KIAS CAC
High-Performance Computing for Research Excellence

Center for
Advanced Computation

KIAS CAC provides high-performance computing resources and technical support for cutting-edge research in mathematics, physics, computational science, and AI.

Get Started System Status
1,645
Running Jobs
762
Waiting Jobs
13,308
Total Cores
360
Compute Nodes

Latest News

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Announcement May 4, 2026

CAC2026

The 17th KIAS CAC Summer School on Artificial Intelligence & Parallel Computing

Announcement Jan 23, 2026

Launch of the New CAC Website

The new CAC website has been officially launched.

Maintenance Schedule

Full Schedule →
NETWORK Scheduled

방화벽 업데이트로 인한 클러스터 시스템 접속 불가 System access unavailable due to firewall upgrade

Feb 13, 2026 10:00- 12:00 KST

Quick Access

Frequently used resources and services for CAC users

Account Request

Apply for a new computing account or request additional resources

User Manual

Comprehensive guides for using our HPC systems

FAQ

Answers to frequently asked questions about our services

Support

Get help with technical issues and resource allocation

Real-time Monitoring

System Status

Monitor the current status of our high-performance computing clusters. Data is updated every 10 minutes.

ADA

5 nodes / 320 cores

Healthy
CPU Usage 45.3%
0 nodes up
145 / 320
19 running
7 pending

GRAMMAR

113 nodes / 7,232 cores

Healthy
CPU Usage 98.9%
111 nodes up
7,151 / 7,232
140 running
173 pending

LEXICON

12 nodes / 288 cores

Warning
CPU Usage 0.0%
10 / 2 down
0 / 288
0 running
0 pending

SYNTAX

13 nodes / 832 cores

Healthy
CPU Usage 45.1%
2 nodes up
375 / 832
71 running
497 pending

BAEKDU

95 nodes / 1,900 cores

Healthy
CPU Usage 99.0%
95 nodes up
1,880 / 1,900
1354 running
5 pending

DNA

53 nodes / 1,080 cores

Healthy
CPU Usage 55.6%
53 nodes up
600 / 1,080
15 running
0 pending

RNA

69 nodes / 1,656 cores

Healthy
CPU Usage 100.0%
69 nodes up
1,656 / 1,656
46 running
80 pending
View Detailed Status
Publications

Recent Research

Latest publications from CAC researchers

Computational Material Science 2026

QAssemble: A Pure Python Package for Quantum Many-Body Theory

Seongjun Mo, Dongming Li, Mancheon Han, Johan Jönsson, Byungkyun Kang, Hoonkyung Lee, Gabriel Kotliar, Sangkook Choi

Astrophysics 2026

Revealing Hidden Cosmic Flows through the Zone of Avoidance with Deep Learning

Alexandra Dupuy, Donghui Jeong, Sungwook E. Hong, Ho Seong Hwang, Juhan Kim, Hélène M. Courtois

The Astrophysical Journal

Computational Material Science 2026

High photovoltaic efficiency in bulk-stacked one-dimensional GeSe <sub>2</sub> van der Waals crystal

Seoung-Hun Kang, Youngjae Kim, Bo Gyu Jang, Sejoong Kim

Journal of Materials Chemistry A

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