la, 2008-05-17 kello 00:39 +0900, David Cournapeau kirjoitti:
On Sat, May 17, 2008 at 12:00 AM, Anne Archibald
wrote: There are four benchmarks: add, multiply, dot, and solve. dot and solve use BLAS, and for them numpy ruby and octave are comparable. Add and multiply are much slower in numpy, but they are implemented in numpy itself.
The benchmark was done in 2005, and we do not know how it was done (no source). I don't know anything about ruby (that's my first ruby "program") but: [clip]
The benchmark sources are in Narray's source directory. I took a look and my conclusion is that the benchmark is simply flawed: for Ruby, only user time is counted, while for Python, both user and system times are counted. The code uses Python's time.clock() which according to the documentation returns the CPU time (apparently user + system). On the Ruby side it uses Process.times.utime which is the elapsed user time. Running the original tests as they are in NArray 0.5.9 yields (I took representative ones from several runs. Eyeballing, the std between runs appeared of the order of 0.1...0.2s): ### Numeric 24.2 (24.2-8ubuntu2) ### Narray 0.5.9 (0.5.9-2) ### numpy 1.0.4 (1:1.0.4-6ubuntu3) ### ### All of these from Ubuntu 8.04 packages. $ time ruby mul.rb a = NArray.float(1000000): [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, ... ] b = NArray.float(1000000): [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, ... ] calculating c = a*b ... Time: 3.05 sec real 0m5.039s user 0m3.116s sys 0m1.564s Obviously, the reported time here is the user time only! $ time python mul.py # the old Numeric a.typecode: d , a.shape: (1000000,) b.typecode: d , b.shape: (1000000,) calculating c = a*b ... Time: 6.020 sec real 0m6.999s user 0m4.308s sys 0m2.164s Whereas here it must be the sum of the user and system times! Running tests for numpy and fixed time counting for Ruby: $ time python mul_numpy.py # the new numpy a.typecode: float64 , a.shape: (1000000,) b.typecode: float64 , b.shape: (1000000,) calculating c = a*b ... Time: 4.580 sec real 0m5.774s user 0m3.352s sys 0m1.996s $ time ruby mul_correct.rb # using T.times.utime + T.times.stime a = NArray.float(1000000): [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, ... ] b = NArray.float(1000000): [ 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, ... ] calculating c = a*b ... Time: 4.57 sec real 0m5.045s user 0m3.060s sys 0m1.620s I think this shows that there is no discernible difference between the performance of numpy and Ruby's NArray. Even though the performance of numpy and NArray is indeed better than that of Numeric, the difference is not as large as the original benchmark led to believe. Benchmark files attached, in case someone wants to contest my analysis. -- Pauli Virtanen