I ran the matrix multiply for M8 and M10. (M9 was uninstalled) M10 is marginally faster but repeating the tests a few times shows M8 can be better than the worst of M10.

Code attached. Chrome freezes every time I insert code so I'll show a sample picture.

I ran Timing and AbsoluteTiming, matrix sizes 1050 and 2050..

• Matrix 1050

10.0 for Microsoft Windows (64-bit) (June 29, 2014) Time = 0.374402

10.0 for Microsoft Windows (64-bit) (June 29, 2014) Time = 0.436803

8.0 for Microsoft Windows (64-bit) (October 7, 2011) Time = 0.406

8.0 for Microsoft Windows (64-bit) (October 7, 2011) Time = 0.468

• Matrix 1050

10.0 for Microsoft Windows (64-bit) (June 29, 2014) (Abs)Time = 0.456026

10.0 for Microsoft Windows (64-bit) (June 29, 2014) (Abs)Time = 0.493028

8.0 for Microsoft Windows (64-bit) (October 7, 2011) (Abs)Time = 0.5020287

8.0 for Microsoft Windows (64-bit) (October 7, 2011) (Abs)Time = 0.5210298

• Matrix 2050

10.0 for Microsoft Windows (64-bit) (June 29, 2014) Time = 2.714417

10.0 for Microsoft Windows (64-bit) (June 29, 2014) Time = 2.839218

8.0 for Microsoft Windows (64-bit) (October 7, 2011) Time = 2.855

8.0 for Microsoft Windows (64-bit) (October 7, 2011) Time = 2.949

• Matrix 2050

10.0 for Microsoft Windows (64-bit) (June 29, 2014) (Abs)Time = 2.938168

10.0 for Microsoft Windows (64-bit) (June 29, 2014) (Abs)Time = 3.058175

8.0 for Microsoft Windows (64-bit) (October 7, 2011) (Abs)Time = 3.1111780

8.0 for Microsoft Windows (64-bit) (October 7, 2011) (Abs)Time = 3.1811819

Attachments:

You can actually see the test code used in the benchmarking. The code for "Matrix Arithmetic" in Mathematica 10 is the following.

Module[{m}, 
 AbsoluteTiming[SeedRandom[1]; m = RandomReal[{}, {840, 840}]; 
  Do[(1.` + 0.5` m)^127, {50}];]]

On my laptop (MacBook Pro Late 2013, i5 2.4GHz), the output is {1.842847, Null} by Mathematica 10, while it is {1.115800, Null} by Mathematica 9. From run to run, the exact time changes, but it is certain that M10 runs slower than M9 for this code.

I have observed that the number of processing cores was detected to be 2 in M10, while it is 4 in M9. I changed the number of parallel kernels manually, but it didn't affect the output of the code above.

On the other hand, the "Matrix Multiplication"

Module[{m1, m2}, 
 AbsoluteTiming[SeedRandom[1]; m1 = RandomReal[{}, {1050, 1050}]; 
  m2 = RandomReal[{}, {1050, 1050}]; Do[m1.m2, {12}]]]

gives {0.581776, Null} by M10, and {1.421713, Null} by M9. Again, the exact time fluctuates a bit, but it is certain that M10 runs the multiplication faster than M9.

Indeed. Some of that is due to MKL getting in update (linear algebra, FFT, etc.) Do we know if the benchmarks included with v9 and v10 are identical though?

My general impression has been that most things are faster in v10, but some examples (like this one) show that some other things got slower. It would be nice to be able to track down what exactly is causing the slowdown.

I gave up with the Benchmarks some time ago. The tests are not run for the new release so you're always comparing apples to oranges.

Hi Marco,

Making a horizontal comparison with yourself is OK, but not a vertical comparison with other machines. It's deceptive to show my computer against any other model since no others have run M10. I took this up with support (going M8->M9) but met with apathy.

(benchmarks should be longer running anyway)

D.

Can you share the exact code you used to benchmark this?