Reply to Bill,
Exactly. That's why I haven't spent too much time benchmarking it.
It would be quite surprising if something I wrote in D outperformed
the ATLAS SSE3 optimized BLAS implementation. (Though It would not be
so surprising if something Don wrote managed to outperform it. :-) )
--bb
Bill Baxter:
> I do find all your benchmark postings interesting.
Most of them are buggy, in the beginning... The main problem is that they often
do nothing real, so there's no practical result to test. In the future I'll add
better tests to avoid the most silly errors of mine.
> Anyway I gave
Tom S wrote:
Andrei Alexandrescu wrote:
Tom S wrote:
Don wrote:
bearophile wrote:
While writing code that works on matrices I have found something
curious...
Here's what I think is going on. AFAIK, D hasn't got any special
code for initializing jagged arrays. So
auto A = new doubl
On Sun, Nov 23, 2008 at 6:15 PM, bearophile <[EMAIL PROTECTED]> wrote:
> Bill Baxter:
>> Exactly. That's why I haven't spent too much time benchmarking it.
>> It would be quite surprising if something I wrote in D outperformed
>> the ATLAS SSE3 optimized BLAS implementation.
>
> Performing many be
Andrei Alexandrescu wrote:
Tom S wrote:
Don wrote:
bearophile wrote:
While writing code that works on matrices I have found something
curious...
Here's what I think is going on. AFAIK, D hasn't got any special code
for initializing jagged arrays. So
auto A = new double[][](N, N);
i
Sun, 23 Nov 2008 07:33:16 -0600, Andrei Alexandrescu wrote:
> Sergey Gromov wrote:
>> The really weird part is, if I comment out the "init mats randomly" loop
>> in #1, it becomes twice as slow, i.e. 20s against the original 10s. I
>> don't get it.
>
> I think what happens is that the speed of F
bearophile wrote:
Andrei Alexandrescu:
My guess is that if you turn that off, the differences won't be as large
(or even detectable for certain ranges of N).
The array bounds aren't controlled, the code is compiled with -O -release
-inline.
Do you see array bound controls in the asm code at t
Tom S wrote:
Don wrote:
bearophile wrote:
While writing code that works on matrices I have found something
curious...
Here's what I think is going on. AFAIK, D hasn't got any special code
for initializing jagged arrays. So
auto A = new double[][](N, N);
involves N+1 memory allocatio
Sergey Gromov wrote:
Sat, 22 Nov 2008 20:14:37 -0500, bearophile wrote:
Can you or someone else run that little D code, so you can tell me if
my timings are right?
Tested your code using DMD 2.019. You are right. The #1 is about 30
times slower than #2: 10s against 0,3s on my laptop. I've
Bill Baxter:
> Exactly. That's why I haven't spent too much time benchmarking it.
> It would be quite surprising if something I wrote in D outperformed
> the ATLAS SSE3 optimized BLAS implementation.
Performing many benchmarks teaches you that it's better not assume too much
things. Nature and c
Tom S:
> Nah, it's about NaNs :)
> Version #1 initializes C to NaN, Version #2 initializes it to 0. The
> 'init mats randomly' loop doesn't touch C at all, thus all the latter
> additions leave C at NaN, causing lots of FP exceptions.
You are right, and I'm a stupid. Most of my benchmarks have s
On Sun, Nov 23, 2008 at 12:25 PM, BCS <[EMAIL PROTECTED]> wrote:
> Reply to bearophile,
>
>> Bill Baxter Wrote:
>>
>>> I haven't done any benchmarks, though. :-)
>>>
>> I see. But using something because it's supposed to be faster without
>> performing actual performance comparisons looks a little
Doh! The NaNs strike again.
--bb
On Sun, Nov 23, 2008 at 3:40 PM, Tom S <[EMAIL PROTECTED]> wrote:
> Don wrote:
>>
>> bearophile wrote:
>>>
>>> While writing code that works on matrices I have found something
>>> curious...
>>
>> Here's what I think is going on. AFAIK, D hasn't got any special c
Don wrote:
bearophile wrote:
While writing code that works on matrices I have found something
curious...
Here's what I think is going on. AFAIK, D hasn't got any special code
for initializing jagged arrays. So
auto A = new double[][](N, N);
involves N+1 memory allocations.
As well as
bearophile wrote:
While writing code that works on matrices I have found something curious...
Here's what I think is going on. AFAIK, D hasn't got any special code
for initializing jagged arrays. So
auto A = new double[][](N, N);
involves N+1 memory allocations.
As well as being slow,
Sat, 22 Nov 2008 20:14:37 -0500, bearophile wrote:
> Can you or someone else run that little D code, so you can tell me if
> my timings are right?
Tested your code using DMD 2.019. You are right. The #1 is about 30
times slower than #2: 10s against 0,3s on my laptop. I've also tried to
replace
Reply to bearophile,
Bill Baxter Wrote:
I haven't done any benchmarks, though. :-)
I see. But using something because it's supposed to be faster without
performing actual performance comparisons looks a little strange to me
:-)
BLAS may well be the most tested, optimized and benchmarked c
Bill Baxter Wrote:
> I haven't done any benchmarks, though. :-)
I see. But using something because it's supposed to be faster without
performing actual performance comparisons looks a little strange to me :-)
> Might be interesting to try out my MingGW-compiled ATLAS BLAS matrix
> mult against
On Sun, Nov 23, 2008 at 8:29 AM, bearophile <[EMAIL PROTECTED]> wrote:
> Andrei Alexandrescu:
>> My guess is that if you turn that off, the differences won't be as large
>> (or even detectable for certain ranges of N).
>
> The array bounds aren't controlled, the code is compiled with -O -release
>
Andrei Alexandrescu:
> My guess is that if you turn that off, the differences won't be as large
> (or even detectable for certain ranges of N).
The array bounds aren't controlled, the code is compiled with -O -release
-inline.
Do you see array bound controls in the asm code at the bottom of my po
bearophile wrote:
While writing code that works on matrices I have found something
curious, so I have written the following little benchmark. As usual
keep eyes open for possible bugs and mistakes of mine:
[snip]
This is yet another proof that bounds checking can cost a lot. Although
the loopi
While writing code that works on matrices I have found something curious, so I
have written the following little benchmark. As usual keep eyes open for
possible bugs and mistakes of mine:
import std.conv: toInt;
import std.c.stdlib: rand, malloc;
const int RAND_MAX = short.max; // RAND_MAX seem
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