M. Cierniak and W. Li. Briki: an optimizing Java compiler. In Proceedings of the IEEE CompCon '97, San Jose, California, February 1997.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....HPF compilation system [83] As HPF has evolved to version 2.0, we have extended our HPF front end to cover HPF 2.0. The Syracuse common runtime also supports an older subset HPF system [61] has a user level C interface, and is being used as the basis of a new HPJava translator. Rochester [31, 34] and Indiana [13, 14, 17, 16] are also developing Java compilers. Rice is working on Java compiler optimizations [19] 2.9 Java and SPMD programming A signi cant new task in the revised statement of work submitted in July 97 was the proposal to provide an infrastructure supporting high level ....

....which highlights the pro le information in an easy to use manner. All of this can be done over the Internet using a client server approach and is independent of the underlying architecture machine and human intervention. More details can be found in [67] Other Rochester publications, see [36, 39, 38, 37, 35, 58, 34, 80, 81, 79]. 31 8 Florida University Report Florida became involved in the project after Sanjay Ranka, one of the original co PIs, moved there from Syracuse. We evaluated the High Performance Fortran (HPF) language as a candidate for implementing scienti c, engineering and computer science software on ....

M. Cierniak and W. Li. Briki: an optimizing Java compiler. In Proceedings of the IEEE CompCon '97, San Jose, California, February 1997.

....loop transformations. Also our approach is simpler for embedding in a compilation system, since it does not require a prior knowledge of any vector such as v: Our extension to multiple nests is also different from the one proposed by Cierniak and Li [3] for global optimization. Cierniak and Li [4] also used data transformations for optimizing JAVA byte codes. IV. ALGORITHM FOR OPTIMIZING LOCALITY In this section we explain our algorithm that automatically transforms a given loop nest to exploit spatial locality and assigns appropriate memory layouts for arrays, both in a unified ....

M. Cierniak and W. Li. Briki: an optimizing Java compiler. In Proc. the IEEE CompCon '97 , San Jose, California, February 1997.

....HPF compilation system [83] As HPF has evolved to version 2.0, we have extended our HPF front end to cover HPF 2.0. The Syracuse common runtime also supports an older subset HPF system [61] has a user level C interface, and is being used as the basis of a new HPJava translator. Rochester [31, 34] and Indiana [13, 14, 17, 16] are also developing Java compilers. Rice is working on Java compiler optimizations [19] 2.9 Java and SPMD programming A significant new task in the revised statement of work submitted in July 97 was the proposal to provide an infrastructure supporting high level ....

....which highlights the profile information in an easy to use manner. All of this can be done over the Internet using a client server approach and is independent of the underlying architecture machine and human intervention. More details can be found in [67] Other Rochester publications, see [36, 39, 38, 37, 35, 58, 34, 80, 81, 79]. 8 Florida University Report Florida became involved in the project after Sanjay Ranka, one of the original co PIs, moved there from Syracuse. We evaluated the High Performance Fortran (HPF) language as a candidate for implementing scientific, engineering and computer science software on ....

M. Cierniak and W. Li. Briki: an optimizing Java compiler. In Proceedings of the IEEE CompCon '97, San Jose, California, February 1997.

....running much faster and using less memory. For our study we use an optimizations technique called data transformations. In previous work we have shown that data transformations can be very effective in compiling Fortran or C programs [3] Recently we have adapted the technique for Java bytecodes [5, 6]. However, our previous experiments with optimizing Java bytecodes have been performed with an off line compiler and the compiler algorithms were not as fast as a competitive JIT compiler is expected to be. To perform data transformations we need more program structure than is directly available ....

....is an order of magnitude longer than the time to perform the optimizations. Since most the high level structure is not needed to perform data transformation, we have decided to use a different approach in our JIT optimizer. This paper shows how to perform the same optimizations as described in [5, 6] while recovering only as much structure as needed and using faster (although not necessarily as accurate) analysis techniques than those traditionally used in off line compilers [1, 11] 2 Overview of Array Transformations Array transformations change the layout of array elements in memory to ....

M. Cierniak and W. Li. Briki: an Optimizing Java Compiler. In Proceedings of the IEEE COMPCON '96, San Jose, CA, February 1997.

....running much faster and using less memory. For our study we use an optimizations technique called data transformations. In previous work we have shown that data transformations can be very effective in compiling Fortran or C programs [4] Recently we have adapted the technique for Java bytecodes [1, 5]. However, our previous experiments with optimizing Java bytecodes have been performed with an off line compiler and the compiler algorithms were not as fast as a competitive JIT compiler is expected to be. To perform data transformations we need more program structure than is directly available ....

....is an order of magnitude longer than the time to perform the optimizations. Since most the high level structure is not needed to perform data transformation, we have decided to use a different approach in our JIT optimizer. This paper shows how to perform the same optimizations as described in [1, 5] while recovering only as much structure as needed and using faster (although not necessarily as accurate) analysis techniques than those traditionally used in off line compilers [6, 7] We have implemented all the techniques described in this paper in our experimental compiler Briki. Briki uses ....

M. Cierniak and W. Li. Briki: an Optimizing Java Compiler. In Proceedings of the IEEE COMPCON '96, San Jose, CA, February 1997.

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