Comments (2)
So looking at the Quo
code, there are a lot of for loops. It looks like it's trying to do things digit by digit. Is this algorithm designed around cases with very large precision? What if there were a fast path for precision <= 34 (decimal128, etc.)?
I benchmarked some decimal128 code based on https://software.intel.com/content/www/us/en/develop/articles/intel-decimal-floating-point-math-library.html by the way and division is comparable to multiplication there. So it must be possible for apd to have a more efficient Quo
implementation for "low" precision.
from apd.
Hi @aaronc, thanks for the report. Quo
performance has improved recently (it's about 50% faster on your benchmark), but it still lags the performance of other operations by quite a margin. As you identified, this has to do with the digit-by-digit loop in Quo
. The algorithm is designed around cases with very large precision and does not include any form of fast-path for low precision values. I'd like to keep this issue open to track the introduction of such a fast path.
from apd.
Related Issues (20)
- Is this maintained? HOT 9
- Thank you! HOT 5
- panic with SetString(".-400000000000000000000000000000000000000") HOT 1
- Precision clarification HOT 1
- Inconsistent (or buggy) Quantize behavior HOT 2
- please drop github.com/pkg/errors HOT 2
- Decompose is not using buf
- clarify .Text 'g' docs
- Proper way to set a apd.NullDecimal? HOT 10
- NewWithBigInt doesn't set negative correctly
- Version v1.1.0 included by default when using Go modules HOT 1
- request for new tag HOT 2
- Function remainder returns division impossible HOT 2
- format weirdness with a non-pointer Decimal HOT 3
- Inconsistent behaviour for negative zero HOT 3
- How to use Quantize with limited precision context HOT 5
- Inconsistent negative flag behavior HOT 2
- cos and friends HOT 1
- precision, scale HOT 6
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