Nam Sung Kim
7 papers · 2018–2026 · 4 venues · across top CS/AI venues
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Achievements
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π£ Hot Topic Early Bird π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π Conference Polyglot Β· Bronze πΊοΈ Taxonomy Completionist (12)
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Venues
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Research topics
Keywords
distributed training
(4)
gradient aggregation
(1)
distributed learning
(1)
neural network optimization
(1)
vector quantization
(1)
rate limiting
(1)
convergence rate
(1)
convolutional neural network
(1)
gradient compression
(1)
tail latency
(1)
performance isolation
(1)
data center
(1)
programmable switch
(1)
bandwidth efficiency
(1)
memory management
(1)
storage system
(1)
metadata management
(1)
i/o scheduler
(1)
nvme driver
(1)
firmware optimization
(1)
Papers
MAC: Metadata Acceleration for Sustainable Performance in Big-Data Systems with CXL DRAM
OSDI 2026
Harmonic: Hardware-assisted RDMA Performance Isolation for Public Clouds
NSDI 2024
PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication
ICLR 2022
Unlocking the Power of Inline Floating-Point Operations on Programmable Switches
NSDI 2022
FlashShare: Punching Through Server Storage Stack from Kernel to Firmware for Ultra-Low Latency SSDs
OSDI 2018
GradiVeQ: Vector Quantization for Bandwidth-Efficient Gradient Aggregation in Distributed CNN Training
NeurIPS 2018
Pipe-SGD: A Decentralized Pipelined SGD Framework for Distributed Deep Net Training
NeurIPS 2018