activity
20192026
most citedFailure Tolerant Training with Persistent Memory Disaggregation over CXL

2 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.AR2026

AutoGNN: End-to-End Hardware-Driven Graph Preprocessing for Enhanced GNN Performance

Seungkwan Kang, Seungjun Lee, Donghyun Gouk +9

Graph neural network (GNN) inference faces significant bottlenecks in preprocessing, which often dominate overall inference latency. We introduce AutoGNN, an FPGA-based accelerator…

cs.DC2025

MPI-over-CXL: Enhancing Communication Efficiency in Distributed HPC Systems

Miryeong Kwon, Donghyun Gouk, Hyein Woo +10

MPI implementations commonly rely on explicit memory-copy operations, incurring overhead from redundant data movement and buffer management. This overhead notably impacts HPC workl…

cs.AR2025

From Block to Byte: Transforming PCIe SSDs with CXL Memory Protocol and Instruction Annotation

Miryeong Kwon, Donghyun Gouk, Junhyeok Jang +8

This paper explores how Compute Express Link (CXL) can transform PCIe-based block storage into a scalable, byte-addressable working memory. We address the challenges of adapting bl…

cs.AR2025

CXL-GPU: Pushing GPU Memory Boundaries with the Integration of CXL Technologies

Donghyun Gouk, Seungkwan Kang, Seungjun Lee +8

This work introduces a GPU storage expansion solution utilizing CXL, featuring a novel GPU system design with multiple CXL root ports for integrating diverse storage media (DRAMs a…

cs.AR2023

GraphTensor: Comprehensive GNN-Acceleration Framework for Efficient Parallel Processing of Massive Datasets

Junhyeok Jang, Miryeong Kwon, Donghyun Gouk +2

We present GraphTensor, a comprehensive open-source framework that supports efficient parallel neural network processing on large graphs. GraphTensor offers a set of easy-to-use pr…

cs.AR2023★ 2 cited

Failure Tolerant Training with Persistent Memory Disaggregation over CXL

Miryeong Kwon, Junhyeok Jang, Hanjin Choi +2

This paper proposes TRAININGCXL that can efficiently process large-scale recommendation datasets in the pool of disaggregated memory while making training fault tolerant with low o…

cs.OS2019

Faster than Flash: An In-Depth Study of System Challenges for Emerging Ultra-Low Latency SSDs

Sungjoon Koh, Junhyeok Jang, Changrim Lee +3

Emerging storage systems with new flash exhibit ultra-low latency (ULL) that can address performance disparities between DRAM and conventional solid state drives (SSDs) in the memo…