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.

2,970
Running Jobs
499
Waiting Jobs
13,308
Total Cores
360
Compute Nodes

Latest News

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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
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 25.0%
2 nodes up
80 / 320
10 running
24 pending

GRAMMAR

113 nodes / 7,232 cores

Healthy
CPU Usage 99.9%
112 nodes up
7,226 / 7,232
45 running
56 pending

LEXICON

12 nodes / 288 cores

Healthy
CPU Usage 42.4%
3 nodes up
122 / 288
32 running
0 pending

SYNTAX

13 nodes / 832 cores

Healthy
CPU Usage 42.0%
1 nodes up
349 / 832
67 running
21 pending

BAEKDU

95 nodes / 1,900 cores

Warning
CPU Usage 97.9%
94 / 1 down
1,860 / 1,900
1380 running
377 pending

DNA

53 nodes / 1,080 cores

Warning
CPU Usage 78.3%
45 nodes up
846 / 1,080
176 running
0 pending

RNA

69 nodes / 1,656 cores

Healthy
CPU Usage 100.0%
69 nodes up
1,656 / 1,656
1260 running
21 pending
Publications

Recent Research

Latest publications from CAC researchers

Particle Physics 2026

Signatures of Long-Lived Heavy Neutral Leptons from Neutrinophilic Charged Higgs Pair Production at the LHC

Nobuchika Okada, Prasenjit Sanyal, Ravindra Kumar Verma

Particle Physics 2026

Dark Photon mediated Inelastic Dark Matter in Cosmology, Astrophysics and Colliders

Abhishek Roy, Prasenjit Sanyal, Stefano Scopel

AI 2026

Co-occurring Associated REtained concepts in Diffusion Unlearning

Miso Kim, Georu Lee, Yunji Kim, Hoki Kim, Jinseong Park, Woojin Lee

International Conference on Learning Representations