Authorized and redacted by Ocean University of China on 4th July, 2017 as an example for ASC

Presentation of

ASC17

Final Competition

Ocean University of China

Team Advisor: Professor Shen Biao

2017-4-28

3

Team introduction

Cluster building

Application optimization

Summary

INTRODUCTION

01

team leader

Marine Science

Liao

JiawenMarine Science

Bai

Zongbao

Atmospheric

Science

Sun

Xiaoshan

Atmospheric

Science

Zhang

JinpeiMarine Science

Yuan Man

Cluster building

02

8

Our cluster

CPU

GPU

CENTOS7.3NVIDIA TESLA P100

9

Cluster building

KNL

GPU

GPU

Performance Optimization of Final Competition Applications

03

11

Performance optimization of HPL

the result we submitted was 9.15TFLOPSthe newer result is 20.14TFLOPS

12

Performance optimization of HPCG

• There are two sections can be altered: Time and Matrix Size.

• Changing the matrix size can optimize performance.

HPCG.dat

• We should run HPCG on many codes with multiple processes.

• When using ordering “mpirun “ we need to write a hostfile to note the code name.

Hostfile

• sudo nvidia-smi -acp 0

• # allow normal user to set GPU clocks

• sudo nvidia-smi -ac 715,1328

• # set max bost clk for P100 PCIe

Boost clocks

Some others we haven’t try : 1, the function OptimizeProblem() OptimezeData2, to change ComputeSPMV and ComputeSYMGS

13

Traffic prediction based paddle

percentage

DREAM

REALITY

difficult in installing many thoughts lack of practice

14

MASNUM

Step 1:Find hotspotproagat.inc implstch.inc

Step 2:Using OpenACC accelerate on 64 CPEs

Step 3:Other optimizations arraycompiler options vectorizaton

15

16

17

18

19

0

2000

4000

6000

8000

10000

12000

14000

openACC vectorization openACC vectorization openaACC vectorization

propagat implsch total

Tim

e(s

)

MASNUM Optimization Results

2CGs 4CGs 256CGs

SUMMARY

New field, New learning, New challenge !

Thank you for your

attention!