89 citations · 191 across the 20 of their papers we have counts for
20 papers
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…
Asynchronous Persistence with ASAP
Ahmed Abulila, Izzat El Hajj, Myoungsoo Jung +1
Supporting atomic durability of updates for persistent memories is typically achieved with Write-Ahead Logging (WAL). WAL flushes log entries to persistent memory before making the…
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…
Hardware/Software Co-Programmable Framework for Computational SSDs to Accelerate Deep Learning Service on Large-Scale Graphs
Miryeong Kwon, Donghyun Gouk, Sangwon Lee +1
Graph neural networks (GNNs) process large-scale graphs consisting of a hundred billion edges. In contrast to traditional deep learning, unique behaviors of the emerging GNNs are e…
Ohm-GPU: Integrating New Optical Network and Heterogeneous Memory into GPU Multi-Processors
Jie Zhang, Myoungsoo Jung
Traditional graphics processing units (GPUs) suffer from the low memory capacity and demand for high memory bandwidth. To address these challenges, we propose Ohm-GPU, a new optica…
Revamping Storage Class Memory With Hardware Automated Memory-Over-Storage Solution
Jie Zhang, Miryeong Kwon, Donghyun Gouk +4
Large persistent memories such as NVDIMM have been perceived as a disruptive memory technology, because they can maintain the state of a system even after a power failure and allow…
FastDrain: Removing Page Victimization Overheads in NVMe Storage Stack
Jie Zhang, Miryeong Kwon, Sanghyun Han +3
Host-side page victimizations can easily overflow the SSD internal buffer, which interferes I/O services of diverse user applications thereby degrading user-level experiences. To a…
ZnG: Architecting GPU Multi-Processors with New Flash for Scalable Data Analysis
Jie Zhang, Myoungsoo Jung
We propose ZnG, a new GPU-SSD integrated architecture, which can maximize the memory capacity in a GPU and address performance penalties imposed by an SSD. Specifically, ZnG replac…
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…
Exploring Fault-Tolerant Erasure Codes for Scalable All-Flash Array Clusters
Sungjoon Koh, Jie Zhang, Miryeong Kwon +4
Large-scale systems with all-flash arrays have become increasingly common in many computing segments. To make such systems resilient, we can adopt erasure coding such as Reed-Solom…
FUSE: Fusing STT-MRAM into GPUs to Alleviate Off-Chip Memory Access Overheads
Jie Zhang, Myoungsoo Jung, Mahmut Taylan Kandemir
In this work, we propose FUSE, a novel GPU cache system that integrates spin-transfer torque magnetic random-access memory (STT-MRAM) into the on-chip L1D cache. FUSE can minimize…
Amber: Enabling Precise Full-System Simulation with Detailed Modeling of All SSD Resources
Donghyun Gouk, Miryeong Kwon, Jie Zhang +5
SSDs become a major storage component in modern memory hierarchies, and SSD research demands exploring future simulation-based studies by integrating SSD subsystems into a full-sys…
Revitalizing Copybacks in Modern SSDs: Why and How
Duwon Hong, Myungsuk Kim, Jisung Park +2
For modern flash-based SSDs, the performance overhead of internal data migrations is dominated by the data transfer time, not by the flash program time as in old SSDs. In order to…
CIAO: Cache Interference-Aware Throughput-Oriented Architecture and Scheduling for GPUs
Jie Zhang, Shuwen Gao, Nam Sung Kim +1
A modern GPU aims to simultaneously execute more warps for higher Thread-Level Parallelism (TLP) and performance. When generating many memory requests, however, warps contend for l…
FlashAbacus: A Self-Governing Flash-Based Accelerator for Low-Power Systems
Jie Zhang, Myoungsoo Jung
Energy efficiency and computing flexibility are some of the primary design constraints of heterogeneous computing. In this paper, we present FlashAbacus, a data-processing accelera…
Understanding System Characteristics of Online Erasure Coding on Scalable, Distributed and Large-Scale SSD Array Systems
Sungjoon Koh, Jie Zhang, Miryeong Kwon +4
Large-scale systems with arrays of solid state disks (SSDs) have become increasingly common in many computing segments. To make such systems resilient, we can adopt erasure coding…
TraceTracker: Hardware/Software Co-Evaluation for Large-Scale I/O Workload Reconstruction
Miryeong Kwon, Jie Zhang, Gyuyoung Park +5
Block traces are widely used for system studies, model verifications, and design analyses in both industry and academia. While such traces include detailed block access patterns, e…
Sprinkler: Maximizing Resource Utilization in Many-Chip Solid State Disks
Myoungsoo Jung, Mahmut T. Kandemir
Resource utilization is one of the emerging problems in many-chip SSDs. In this paper, we propose Sprinkler, a novel device-level SSD controller, which targets maximizing resource…
SimpleSSD: Modeling Solid State Drives for Holistic System Simulation
Myoungsoo Jung, Jie Zhang, Ahmed Abulila +5
Existing solid state drive (SSD) simulators unfortunately lack hardware and/or software architecture models. Consequently, they are far from capturing the critical features of cont…
Exploiting Data Longevity for Enhancing the Lifetime of Flash-based Storage Class Memory
Wonil Choi, Mohammad Arjomand, Myoungsoo Jung +1
Storage-class memory (SCM) combines the benefits of a solid-state memory, such as high-performance and robustness, with the archival capabilities and low cost of conventional hard-…