Vectorization Techniques for BlueGene / L ’ s Double FPU

This paper presents vectorization techniques tailored to meet the specifics of the twoway single-instruction multiple-data (SIMD) double-precision floating-point unit, which is a core element of the node ASICs of IBM's 360 Tflop/s supercomputer BlueGene/L. The paper focuses on the general-purpose basic-block vectorization methods provided by the Vienna MAP vectorizer. In addition, the paper introduces vectorization techniques specific to discrete signal transforms. The presented vectorization methods are evaluated in connection with the state-of-the-art automatic performance tuning systems SPIRAL and FFTW. The combination of automatic performance tuning and the presented vectorization techniques result in FFT codes tuned automatically to a single BlueGene/L processor which are up to 60% faster than the best scalar code generated by the respective systems and five times faster than the mixed-radix FFT implementation provided by the GNU scientific library GSL.