1 citations · 1 across the 6 of their papers we have counts for
6 papers
V-Rex: Real-Time Streaming Video LLM Acceleration via Dynamic KV Cache Retrieval
Donghyuk Kim, Sejeong Yang, Wonjin Shin +1
Streaming video large language models (LLMs) are increasingly used for real-time multimodal tasks such as video captioning, question answering, conversational agents, and augmented…
RED: Energy Optimization Framework for eDRAM-based PIM with Reconfigurable Voltage Swing and Retention-aware Scheduling
Jae-Young Kim, Donghyuk Kim, Seungjae Yoo +3
In the era of artificial intelligence (AI), Transformer demonstrates its performance across various applications. The excessive amount of parameters incurs high latency and energy…
Securing DRAM at Scale: ARFM-Driven Row Hammer Defense with Unveiling the Threat of Short tRC Patterns
Nogeun Joo, Donghyuk Kim, Hyunjun Cho +3
To address the issue of powerful row hammer (RH) attacks, our study involved an extensive analysis of the prevalent attack patterns in the field. We discovered a strong correlation…
HURRY: Highly Utilized, Reconfigurable ReRAM-based In-situ Accelerator with Multifunctionality
Hery Shin, Jae-Young Kim, Donghyuk Kim +1
Resistive random-access memory (ReRAM) crossbar arrays are suitable for efficient inference computations in neural networks due to their analog general matrix-matrix multiplication…
SAL-PIM: A Subarray-level Processing-in-Memory Architecture with LUT-based Linear Interpolation for Transformer-based Text Generation
Wontak Han, Hyunjun Cho, Donghyuk Kim +1
Text generation is a compelling sub-field of natural language processing, aiming to generate human-readable text from input words. In particular, the decoder-only generative models…
Darwin: A DRAM-based Multi-level Processing-in-Memory Architecture for Data Analytics
Donghyuk Kim, Jae-Young Kim, Wontak Han +4
Processing-in-memory (PIM) architecture is an inherent match for data analytics application, but we observe major challenges to address when accelerating it using PIM. In this pape…