R-CCS Cafe 第198回 第2部

We use floating-point numbers for numerical computations in computers. However, as floating-point numbers are represented in finite-precision (usually, 32-bit or 64-bit), the computation has rounding errors. The accumulation may result in inaccuracy of the computation. Moreover, the result can be non-identical at the rounding-error level on different computational environments because the rounding-errors are introduced depending on the order of the computation. Our team studies and develops technologies for addressing those issues to improve the reliability of numerical computations. In this talk, I will introduce several studies that I have been conducting now, including (1) high-precision matrix-multiplications using low-precision operations, (2) accurate and reproducible BLAS and sparse linear solvers, and (3) minimal-precision computing project.