This paper presents transprecision techniques for iterative refinement, which utilize various precision arithmetic dynamically according to numeric properties of the algorithm and computational latencies depending on precisions. The transprecision techniques were plugged into a mixed precision iterative refinement on an Intel Xeon E5-2650 2GHz core with MKL 2017 and XBLAS 1.0. The transprecision techniques brought further 2.0-3.4X speedups and 3.0-4.1X energy reductions to a mixed precision iterative refinement when double precision solution accuracy was required for forward error and a matrix size was ranged from 4K to 32K.
|Accepted - 01 Sept 2017
|Supercomputing'17 (SC17): International Conference on High Performance Computing, Networking, Storage and Analysis - Denver, United States
Duration: 11 Nov 2017 → 17 Nov 2017
|Supercomputing'17 (SC17): International Conference on High Performance Computing, Networking, Storage and Analysis
|11/11/2017 → 17/11/2017
- transprecision, mixed precision, iterative refinement