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Date: Fri, 7 Mar 2008 20:39:36 +0800
From: "Simon Chow" <simon.harmony@gmail.com>
To: dev@harmony.apache.org
Subject: [general][evaluation] I did a performance evaluation using Scimark2
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I use a scientific computing benchmark Scimark2, which has 2 running modes:
default and -large.
I would like to share it with you. :=3D)


Platform:
Intel(R) Xeon(TM) CPU 2.80GHz*4.
arch: x86
os: Linux 2.6.18-8.el5xen;
Mem:4GB

Harmony

-Xms1500m -Xmx1500m -Xem:server jnt.scimark2.commandline

Composite Score

FFT

(1024)

SOR

(100*100)

Monte Carlo

Sparse matmult

(N=3D1000,nz=3D5000)

LU

(100*100)

193.99

223.91

366.62

28.42

184.19

166.83

194.05

222.20

370.43

28.04

183.16

166.42

193.67

223.05

369.72

28.61

181.29

165.70

193.41

221.29

371.28

27.69

182.04

164.74

194.34

222.48

371.00

28.17

183.32

166.75

-Xms1500m -Xmx1500m -Xem:server jnt.scimark2.commandline -large

Composite Score

FFT

(1048576)

SOR

(1000*1000)

Monte Carlo

Sparse matmult

(N=3D100000,

nz=3D1000000)

LU

(1000*1000)

179.31

37.93

359.34

27.18

289.51

182.60

178.31

35.84

359.34

28.08

288.78

179.50

179.35

37.19

258.66

28.08

289.43

183.40

179.02

35.63

360.01

27.14

289.92

182.40

179.80

37.44

360.01

27.25

290.08

184.21


Sun sdk1.5

-Xms1500m -Xmx1500m -server jnt.scimark2.commandline

Composite Score

FFT

(1024)

SOR

(100*100)

Monte Carlo

Sparse matmult

(N=3D1000,nz=3D5000)

LU

(100*100)

427.30

252.57

593.82

22.51

321.41

946.18

431.48

272.11

596.21

22.16

322.68

944.21

432.80

273.99

596.77

22.54

322.20

948.48

428.75

256.96

596.03

22.58

323.63

944.54

432.90

276.25

597.32

22.59

323.16

945.19


-Xms1500m -Xmx1500m =96server jnt.scimark2.commandline -large

Composite Score

FFT

(1048576)

SOR

(1000*1000)

Monte Carlo

Sparse matmult

(N=3D100000,

nz=3D1000000)

LU

(1000*1000)

243.25

36.42

553.20

34.72

381.71

265.18

278.28

37.74

576.72

39.89

369.94

367.11

266.89

37.42

575.21

41.22

368.48

312.11

271.74

37.63

577.16

39.48

371.28

333.17

269.53

37.49

574.99

41.12

368.88

325.20


gcj-4.0.2 =96O3

Composite Score

FFT

(1024)

SOR

(100*100)

Monte Carlo

Sparse matmult

(N=3D1000,

nz=3D5000)

LU

(100*100)

214.69

228.30

360.18

11.19

151.84

321.94

220.42

195.46

338.18

7.96

276.17

284.33

254.33

214.59

360.18

11.58

277.23

408.05

179.55

184.54

355.71

6.71

143.22

227.56

233.90

215.02

360.58

11.57

276.41

305.92

-large

Composite Score

FFT

(1048576)

SOR

(1000*1000)

Monte Carlo

Sparse matmult

(N=3D100000,

nz=3D1000000)

LU

(1000*1000)

192.24

29.62

348.23

11.55

222.95

348.86

177.07

35.24

322.72

8.16

232.94

286.25

174.29

35.02

331.95

9.75

249.63

245.09

196.79

27.28

347.29

11.50

255.12

342.76

179.69

37.69

349.346

10.69

176.19

324.57


--=20
>From : Simon.Chow@Software School of Fudan University

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