From Optimizing Compilers for Modern Architectures: A Dependence-Based Approach

1.1 Overview and Goals

The past two decades have been exciting ones for high-performance computing. Desktop personal computers today feature computing power equivalent to the most powerful supercomputers of the late 1970s. Meanwhile, through the use of parallelism and innovations in the memory hierarchy, supercomputers have exceeded a sustained teraflop on real applications and are now setting their sights on 10 to 100 teraflops. High-end supercomputing systems can be seen as laboratories for software research and development because innovations developed on such systems eventually find their way to the desktop computer systems.

The phenomenal improvements in computer speeds have been the result of two effects. First, the underlying technology from which machines are constructed has seen remarkable advances on a pace predicted by Moore's Law. Figure 1.1 plots the peak performance of the fastest supercomputer by year from 1950 to 2000. The regression fit, which follows Moore's Law quite well, indicates that supercomputer performance has increased by two orders of magnitude every decade. However, technology by itself has not been enough. The four outlined regions show that differences in computer architecture from scalar through superscalar and vector to parallel have been necessary to keep performance on track. Clearly, parallelism of one form or another is essential to supercomputing performance.

Figure 1.1: Performance of the fastest supercomputers over 50 years.

But parallelism is not just for supercomputers anymore. Even though today's uniprocessors achieve phenomenal performance levels, they still cannot satisfy the thirst of image-processing applications and multimedia on the desktop. Meeting...

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Topics of Interest

2.1 Introduction As we learned in Chapter 1, optimization has an important function in the acceptance of a programming language if the optimizer does not do a good job, no one will use the language.

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