Announcement

Collapse
No announcement yet.

R, Go & Other New Benchmarks Added

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • R, Go & Other New Benchmarks Added

    Phoronix: R, Go & Other New Benchmarks Added

    For those relying upon the Phoronix Test Suite for your open-source, automated benchmark needs on Linux, BSD, Solaris, and other operating systems, a number of new test profiles were recently made available...

    Phoronix, Linux Hardware Reviews, Linux hardware benchmarks, Linux server benchmarks, Linux benchmarking, Desktop Linux, Linux performance, Open Source graphics, Linux How To, Ubuntu benchmarks, Ubuntu hardware, Phoronix Test Suite

  • #2
    FYI, if you're going to use R as a benchmark, you *REALLY* need to make sure you have linked it against an optimized BLAS if your benchmark makes heavy use of matrices. The reference BLAS included with R is dog slow. Here's an R benchmark I ran on one of our Ivy Bridge Xeons comparing the stock BLAS to an optimized BLAS (in this case OpenBLAS). You can see several cases where an optimized BLAS is 20 times faster than the reference.



    OpenBLAS, GotoBlas, ATLAS, Intel MKL, and AMD ACML are good BLAS to choose from. For extra fun, you can use nVidia's cuBLAS and offload matrix operations to the GPU for even more speedup.

    If you don't replace the BLAS, you are effectively benchmarking the reference BLAS rather than the underlying hardware.

    Comment


    • #3
      Originally posted by MetricT View Post
      FYI, if you're going to use R as a benchmark, you *REALLY* need to make sure you have linked it against an optimized BLAS if your benchmark makes heavy use of matrices. The reference BLAS included with R is dog slow. Here's an R benchmark I ran on one of our Ivy Bridge Xeons comparing the stock BLAS to an optimized BLAS (in this case OpenBLAS). You can see several cases where an optimized BLAS is 20 times faster than the reference.



      OpenBLAS, GotoBlas, ATLAS, Intel MKL, and AMD ACML are good BLAS to choose from. For extra fun, you can use nVidia's cuBLAS and offload matrix operations to the GPU for even more speedup.

      If you don't replace the BLAS, you are effectively benchmarking the reference BLAS rather than the underlying hardware.
      The R benchmark is relying upon the system's R build, which is what they intend for being able to compare distribution's performance, etc.
      Michael Larabel
      https://www.michaellarabel.com/

      Comment

      Working...
      X