21,449 research outputs found
Radix Conversion for IEEE754-2008 Mixed Radix Floating-Point Arithmetic
Conversion between binary and decimal floating-point representations is
ubiquitous. Floating-point radix conversion means converting both the exponent
and the mantissa. We develop an atomic operation for FP radix conversion with
simple straight-line algorithm, suitable for hardware design. Exponent
conversion is performed with a small multiplication and a lookup table. It
yields the correct result without error. Mantissa conversion uses a few
multiplications and a small lookup table that is shared amongst all types of
conversions. The accuracy changes by adjusting the computing precision
Improved Accuracy and Parallelism for MRRR-based Eigensolvers -- A Mixed Precision Approach
The real symmetric tridiagonal eigenproblem is of outstanding importance in
numerical computations; it arises frequently as part of eigensolvers for
standard and generalized dense Hermitian eigenproblems that are based on a
reduction to tridiagonal form. For its solution, the algorithm of Multiple
Relatively Robust Representations (MRRR) is among the fastest methods. Although
fast, the solvers based on MRRR do not deliver the same accuracy as competing
methods like Divide & Conquer or the QR algorithm. In this paper, we
demonstrate that the use of mixed precisions leads to improved accuracy of
MRRR-based eigensolvers with limited or no performance penalty. As a result, we
obtain eigensolvers that are not only equally or more accurate than the best
available methods, but also -in most circumstances- faster and more scalable
than the competition
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