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Although there has been some experimentation with Java as a language for numerically intensive computing, there is a perception by many that the language is unsuited for such work. In this paper we show how optimizing array bounds checks and null pointer checks creates loop nests on which aggressive optimizations can be used. Applying these optimizations by hand to a simple matrix-multiply test case leads to Java compliant programs whose performance is in excess of 500~Mflops on an RS/6000 SP 332MHz SMP node. We also report in this paper the effect that various optimizations have on the performance of six floating-point intensive benchmarks. Through these optimizations we have been able to achieve with Java at least 80% of the peak Fortran performance on the same benchmarks. Since all of these optimizations can be automated, we conclude that Java will soon be a serious contender for numerically intensive computing.
By: Jose Moreira, Sam Midkiff, Manish Gupta
Published in: ACM Transactions on Programming Languages and Systems, volume 22, (no 2), pages 265-95 in 2000
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