Automatic Detection of Parallelism: A grand challenge for high performance computing
William Blume, Rudolf Eigenmann, Jay P. Hoeflinger, David Padua, Paul M. Petersen, Lawrence Rauchwerger, Perg Tu · IEEE Parallel & Distributed Technology Systems & Applications · 1994
The limited ability of compilers to nd the parallelism in programs is a signi cant barrier to the use of high performance computers. It forces programmers to resort to parallelizing their programs by hand, adding another level of complexity to the programming task. We show evidence that compilers can be improved, through static and run-time techniques, to the extent that a signi cant group of scienti c programs may be parallelized automatically. Symbolic dependence analysis and array privatization, plus run-time versions of those techniques are shown to be important to the success of this e ort. If we can succeed to parallelize programs automatically, the acceptance and use of large-scale parallel processors will be enhanced greatly.