On the Use of Subword Parallelism in Medical Image Processing

Parallel implementations of algorithms for medical image processing mostly focus on the use of multiprocessor parallelism. Modern processor architectures however, provide several additional forms of parallelism at the processor level: subword parallelism, speculative execution, superscalar pipelining, very long instruction word, etc. In this article, we show that well-known parallelization techniques for multiprocessor systems can be used to exploit subword parallelism. Loop unrolling, loop fusion and if-hoisting prove to be valuable to achieve this goal. To illustrate this, we transformed the inner loops of a positron emission tomography image reconstruction algorithm. We achieved a speed-up of 45% on Sun's UltraSPARC processor. Key words: subword parallelism, loop transformations, positron emission tomography