Ag
10 楼
even use double precision, you still can't get accurate result
for each step. As a result, gradually, the error will be bigger
and bigger. Different CPUs with various hardwares handle data in
different ways, you get different results, which is quiet normal.
【在 s***t 的大作中提到】
: then how can you trust such results ?
for each step. As a result, gradually, the error will be bigger
and bigger. Different CPUs with various hardwares handle data in
different ways, you get different results, which is quiet normal.
【在 s***t 的大作中提到】
: then how can you trust such results ?
s*t
12 楼
what i meant was if this happens, either your algorithm is bad, or your
problem is ill-posed. so the results is not meaningful at all.
【在 Ag 的大作中提到】
: even use double precision, you still can't get accurate result
: for each step. As a result, gradually, the error will be bigger
: and bigger. Different CPUs with various hardwares handle data in
: different ways, you get different results, which is quiet normal.
problem is ill-posed. so the results is not meaningful at all.
【在 Ag 的大作中提到】
: even use double precision, you still can't get accurate result
: for each step. As a result, gradually, the error will be bigger
: and bigger. Different CPUs with various hardwares handle data in
: different ways, you get different results, which is quiet normal.
a*s
13 楼
For you,it maybe normal. But for others,eg. me,it is not normal.:)
How come?
【在 Ag 的大作中提到】
: even use double precision, you still can't get accurate result
: for each step. As a result, gradually, the error will be bigger
: and bigger. Different CPUs with various hardwares handle data in
: different ways, you get different results, which is quiet normal.
How come?
【在 Ag 的大作中提到】
: even use double precision, you still can't get accurate result
: for each step. As a result, gradually, the error will be bigger
: and bigger. Different CPUs with various hardwares handle data in
: different ways, you get different results, which is quiet normal.
Ag
15 楼
only if the results are similar, say, in the range of +/-0.5%.
surely it's not acceptable if totally different.
but for 1.23567 and 1.23568, I consider them the same.
【在 s***t 的大作中提到】
: what i meant was if this happens, either your algorithm is bad, or your
: problem is ill-posed. so the results is not meaningful at all.
surely it's not acceptable if totally different.
but for 1.23567 and 1.23568, I consider them the same.
【在 s***t 的大作中提到】
: what i meant was if this happens, either your algorithm is bad, or your
: problem is ill-posed. so the results is not meaningful at all.
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