Faster arbitrary-precision dot product and matrix multiplication
Langue
en
Communication dans un congrès
Ce document a été publié dans
26th IEEE Symposium on Computer Arithmetic (ARITH26), 2019-06-10, Kyoto.
Résumé en anglais
We present algorithms for real and complex dot product and matrix multiplication in arbitrary-precision floating-point and ball arithmetic. A low-overhead dot product is implemented on the level of GMP limb arrays; it is ...Lire la suite >
We present algorithms for real and complex dot product and matrix multiplication in arbitrary-precision floating-point and ball arithmetic. A low-overhead dot product is implemented on the level of GMP limb arrays; it is about twice as fast as previous code in MPFR and Arb at precision up to several hundred bits. Up to 128 bits, it is 3-4 times as fast, costing 20-30 cycles per term for floating-point evaluation and 40-50 cycles per term for balls. We handle large matrix multiplications even more efficiently via blocks of scaled integer matrices. The new methods are implemented in Arb and significantly speed up polynomial operations and linear algebra.< Réduire
Mots clés en anglais
Arbitrary-precision arithmetic
Ball arithmetic
Dot product
Matrix multiplication
Origine
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