkan Moradifirouzabadi, Xiangjin Wu +6

Mass spectrometry (MS) is essential for proteomics and metabolomics but faces impending challenges in efficiently processing the vast volumes of data. This paper introduces SpecPCM…

cs.AR2024★ 9 cited

An Analog and Digital Hybrid Attention Accelerator for Transformers with Charge-based In-memory Computing

Ashkan Moradifirouzabadi, Divya Sri Dodla, Mingu Kang

The attention mechanism is a key computing kernel of Transformers, calculating pairwise correlations across the entire input sequence. The computing complexity and frequent memory…