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Here is a comparison of the parallel kernels launched under Mathematica under v9 and v10, on the same identical current 2014 R2-D2 Mac Pro ...

[ Update: Valerio has commented that the same issue arises on the Macbook Air.]

Under v9.01

$ProcessorCount 

12

Issuing:

 LaunchKernels[]

... launches 12 kernels, and actually uses them ... notice that the ParallelTable is 12 times the speed of Table[] for this construct:

In[5]:= Table[Pause[1]; f[i], {i, 12}] // AbsoluteTiming

Out[5]= {12.003106, {f1, f2, f[3], f[4], f[5], f[6], f[7], f[8], f[9], f[10], f[11], f[12]}}

In[6]:= ParallelTable[Pause[1]; f[i], {i, 12}] // AbsoluteTiming

Out[6]= {1.010648, {f1, f2, f[3], f[4], f[5], f[6], f[7], f[8], f[9], f[10], f[11], f[12]}}

So, to perform the same operation, the parallel result under v9 is 12 times the speed of the single kernel result.

Under v10 -- half my potential processing power has gone

$ProcessorCount

6

... down from 12 - even though I am running on the identical machine. Now, I know that my Mac Pro actually has 6 processors, and each runs 2 threads ... and under v9, that yielded 12 processor kernels for Mma 9 ... but under v10, it is only yielding 6 kernels ... ON THE SAME MACHINE. And this has real effects ... it effectively reduces by 50% the maximum potential power of my Mac:

 LaunchKernels[]

... launches 6 kernels (not 12 kernels as under v9).

Compare the performance:

 In[3]:= ParallelTable[Pause[1]; f[i], {i, 12}] // AbsoluteTiming

Out[3]= {2.009933, {f1, f2, f[3], f[4], f[5], f[6], f[7], f[8], f[9], f[10], f[11], f[12]}}

So, under the new v10, I am getting half the parallel performance here and half the kernels that I got under v9. Even more perplexing is that this worked fine in an earlier pre-release version of v10.

I am very confused. Anyone have any ideas how I can get my missing kernels back? Or why a decision may have been made to hobble the performance of the Mac Pro under v10?

Addendum

Just noticed that if I go to:

  • Evaluation Menu -> Parallel Kernel Configuration

... the automatic setting for:

  • Number of kernels to use: is set to: Automatic (which Mma sets to 6)

If I change this to:

  • Manual setting

and set it to 12 ... then it seems to use 12.

But I am still confused as to why, if Mathematica 10 can actually support 12 kernels on the machine, ... why would Wolfram set it to use only half of them by default, when v9 supported all of them by default?

Reply to Szabolcs: real-world test

Szabolcs suggests below that Mathematica may not practically use more kernels than physical cores, even if your processor supports virtual cores ... so there is no real difference. In reply, here is a quick timing test of a real-world application (kernel density estimation) from the mathStatica benchmarking test suite. The task is to plot 12 kernel density estimates, corresponding to 12 different bandwidths.

bandwidths = {.2, .35, .45, .55, .65, 1, 1.5, 2, 2.2, 2.5, 3, 3.2};

enter image description here

Here are the results running under:

  • v9 (default: 12 kernels): 3.38 seconds
  • v10 (default: 6 kernels): 9.53 seconds
  • v10 (manual overide to 12 kernels): 7.46 seconds

I don't know what has changed to cause such a performance hit under v10 ... but even so, that is not the point. The point is that the v10 default kernel setting fails to take advantage of the power of the Mac Pro ... and results in worse performance in a typical parallel-processing application.

More extensive real-world test:

Update: 1 August 2014

I have now had the opportunity to run the full mathStatica (primarily symbolic) benchmark suite under both:

  • the default v10 parallel setting (6 kernels)
  • the manual override v10 setting (12 kernels)

Here are the results:

enter image description here

The results fall into 2 categories:

  • For problems that have more than 6 separate components to them: ... For such problems, using 12 kernels is ALWAYS unambiguously faster, and significantly so.

  • For problems that have 6 or less separate components: ...For instance, Examples 7 and 9 can only be broken down into 2 symbolic components, so the benefits of parallelism max out with 2 kernels. In these cases, the 6 automatic kernels case is sometimes marginally faster than the 12 kernel case (presumably due to running overheads etc) ... but the difference is tiny, and essentially unnoticeable.

In summary: for problems that CAN benefit from more than 6 kernels, the default Mma 10 (automatic) setting of 6 kernels on a Mac Pro appears to be sub-optimal, and fails to take advantage of the full capability of the machine. This problem is new to v10, and does not occur under v9.

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    $\begingroup$ +1. This is a very well-researched post and even the example is pretty. That said, I would suggest to entertain the possibility that the cause of the performance hit is not directly due to the number of kernels launched or even the number of recognized cores in v10 but that it could be due to some other reason. It may also be worthwhile to track what MMA is doing in Activity Monitor. $\endgroup$ – heropup Jul 11 '14 at 14:53
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    $\begingroup$ Something else that is also worth asking is whether we see a similar performance hit between v9 and v10 on Windows. $\endgroup$ – heropup Jul 11 '14 at 16:36
  • $\begingroup$ What functions are run in the benchmark? $\endgroup$ – rcollyer Jul 11 '14 at 18:05
  • $\begingroup$ @rcollyer mathStatica's NPKDEPlot function uses ParallelTable[Plot[ Funky ] ] to produce each separate curve on a separate kernel, where Funky is a Compiled application of (Map of Total of some Ifs and Buts). $\endgroup$ – wolfies Jul 11 '14 at 18:28
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    $\begingroup$ I have the same issue on my MacBook Air: by default Mathematica 10 uses 2 instead of the 4 cores that Mathematica 9 would use. $\endgroup$ – Valerio Jul 31 '14 at 14:17
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Let's answer this to get it off the list of questions without answers.

Prelim

By default Mathematica uses a number of parallel kernels equal to the number of physical processor cores present in the machine. You can override this default in the settings under Edit > Preferences... > Parallel > Local Kernels (or Evaluation > Parallel Kernel Configuration ...)

You can also override the default in a single session/notebook by manually lauching the desired number of kernels with LaunchKernels[n] where n is the desired number of kernels.

In principle, there is no real limit to the number of parallel kernels that you can run other than the number of licenses available. (At some point you are bound to run out of memory though.)

Why does Mathematica default to the number of physical processors ?

The question asked by the OP amounts to why Mathematica defaults to using the number of physical processors rather than the number of logical cores. A key part of the answer lies in dimishing returns of using more than the number physical processors. This is because (depending on the hardware implementation) multiple logical cores share some or all resources of a physical core. This means that for straight-up numerical tasks, which can often reach very high efficient uses of a processor, will have limited benefit from using more than the physically available cores.

However, as shown by the benchmark in the OP's post, generally there will be some peformance benefit, and rarely any preformance disadvantage to using all available logical cores. So why not just always use the number of logical cores if that is the cases? Well, there are other considerations accept pure performance.

  1. Licences The first (and IMHO probably the most important) consideration is license availability. For each parallel kernel run, Mathematica needs a separate subkernel license. When using shared licenses at an institution (one of the more common setups), using double the number of licenses for little to no performance gain, may not be the most efficient use of licenses. Since users may not be aware of this, it is not a bad idea to have the default set to a conservative number.

  2. Overhead There is additional overhead to running more parallel kernels. Each parallel kernel is a full functional mathematica kernel that runs completely independently of the other kernels. In particular, there is no shared memory usage between kernels. Consequently, the kernels each duplicate a lot of memory usage. This can quickly run out of control when using many kernels. Since many users will not be aware of this, it is again smart to have the default number be conservative.

  3. In cases where the extra performance is really desired and the user knows what she is doing, it is easy enough to increase to number of kernels used.

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  • $\begingroup$ The answer begins: "The question asked by the OP amounts to why Mathematica defaults to using the number of physical processors rather than the number of logical cores" That characterisation seems plainly incorrect. The question is (a) why the default Mma setting changed from using the number of logical cores, to the number of physical processors, (b) in circumstances where this has a power hit on performance. By the logic expressed in the above answer, perhaps they should also restrict the number of kernels to be a subset of the number of physical processors (say half of them, or quarter)? $\endgroup$ – wolfies 2 days ago

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