Schneider, TimoHoefler, TorstenWunderlich, SimonMehlan, TorstenRehm, WolfgangNagel, Wolfgang E.Hoffmann, RolfKoch, Andreas2019-05-062019-05-062008978-3-88579-218-5https://dl.gi.de/handle/20.500.12116/22270The architecture of the IBM Cell BE processor represents a new approach for designing CPUs. The fast execution of legacy software has to stand back in order to achieve very high performance for new scientific software. The Cell BE consists of 9 independent cores and represents a new promising architecture for HPC systems. The programmer has to write parallel software that is distributed to the cores and executes subtasks of the program in parallel. The simplified Vector-CPU design achieves higher clock-rates and power efficiency and exhibits predictable behavior. But to exploit the capabilities of this upcoming CPU architecture it is necessary to provide optimized libraries for frequently used algorithms. The Basic Linear Algebra Subprograms (BLAS) provide functions that are crucial for many scientific applications. The routine ZGEMM, which computes a complex matrix–matrix–product, is one of these functions. This article describes strategies to implement the ZGEMM routine on the Cell BE processor. The main goal is achieve highest performance. We compare this optimized ZGEMM implementation with several math libraries on Cell and other modern architectures. Thus we are able to show that our ZGEMM algorithm performs best in comparison to the fastest publicly available ZGEMM and DGEMM implementations for Cell BE and reasonably well in the league of other BLAS implementations.enText/Conference Paper1617-5468