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Articles: CPU

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Performance in Mathematical Calculations

We can see a similar picture in a popular Mathematica 5 package. However, this is not surprising at all, I should say. Computational tasks have always been a trump of AMD CPUs, even since the times of K7 solutions.

Besides Mathematica 5 test set, we also used for our testing purposes a popular Matlab 7.0 application with the benchmark built into it by default. This benchmark consists of 6 subtests. Here they are:

  • LU – Linear algebra operations on large real matrixes;
  • FFT – Fast Fourier Transformation;
  • ODE – Regular differential equations solution;
  • Sparse – Work with sparse matrices;
  • 2-D – 2D graphs processing;
  • 3-D – 3D graphs processing in OpenGL.

As a result of this benchmark we obtain a total performance score, which you can see on the graph below for all our testing participants.

Besides the overall score we can also show you the time it took our testing participants to complete each of the 6 subtests (of course, the lower numbers stand for better performance):

 

Pentium 4 560

Pentium 4 XE 3.4

Pentium 4 XE 3.46

Athlon 64 3800+

Athlon 64 4000+

Athlon 64 FX-55

LU

0.359

0.328

0.313

0.34

0.331

0.31

FFT

0.328

0.422

0.406

0.281

0.28

0.27

ODE

0.313

0.281

0.281

0.2

0.2

0.18

Sparse

0.484

0.422

0.406

0.451

0.441

0.421

2-D

0.438

0.422

0.407

0.28

0.271

0.261

3-D

0.219

0.219

0.219

0.2

0.19

0.17

As we see, AMD CPUs are beyond any competition in Matlab 7.0.

Performance during Software Development

Visual C++ is another application where AMD processors show their strengths. Although Intel Pentium 4 XE works here better than the regular Pentium 4 processors, they are still unable to catch up with Athlon 64.

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