Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

1

OUTLINE

1.1

Supercomputer System

In School year 2022 (SY 2022), the ISSP supercomputer center provided users
with System B - Dell PowerEdge C6525/R940 system named “ohtaka” and System C - HPE Apollo 2000 Gen10 Plus/HPE Apollo 6500 Gen10 Plus system named“kugui”. System B is a massively-parallel supercomputer with two types of compute nodes: 8 “Fat” nodes and 1680 “CPU” nodes. “Fat” nodes are each comprisedof four Intel Xeon Platinum 8280 CPUs (28 cores/CPU) and 3 TB of memory per
node. “CPU” nodes have two AMD EPYC 7702 CPUs (64 cores/CPU) and 256
GB of memory per node. System B achieves about 6.881 PFLOPS in theoreticalpeak performance with high power eﬃciency. The subsystem comprised of only
CPU nodes ranks 87st in the Nov. 2020 Top 500 List, which is a ranking based
on total performance measured by the HPL benchmark. The compute nodes communicate to each other through HDR100 Inﬁniband and are connected in fat tree
topology. SY 2022 was the third year of the operation of the current System B. In
June 2022, “kugui” was introduced as System C, which will be operated for the
next six years. System C is a massively-parallel supercomputer with two typesof compute nodes: 128 “CPU” nodes and 8 “ACC” nodes. “CPU” nodes areeach comprised of two AMD EPYC 7763 CPUs (64 cores/CPU) and 256 GB ofmemory. The compute nodes communicate to each other through HDR200 Inﬁniband and are connected in fat tree topology. “ACC” nodes are each comprised of
one AMD EPYC 7763 CPUs (64 cores/CPU), four NVIDIA A100 40GB for HGXGPUs and 256 GB of memory. System C achieves 973 TFLOPS in theoreticalpeak performance. System C entered oﬃcial operation in June 14th, 2022. Trial
operation of System C continued until July 18th, 2022. SY 2022 was the ﬁrst yearof the operation of the current System C. For further details, please contact ISSP
Supercomputer Center (SCC-ISSP).
[Correspondence: center@issp.u-tokyo.ac.jp]

1.2

Project Proposals

The ISSP supercomputer system provides computation resources for scientists
working on condensed matter sciences in Japan. All scientiﬁc staﬀ members (including post-docs) at universities or public research institutes in Japan can submit
proposals for projects related to research activities on materials and condensed
matter sciences. These proposals are peer-reviewed by the Advisory Committee
members (see Sec. 1.3), and then the computation resources are allocated basedon the review reports. The leader of an approved project can set up user accounts
for collaborators. Other types of scientists, including graduate students, may also
be added. Proposal submissions, peer-review processes, and user registration are
all managed via a web system.
The computation resources are distributed in a unit called “point”, determined
as a function of available CPU utilization time and consumed disk resources. There1

Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Figure 1: Supercomputer System at the SCC-ISSP

were calls for six classes of research projects in SY 2022. The number of projects
and the total number of points that were applied for and approved in this school
year are listed in Table 1.
• Class A is for trial use by new users; proposals for Class A projects are
accepted throughout the year.
• Proposals for projects in Classes B (small), C (mid-size), E (large-scale), andS (exceptional) can be submitted twice a year. Approved projects in Classes
A, B, C, and E continue to the end of the school year.
• In Class D, projects can be proposed on rapidly-developing studies that needto perform urgent and relatively large calculations. An approved projectcontinues for 6 months from its approval.
• Class S is for projects that are considered extremely important for the ﬁeldof condensed matter physics and requires extremely large-scale computation.
The project may be carried out either by one research group or cooperatively
by several investigators at diﬀerent institutions. A project of this class should
be applied with at least 10,000 points; there is no maximum. We requiregroup leaders applying for Class S to give a presentation on the proposal to
the Steering Committee of the SCC-ISSP. Class S projects are carried out
within one year from its approval.
• Project leaders can apply for points so that the points for each system do
not exceed the maximum point shown in this table.

2

Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 1: Classes of research projects in SY 2022. Total points listed in this table
are rounded. In Class D, we collect information about the projects ended in eachsemester.
Class

A
B
C
D
E
S
SCCMS
Total

Maximum
PointsSys–B Sys–C
100
50
800
100
8k
500
10k
500
24k
1.5k
–
–

Application

# of
Proj.

any time
twice a year
twice a year
any time
twice a year
twice a year

28
94
176
6
13
0
20
337

Total points
AppliedApproved
Sys–B Sys–C Sys–B Sys–C
2.8k
1.4k
2.8k
1.4k
65.9k
6.7k
38.6k
5.5k
1092.9k 47.4k 566.8k 35.7k
28.5k
1.2k
23.0k
1.0k
273.0k 18.0k 185.5k 14.4k
0
0
0
0
5.2k
52.3k
5.2k
52.3k
1515.4k 79.9k 869.0k 63.2k

In addition, from SY 2016, ISSP Supercomputer has been providing 20% of
its computational resources for Supercomputing Consortium for Computational
Materials Science (SCCMS), which aims at advancing parallel computations incondensed matter, molecular, and materials sciences on the 10-PFlops K Computer
and the exascale post-K project. From SY 2020, up to 10% of the computational
resources have been provided for SCCMS. Computational resources have also beenallotted to Computational Materials Design (CMD) workshops, as well as CCMS
hands-on workshops.

1.3

Committees

In order to fairly manage the projects and to smoothly determine the system
operation policies, the Materials Design and Characterization Laboratory (MDCL)of the ISSP has organized the Steering Committee of the MDCL and the Steering
Committee of the SCC-ISSP, under which the Supercomputer Project Advisory
Committee (SPAC) is formed to review proposals. The members of the committees
in SY 2022 were as follows:

Steering Committee of the MDCLKAWASHIMA, Naoki
HIROI, Zenji
OZAKI, Taisuke
NOGUCHI, Hiroshi
UWATOKO, Yoshiya
OKAMOTO, Yoshihiko
SUGINO, Osamu
KUBO, Momoji

ISSP (Chair person)
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
Tohoku Univ.

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Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

HUKUSHIMA, Koji
HONDA, Fuminori
SHIMAKAWA, Yuichi
MOTOME, Yukitoshi
HOSHI, Takeo
ISHIWATA, Shintaro
HASEGAWA, Masashi
NAKATSUJI, Satoru

Univ. of Tokyo
Kyushu Univ.
Kyoto Univ.
Univ. of Tokyo
Tottori Univ.
Osaka Univ.
Nagoya Univ.
ISSP

Steering Committee of the SCC-ISSP
KAWASHIMA, Naoki
NOGUCHI, Hiroshi
OZAKI, Taisuke
SUGINO, Osamu
TSUNETSUGU, Hirokazu
KATO, Takeo
KIMURA, Takashi
MORITA, Satoshi
FUKUDA, Masahiro
IDO, Kota
KAWAMURA, Mitsuaki
NAKAJIMA, Kengo
OTSUKI, Junya
MOTOME, Yukitoshi
ONO, Tomoya
TODO, Synge
KUBO, Momoji
OBA, Fumiyasu
WATANABE, Hiroshi
HUKUSHIMA, Koji
KITAO, Akio
HAMADA, Ikutaro
YOSHIMI, Kazuyoshi
YATA, Hiroyuki
FUKUDA, Takaki

ISSP (Chair person)
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
ISSP
Univ. of Tokyo
Okayama Univ.
Univ. of Tokyo
Kobe Univ.
Univ. of Tokyo
Tohoku Univ.
Tokyo Tech.
Keio Univ.
Univ. of Tokyo
Tokyo Tech.
Osaka Univ.
ISSP
ISSP
ISSP

Supercomputer Project Advisory Committee
KAWASHIMA, Naoki
OZAKI, Taisuke
NOGUCHI, Hiroshi
SUGINO, Osamu
TSUNETSUGU, Hirokazu
KIMURA, Takashi

ISSP (Chair person)
ISSP
ISSP
ISSP
ISSP
ISSP

4

Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

KATO, Takeo
MORITA, Satoshi
FUKUDA, Masahiro
IDO, Kota
KAWAMURA, Mitsuaki
NAKAJIMA, Kengo
MOTOME, Yukitoshi
TODO, Synge
KUBO, Momoji
OBA, Fumiyasu
WATANABE, Hiroshi
HUKUSHIMA, Koji
ONO, Tomoya
OTSUKI, Junya
KITAO, Akio
HAMADA, Ikutaro
IKUHARA, Yuichi
SHIBATA, Naokazu
AKAGI, Kazuto
YANASE, Yoichi
HATSUGAI, Yasuhiro
OKADA, Susumu
KOBAYASHI, Nobuhiko
NAKAYAMA, Takashi
HOTTA, Takashi
MATSUKAWA, Hiroshi
YAMAUCHI, Jun
HAGITA, Katsumi
KONTANI, Hiroshi
SAITO, Mineo
YUKAWA, Satoshi
SUGA, Seiichiro
YASUDA, Chitoshi
KIM, Kang
MORIKAWA, Yoshitada
KOGA, Akihisa
SHIMOJO, Fuyuki
TAKETSUGU, Tetsuya
TSURUTA, Kenji
HAMAGUCHI, Satoshi
NISHIDATE, Kazume
KAGESHIMA, Hiroyuki
ISHII, Fumiyuki
TATETSU, Yasutomi
YANAGISAWA, Susumu

ISSP
ISSP
ISSP
ISSP
ISSP
Univ. of Tokyo
Univ. of Tokyo
Univ. of Tokyo
Tohoku Univ.
Tokyo Tech.
Keio Univ.
Univ. of Tokyo
Kobe Univ.
Okayama Univ.
Tokyo Tech.
Osaka Univ.
Univ. of Tokyo
Tohoku Univ.
Tohoku Univ.
Kyoto Univ.
Univ. of Tsukuba
Univ. of Tsukuba
Univ. of Tsukuba
Chiba Univ.
Tokyo Metropolitan Univ.
Aoyama Gakuin Univ.
Keio Univ.
National Defense Academy
Nagoya Univ.
Kanazawa Univ.
Osaka Univ.
Univ. of Hyogo
Univ. of the Ryukyus
Osaka Univ.
Osaka Univ.
Tokyo Tech.
Kumamoto Univ.
Hokkaido Univ.
Okayama Univ.
Osaka Univ.
Iwate Univ.
Shimane Univ.
Kanazawa Univ.
Meio Univ.
Univ. of the Ryukyus

5Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of TokyoSHUDO, Ken-ichi
Yokohama Natl. Univ.
OHMURA, Satoshi
Hiroshima Inst. Tech.
NOGUCHI, Yoshifumi
Shizuoka Univ.
NAKAMURA, Kazuma
Kyushu Inst. Tech.
GOHDA, Yoshihiro
Tokyo Tech.
RAEBIGER, Hannes
Yokohama Natl. Univ.
KAWARABAYASHI, Tohru Toho Univ.
KATO, Yusuke
Univ. of Tokyo
NASU, Joji
Tohoku Univ.
HOTTA, Chisa
Univ. of Tokyo
ISOBE, Masaharu
Nagoya Inst. Tech.
HARADA, Ryuhei
Univ. of Tsukuba
TANAKA, Shu
Keio Univ.
KOBAYASHI, Kazuaki
NIMS
TATEYAMA, Yoshitaka
NIMS
TAMURA, Ryo
NIMS
TADA, Tomofumi
Kyushu Univ.
HATANO, Naomichi
Univ. of TokyoYOSHINO, Hajime
Osaka Univ.
OKUMURA, Hisashi
NINS-ExCELLSHOSHI, Takeo
Tottori Univ.
TSUNEYUKI, Shinji
Univ. of TokyoSUZUKI, Takafumi
Univ. of Hyogo
YOSHIMOTO, Yoshihide Univ. of Tokyo
TOHYAMA, Takami
Tokyo Univ. of Sci.
ARITA, Ryotaro
Univ. of Tokyo
OGATA, Masao
Univ. of TokyoWATANABE, Satoshi
Univ. of Tokyo
YABANA, Kazuhiro
Univ. of Tsukuba
FURUKAWA, Nobuo
Aoyama Gakuin Univ.
KUROKI, Kazuhiko
Osaka Univ.
TANAKA, Yukio
Nagoya Univ.
KUSAKABE, Koichi
Univ. of Hyogo
SAKAI, Toru
Univ. of Hyogo
ISHIBASHI, ShojiAISTOTANI, Minoru
Univ. of Tsukuba
TOMITA, Yusuke
Shibaura Inst. Tech.
SHIRAISHI, Kenji
Nagoya Univ.
OGUCHI, Tamio
Osaka Univ.
KAWAKATSU, Toshihiro Tohoku Univ.
OTSUKI, Tomi
Sophia Univ.
ODA, Tatsuki
Kanazawa Univ.
ARAI, Noriyoshi
Keio Univ.
UNEYAMA, Takashi
Nagoya Univ.

6

Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

1.4

Staﬀ

The following staﬀ members of the SCC-ISSP usually administrate the ISSP Supercomputer.
KAWASHIMA, Naoki
NOGUCHI, Hiroshi
OZAKI, Taisuke
SUGINO, Osamu
IDO, Kota
FUKUDA, Masahiro
KAWAMURA, Mitsuaki
MORITA, Satoshi
NAKANO, Hiroyoshi
YOSHIMI, Kazuyoshi
AOYAMA, Tatsumi
MOTOYAMA, Yuichi
YATA, Hiroyuki
FUKUDA, Takaki
ARAKI, Shigeyuki

Professor (Chair person)
Associate Professor
Professor
Professor
Research Associate
Research Associate
Research Associate
Research Associate
Research Associate
Project Researcher
Project Researcher
Technical Specialist
Technical Specialist
Technical Specialist
Project Academic Specialist

2

STATISTICS (SCHOOL YEAR 2022)

2.1

System and User Statistics

In the following, we present statistics for operation time taken in the period from
April 1st 2022 to April 3rd 2023 (SY 2022). In Table 2, we show general statisticsof the supercomputer system in SY 2022. The total numbers of compute nodes in
System B “ohtaka” and System C “kugui” are 1688 and 136, respectively. Consumed disk points amount to about a few percent of the total consumed points inboth System B and System C.
In Fig. 2, availabilities, utilization rates, and consumed points in Systems B
and C are plotted for each month. Throughout the school year, the availability
and the utilization rates were very high : the availability and the utilization rates
exceed about 90% and 80% throughout most of the year, respectively.
The user statistics are shown in Fig. 3. The horizontal axis shows the rank of theuser/group arranged in the descending order of the execution time (hour×nodes).
The execution time of the user/group of the ﬁrst rank is the longest. The verticalaxis shows the sum of the execution time up to the rank. From the saturation
points of the graphs, the numbers of “active” users of Systems B and C are around
400 and 100, respectively. The maximum ranks in the graphs correspond to thenumber of the users/groups that submitted at least one job.

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Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 2: Overall statistics of SY 2022

total service time (×103 node·hours)
number of executed jobs
total consumed points (×103 point)
CPU points (×103 point)
disk points (×103 point)
total exec. time (×103 node·hours)
availability
utilization rate

2.2

System B
ohtaka14420
476439
502
489
13
13293
96.60%
92.3%

System C
kugui
976
1088681818
1790
97.38%
80.98%

Queue and Job Statistics

Queue structures of Systems B and C in SY 2022 are shown in Tables 3 and 4,
respectively. In System B “ohtaka”, users can choose from two types of computenodes; jobs submitted to queues with “cpu” and “fat” at the end of their queue
names are submitted to CPU and Fat nodes, respectively. In System C, there are
two types of compute nodes: CPU and ACC nodes. Jobs submitted to queues with“cpu” and “acc” at the end of their queue names are submitted to CPU and ACC
nodes, respectively, If users submit a job to queues with “accs” at the end of theirqueue names, the job runs in the ACC node shared by other jobs of “accs“ queues.
See Sec. 1.1 for a description of each type of compute node. The user then has
to choose the queue according to the number of nodes to use and the duration of
their calculation jobs. Queue names starting with “F” are for jobs taking 24 hours
or less, while those starting with “L” can run much longer up to 120 hours. Morenodes are allotted to “F” queues in order to maximize the turnaround time of user
jobs. The queue names starting with “i” are used for interactive debugging of user
programs and the elapsed time limit is 30 minutes. The number following “F”,
“L”, or “i” correspond to the number of nodes that can be used by one user job.
Although we do not mention here in detail, to promote utilization of the massively
parallel supercomputer, background queues (queue name starting with “B”) for
Systems B and C which charge no points for the jobs have also been open.
To prevent overuse of the storage, points are charged also for usage of disk
quota in the three systems, as shown in Table 5. Disk points are revised often for
optimal usage of the resources by examining usage tendencies each year.
The number of jobs, average waiting time, and total execution time in eachqueue are shown in Tables 6 and 7. In Systems B and C, a large portion of jobs
have been executed in “F” queues. The largest amount of the execution time has
been consumed in the large-scale “F72cpu” and “F16cpu” queues for Systems B
and C, respectively. However, substantial number of jobs were run in every queue,
suggesting that a wide variety of user needs are met by this queuing scheme. In

8Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

System B

System C
Availability, Utilization [%]

100

90
80
Availability
Utilization

70

80
60

60

20

80

6

60
40
20
0
04

05

06

07

08

09 10
Month

11

12

01

02

4

2

0
04

03

Availability
Utilization

40

Point consumption[×103 points]

Point consumption[×103 points]

Availability, Utilization [%]

100

05

06

07

08

09 10
Month

11

12

01

02

03

Figure 2: Availabilities, utilization rates and point consumptions of each month
during SY 2022.

System B

System C
0.8

12
0.7
10

106 node·hours

106 node·hours

0.6
8

6

0.5

0.4
4
0.3
user exec. timegroup exec. time2

user exec. timegroup exec. time
0.2

0

100

200 300 400 500
Rank of user/group

600

700

0

20

40

60
80
100
Rank of user/group

120

140

Figure 3: User statistics. The horizontal axis shows the rank of the user/grouparranged in the descending order of the execution time (hour×nodes). The verticalaxis shows the sum of the execution time up to the rank.

9Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 3: Queue structures of System B in SY 2022

queue
name
F1cpu
L1cpu
F4cpu
L4cpu
F16cpuL16cpuF36cpuL36cpuF72cpuL72cpuF144cpu
L144cpu
i8cpu
F2fat
L2fat
i1fat

Elapsed time
limit (hr)
24
120
24
120
24
120
24
120
24
120
24
120
0.5
24
120
0.5

System B, ohtaka# of nodes # of nodes/job/queue
1
600
1
300
2–4
216
2–4
108
5–16
288
5–16
144
17–36
72
17–36
36
72
576
72
288
144
432
144
144
1–8
72
1–2
7
1–2
3
1
1

Memorylimit (GB)230/node
230/node
230/node
230/node
230/node
230/node
230/node
230/node
230/node
230/node
230/node
230/node
230/node
2900/node2900/node2900/nodejob points/(node·day)
1
1
1
1
1
1
1
1
1
1
1
1
1
4
4
4

most of these queues, the queue settings meet the user’s tendencies in that thewaiting times are on the order of the elapsed-time limit.

2.3

Project for Advancement of Software Usability in Materials Science

From School Year 2015, the supercomputer center (SCC) has started “Project
for advancement of software usability in materials science”. In this project, forenhancing the usability of the supercomputer system in ISSP, we perform some
software-advancement activity such as implementing a new function to an existing
code, releasing a private code on Web, writing manuals. Target programs are
publicly oﬀered in December and selected in the review by the Steering Committeeof SCC. The projects are carried out by the software development team composedof three members in ISSP. In SY 2022, three projects were selected as listed inTable 8.

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Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 4: Queue structures of System C in SY 2022

queue
name
i2cpu
F1cpu
L1cpu
F4cpu
L4cpu
F16cpuL16cpuF1accsL1accsi1accs
F2acc
L2acc
∗

Elapsed time
limit (hr)
0.5
24
120
24
120
24
120
24
120
0.5
24
120

System C, kugui# of nodes # of nodes/job/queue
1–2
8
1
120
1
60
2–4
32
2–4
16
5–16
64
5–16
32
1
3
1
1
1
1
1–2
4
1–2
2

Memorylimit (GB)240/node
240/node
240/node
240/node
240/node
240/node
240/node
60×NGPU
60×NGPU
60×NGPU
240/node
240/node

job points/(node·day)
1
1
1
1
1
1
1
1
1
1
1
1

NGPU in ACC queues denotes the number of occupied GPUs.

2.4

ISSP Data Repository

From School Year 2021, the supercomputer center (SCC) has started to operate
ISSP Data Repository (ISSP-DR) for accumulating and utilizing research data inmaterials science. GitLab is used as the data management system, and a portalsite is provided as a data registration and search system for the registered data.
By using ISSP-DR, it is possible to store and publish research data used in papers and datasets useful in the ﬁeld of condensed matter science. Users of ISSP
Supercomputer are welcome to apply for and use ISSP-DR.

Acknowledgments
The staﬀs would like to thank Prof. Takafumi Suzuki (now at University of Hyogo)
for developing WWW-based system (SCM: SuperComputer Management System)
for management of project proposals, peer-review reports by the SPAC committee,
and user accounts. We also thank Ms. Reiko Iwafune for creating and maintaining
a new WWW page of the ISSP Supercomputer Center.

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Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 5: Disk points of Systems B and C

System B ohtaka
System C kugui

∗
∗

/home
/work
/home
/work

point/day
0.001 × θ(q − 600)
0.0001 × θ(q − 6000)
0.001 × θ(q − 150)
0.0001 × θ(q − 1500)

q is denoted in unit of GB.
θ(x) is equal to the Heaviside step function H(x) multiplied by x, i.e., xH(x).

Table 6: Number of jobs, average waiting time, total execution time, and average
number of used nodes per job in each queue of System B.

queue# of Jobs

F1cpu
L1cpu
F4cpu
L4cpu
F16cpuL16cpuF36cpuL36cpuF72cpuL72cpuF144cpu
L144cpu
i8cpu
F2fat
L2fat
i1fat

160175
4726
77846
4400
44145
1990
1179
102
8509
101
3422
114
143548
5698
508
1003

System B, ohtaka
Waiting Time
Exec. Time # of nodes
3(hour) (×10 node·hour)
31.64
290.451.00
63.51
207.391.00
26.01
1203.73
2.82
58.22
493.382.89
12.77
1586.639.23
58.49
661.299.29
52.79
311.3528.75
69.71
115.5022.46
19.76
3711.88
72.00
40.95
270.2772.00
18.28
2090.58
144.00257.46581.50144.00
0.09
95.25
4.28
206.85
36.39
1.24
60.36
17.51
1.21
0.35
0.09
1.00

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Activity Report 2022 / Supercomputer Center, Institute for Solid State Physics, The University of Tokyo

Table 7: Number of jobs, average waiting time, total execution time, and average
number of used nodes per job in each queue of System C.

queue# of Jobs

i2cpu
F1cpu
L1cpu
F4cpu
L4cpu
F16cpuL16cpui1accsF1accsL1accs
F2acc
L2acc

6417
32465
862
3780
374
1837
83
3794
2946
418
3225
72

System C, kugui
Waiting Time
Exec. Time # of nodes
3(hour) (×10 node·hour)
0.39
0.84
1.30
3.03
92.09
1.00
24.34
31.42
1.00
6.13
80.44
3.31
35.69
45.22
3.44
12.60
134.95
13.53
16.11
23.83
12.24
0.00
0.20
1.00
2.88
10.41
1.00
1.16
1.57
1.00
5.96
4.16
1.04
2.05
0.63
1.29

Table 8: List of Project for advancement of software usability in materials science
for SY 2022.
Project Proposer
Shusuke Kasamatsu
Yamagata University
Akito Kobayashi
Nagoya University

Project Name
Coupling of extended ensemble sampling
and ﬁrst-principles solvers
Advancement of eﬀective model solvers
toward high-throughput calculations― Wavenumber based mean-ﬁeld approximation
and random phase approximation

13