I use a scientific computing benchmark Scimark2, which has 2 running modes: default and -large. I would like to share it with you. :=)
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=1000,nz=5000) 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=100000, nz=1000000) 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=1000,nz=5000) 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 –server jnt.scimark2.commandline -large Composite Score FFT (1048576) SOR (1000*1000) Monte Carlo Sparse matmult (N=100000, nz=1000000) 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 –O3 Composite Score FFT (1024) SOR (100*100) Monte Carlo Sparse matmult (N=1000, nz=5000) 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=100000, nz=1000000) 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 -- >From : [EMAIL PROTECTED] School of Fudan University
