In this particular case, the performance would be doubled if the copying was eliminated. If that is done, along with an optimisation of the reduction operators, you would see at least a 10× improvement.
In my previous tests I even higher improvements (100× or so) for specific cases. Unfortunately my copy-on-write algorithm didn't actually work properly so it needed to be rolled back. The potential is there, however. Regards, Elias On 28 Aug 2015 20:46, "Mike Duvos" <[email protected]> wrote: > Hi Elias, > > That's very interesting. > > How fast do you think GNU APL could be made if the gratuitous array > copying were completely eliminated? I'm guessing it's always going to be > more of an educational tool than a competitor to expensive commercial APL > systems, which special case everything by type and rank, and do extensive > idiom recognition. > > Regards, > > Mike > > > > On Thu, Aug 27, 2015 at 11:54 PM, Elias Mårtenson <[email protected]> > wrote: > >> Thanks. I've run the test case with Callgrind now (it took over 3 hours). >> >> Like the previous test, we see that the reduce operator takes an >> excessive amount of time. Specifically, the call to Prefix::reduce_A_F_B() >> was called 67157 times and took 50% CPU time, of which 30% of the total >> time (i.e. 60% of the reduction) was doing the ⍴-reduction and 11.5% was >> doing a ↑-reduction. >> >> Out of the other half of processing time, 47.24% was spent doing >> 6210421621 calls to Cell::init(). This was mostly caused by 105552 calls to >> Value::clone(), creating what I believe is mostly unnecessary copies of the >> an array with an average of 6210421621/105552≈59000 elements. >> >> Regards, >> Elias >> >> >> On 28 August 2015 at 10:49, Mike Duvos <[email protected]> wrote: >> >>> Hi Elias, >>> >>> )IN PRIMESATF >>> >>> Should load PRIMESATF.atf. You need to have it in your workspaces >>> directory. You can see where that is with )LIBS >>> >>> Regards, >>> >>> Mike >>> >>> >>> >>> On Thu, Aug 27, 2015 at 7:45 PM, Elias Mårtenson <[email protected]> >>> wrote: >>> >>>> I have never used an ATF file, how do I load them? >>>> >>>> Generally, I just edit my APL files as plain .apl files. Makes the >>>> Emacs navigate-to-definition easy to use too. >>>> >>>> Regards, >>>> Elias >>>> >>>> On 28 August 2015 at 10:42, Mike Duvos <[email protected]> wrote: >>>> >>>>> Hi Elias, >>>>> >>>>> I am apparently still having problems with pasting Unicode dropping >>>>> less than or equal to and greater than or equal to. I've attached the >>>>> .atf >>>>> >>>>> Regards, >>>>> >>>>> Mike >>>>> >>>>> >>>>> >>>>> On Thu, Aug 27, 2015 at 7:37 PM, Elias Mårtenson <[email protected]> >>>>> wrote: >>>>> >>>>>> I wanted to test this thing myself, but I'm getting this error when >>>>>> testing it: >>>>>> >>>>>> * TIME 'PRIMES←SIEVE 100000'* >>>>>> DOMAIN ERROR >>>>>> SIEVE[3] →((⍴B)P←B⍳1)/L2 >>>>>> ^ ^ >>>>>> >>>>>> Regards, >>>>>> Elias >>>>>> >>>>>> On 28 August 2015 at 10:30, Mike Duvos <[email protected]> wrote: >>>>>> >>>>>>> Here is a function that finds all the Primes less than N, by >>>>>>> clearing bits in a boolean vector. >>>>>>> >>>>>>> )CLEAR >>>>>>> CLEAR WS >>>>>>> >>>>>>> ⎕IO←0 >>>>>>> >>>>>>> ∇ >>>>>>> [0] Z←SIEVE N;B;K;P >>>>>>> [1] Z←B←0 0,(¯2+N)⍴0=K←0 >>>>>>> [2] L1:→((⍴B)P←B⍳1)/L2 >>>>>>> [3] B←B∧(⍴B)⍴∼P↑1 >>>>>>> [4] Z[K]←P◊K←K+1 >>>>>>> [5] →L1 >>>>>>> [6] L2:Z←K↑Z >>>>>>> ∇ >>>>>>> >>>>>>> And our timing function, which we have used previously. >>>>>>> >>>>>>> ∇ >>>>>>> [0] TIME X;TS >>>>>>> [1] TS←⎕TS >>>>>>> [2] ⍎X >>>>>>> [3] (⍕(24 60 60 1000⊥¯4↑⎕TS-TS)÷1000),' Seconds.' >>>>>>> ∇ >>>>>>> >>>>>>> [IBM APL2] >>>>>>> >>>>>>> TIME 'PRIMES←SIEVE 100000' >>>>>>> 1.865 Seconds. >>>>>>> >>>>>>> [GNU APL] >>>>>>> >>>>>>> TIME 'PRIMES←SIEVE 100000' >>>>>>> 132.056 Seconds. >>>>>>> >>>>>>> 10 10⍴PRIMES >>>>>>> 2 3 5 7 11 13 17 19 23 29 >>>>>>> 31 37 41 43 47 53 59 61 67 71 >>>>>>> 73 79 83 89 97 101 103 107 109 113 >>>>>>> 127 131 137 139 149 151 157 163 167 173 >>>>>>> 179 181 191 193 197 199 211 223 227 229 >>>>>>> 233 239 241 251 257 263 269 271 277 281 >>>>>>> 283 293 307 311 313 317 331 337 347 349 >>>>>>> 353 359 367 373 379 383 389 397 401 409 >>>>>>> 419 421 431 433 439 443 449 457 461 463 >>>>>>> 467 479 487 491 499 503 509 521 523 541 >>>>>>> >>>>>>> 10 10 ⍴¯100↑PRIMES >>>>>>> 98897 98899 98909 98911 98927 98929 98939 98947 98953 98963 >>>>>>> 98981 98993 98999 99013 99017 99023 99041 99053 99079 99083 >>>>>>> 99089 99103 99109 99119 99131 99133 99137 99139 99149 99173 >>>>>>> 99181 99191 99223 99233 99241 99251 99257 99259 99277 99289 >>>>>>> 99317 99347 99349 99367 99371 99377 99391 99397 99401 99409 >>>>>>> 99431 99439 99469 99487 99497 99523 99527 99529 99551 99559 >>>>>>> 99563 99571 99577 99581 99607 99611 99623 99643 99661 99667 >>>>>>> 99679 99689 99707 99709 99713 99719 99721 99733 99761 99767 >>>>>>> 99787 99793 99809 99817 99823 99829 99833 99839 99859 99871 >>>>>>> 99877 99881 99901 99907 99923 99929 99961 99971 99989 99991 >>>>>>> >>>>>>> So on that function, GNU APL is 70.807 times as slow as APL2, so >>>>>>> obviously some performance issues remain. >>>>>>> >>>>>>> Function PD returns a list of the primes not greater than the square >>>>>>> root of a number which divide it evenly. If there are none, the number >>>>>>> is >>>>>>> prime, and it returns the number. FACTOR calls PD repeatedly to get the >>>>>>> full prime factorization of its argument. FFMT factors a list of >>>>>>> numbers, >>>>>>> and returns the numbers and their factorizations printed out neatly. >>>>>>> >>>>>>> ∇ >>>>>>> [0] Z←PD X;Q >>>>>>> [1] →(0≠⍴Z←(Q=⌊Q←X÷Z)/Z←(PRIMES⌈X⋆0.5)/PRIMES)/0 >>>>>>> [2] Z←,X >>>>>>> ∇ >>>>>>> >>>>>>> ∇ >>>>>>> [0] Z←FACTOR X;Q >>>>>>> [1] Z←'' >>>>>>> [2] L1:→(1=Q←⌊X÷×/Z)/L2 >>>>>>> [3] Z←Z,PD Q >>>>>>> [4] →L1 >>>>>>> [5] L2:Z←Z[⍋Z] >>>>>>> ∇ >>>>>>> >>>>>>> ∇ >>>>>>> [0] Z←FFMT X >>>>>>> [1] Z←FACTOR¨X←,X >>>>>>> [2] Z←(((⍴X),1)⍴X),Z >>>>>>> [3] Z←('Number' 'Prime Factorization'),[0]Z >>>>>>> [4] >>>>>>> ∇ >>>>>>> >>>>>>> Now lets get some random data, being careful to call Roll and not >>>>>>> the system-destroying Deal. >>>>>>> >>>>>>> 4 5⍴DATA←?20⍴¯1+2*31 >>>>>>> 1979327593 1319354819 771200257 1811210650 789012101 >>>>>>> 1029042612 152268513 20570707 832781767 898376923 >>>>>>> 1725231712 117387147 931909676 752862863 1800558041 >>>>>>> 736032325 151634070 731135336 1798144557 1223769030 >>>>>>> >>>>>>> FFMT DATA >>>>>>> Number Prime Factorization >>>>>>> 1979327593 14747 134219 >>>>>>> 1319354819 17 23 101 33409 >>>>>>> 771200257 17 17 1117 2389 >>>>>>> 1811210650 2 5 5 31 1168523 >>>>>>> 789012101 101 7812001 >>>>>>> 1029042612 2 2 3 3 13 29 75821 >>>>>>> 152268513 3 137 370483 >>>>>>> 20570707 20570707 >>>>>>> 832781767 47 199 269 331 >>>>>>> 898376923 898376923 >>>>>>> 1725231712 2 2 2 2 2 53913491 >>>>>>> 117387147 3 23 1701263 >>>>>>> 931909676 2 2 23 23 37 11903 >>>>>>> 752862863 752862863 >>>>>>> 1800558041 6841 263201 >>>>>>> 736032325 5 5 7 29 145031 >>>>>>> 151634070 2 3 3 5 7 233 1033 >>>>>>> 731135336 2 2 2 7247 12611 >>>>>>> 1798144557 3 11 1667 32687 >>>>>>> 1223769030 2 3 5 11 1471 2521 >>>>>>> >>>>>>> That ran in a reasonable amount of time. >>>>>>> >>>>>>> >>>>>>> >>>>>> >>>>> >>>> >>> >> >
