Faster arbitrary-precision dot product and matrix multiplication
Idioma
en
Communication dans un congrès
Este ítem está publicado en
26th IEEE Symposium on Computer Arithmetic (ARITH26), 2019-06-10, Kyoto.
Resumen en inglés
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 ...Leer más >
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.< Leer menos
Palabras clave en inglés
Arbitrary-precision arithmetic
Ball arithmetic
Dot product
Matrix multiplication
Orígen
Importado de HalCentros de investigación