Engineering topics
Publications and source records attributed to Pranesh, Srikara.
Two main tasks have been performed in the past year as part of the Mixed Precision xsdk Project: analysis and development of mixed precision algorithms, and community engagement. Each is briefly discussed and work summarized.
The efficient utilization of mixed-precision numerical linear algebra algorithms can offer attractive acceleration to scientific computing applications. Especially with the hardware integration of low-precision special-function units designed for machine learning applications, the traditional numerical algorithms community urgently needs to reconsider the floating point formats used in the distinct operations to efficiently leverage the available compute power. In this study, we provide a comprehensive survey of mixed-precision numerical linear algebra routines, including the underlying concepts, theoretical background, and experimental results for both dense and sparse linear algebra problems.