On Wednesday, 15 July 2020 at 07:51:31 UTC, 9il wrote:
On Wednesday, 15 July 2020 at 07:34:59 UTC, tastyminerals wrote:
On Wednesday, 15 July 2020 at 06:57:21 UTC, 9il wrote:
On Wednesday, 15 July 2020 at 06:55:51 UTC, 9il wrote:
On Wednesday, 15 July 2020 at 06:00:46 UTC, tastyminerals
> I've mixed up @fastmath and @fmamath as well. No worries.
Seems like this might be a good awareness opportunity to change one
of the names to be more descriptive and more distinctive.
FWIW, I read half way through threw the thread before I caught onto
the distinction. I can imagine making that
On Wednesday, 15 July 2020 at 11:41:35 UTC, 9il wrote:
[snip]
Ah, no, my bad! You write @fmamath, I have read it as
@fastmath. @fmamath is OK here.
I've mixed up @fastmath and @fmamath as well. No worries.
On Wednesday, 15 July 2020 at 11:37:23 UTC, jmh530 wrote:
On Wednesday, 15 July 2020 at 11:26:19 UTC, 9il wrote:
[snip]
@fmamath private double sd(T)(Slice!(T*, 1) flatMatrix)
@fastmath violates all summation algorithms except `"fast"`.
The same bug is in the original author's post.
I
On Wednesday, 15 July 2020 at 11:26:19 UTC, 9il wrote:
[snip]
@fmamath private double sd(T)(Slice!(T*, 1) flatMatrix)
@fastmath violates all summation algorithms except `"fast"`.
The same bug is in the original author's post.
I hadn't realized that @fmamath was the problem, rather than
On Wednesday, 15 July 2020 at 11:23:00 UTC, jmh530 wrote:
On Wednesday, 15 July 2020 at 05:57:56 UTC, tastyminerals wrote:
[snip]
Here is a (WIP) project as of now.
Line 160 in
https://github.com/tastyminerals/mir_benchmarks_2/blob/master/source/basic_ops.d
std of [60, 60] matrix 0.0389492
On Wednesday, 15 July 2020 at 05:57:56 UTC, tastyminerals wrote:
[snip]
Here is a (WIP) project as of now.
Line 160 in
https://github.com/tastyminerals/mir_benchmarks_2/blob/master/source/basic_ops.d
std of [60, 60] matrix 0.0389492 (> 0.001727)
std of [300, 300] matrix 1.03592 (> 0.043452)
On Wednesday, 15 July 2020 at 07:34:59 UTC, tastyminerals wrote:
On Wednesday, 15 July 2020 at 06:57:21 UTC, 9il wrote:
On Wednesday, 15 July 2020 at 06:55:51 UTC, 9il wrote:
On Wednesday, 15 July 2020 at 06:00:46 UTC, tastyminerals
wrote:
On Wednesday, 15 July 2020 at 02:08:48 UTC, 9il
On Wednesday, 15 July 2020 at 06:57:21 UTC, 9il wrote:
On Wednesday, 15 July 2020 at 06:55:51 UTC, 9il wrote:
On Wednesday, 15 July 2020 at 06:00:46 UTC, tastyminerals
wrote:
On Wednesday, 15 July 2020 at 02:08:48 UTC, 9il wrote:
On Tuesday, 14 July 2020 at 19:04:45 UTC, tastyminerals
wrote:
On Wednesday, 15 July 2020 at 06:00:46 UTC, tastyminerals wrote:
On Wednesday, 15 July 2020 at 02:08:48 UTC, 9il wrote:
On Tuesday, 14 July 2020 at 19:04:45 UTC, tastyminerals wrote:
@fastmath private double sd0(T)(Slice!(T*, 1) flatMatrix)
@fastmath shouldn't be really used with summation
On Wednesday, 15 July 2020 at 06:55:51 UTC, 9il wrote:
On Wednesday, 15 July 2020 at 06:00:46 UTC, tastyminerals wrote:
On Wednesday, 15 July 2020 at 02:08:48 UTC, 9il wrote:
On Tuesday, 14 July 2020 at 19:04:45 UTC, tastyminerals wrote:
@fastmath private double sd0(T)(Slice!(T*, 1)
On Wednesday, 15 July 2020 at 02:08:48 UTC, 9il wrote:
On Tuesday, 14 July 2020 at 19:04:45 UTC, tastyminerals wrote:
@fastmath private double sd0(T)(Slice!(T*, 1) flatMatrix)
@fastmath shouldn't be really used with summation algorithms
except the `"fast"` version of them. Otherwise, they
On Tuesday, 14 July 2020 at 19:36:21 UTC, jmh530 wrote:
On Tuesday, 14 July 2020 at 19:04:45 UTC, tastyminerals wrote:
[...]
It would be helpful to provide a link.
You should only need one accumulator for mean and centered sum
of squares. See the python example under the Welford example
On Wednesday, 15 July 2020 at 02:08:48 UTC, 9il wrote:
On Tuesday, 14 July 2020 at 19:04:45 UTC, tastyminerals wrote:
@fastmath private double sd0(T)(Slice!(T*, 1) flatMatrix)
@fastmath shouldn't be really used with summation algorithms
except the `"fast"` version of them. Otherwise, they
On Tuesday, 14 July 2020 at 19:04:45 UTC, tastyminerals wrote:
@fastmath private double sd0(T)(Slice!(T*, 1) flatMatrix)
@fastmath shouldn't be really used with summation algorithms
except the `"fast"` version of them. Otherwise, they may or may
not behave like "fast".
On Tuesday, 14 July 2020 at 19:04:45 UTC, tastyminerals wrote:
I am trying to implement standard deviation calculation in Mir
for benchmark purposes.
I have two implementations. One is the straightforward std =
sqrt(mean(abs(x - x.mean())**2)) and the other follows
Welford's algorithm for
I am trying to implement standard deviation calculation in Mir
for benchmark purposes.
I have two implementations. One is the straightforward std =
sqrt(mean(abs(x - x.mean())**2)) and the other follows Welford's
algorithm for computing variance (as described here:
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