We present results from a study of QCD with two flavors of Wilson fermions using the hybrid Monte Carlo algorithm, which incorporates the effects of fermion loops exactly. We evaluate the performance of the algorithm and its potential for large-scale computations. We argue that in the best case the algorithm slows down as ~~'~m ; " '~ at a fixed gauge coupling. We present improved algorithms for calculating the inverse and the determinant of the Wilson fermion operator. Results for the finite-temperature transition on 4 X 6 b n d 6 x 8; lattices are presented at P15.2-5.6. We also give Wilson loop expectation values obtained on 84 lattices at 8=5.3 for six values of K . The data show evidence for screening in the qq potential. Lastly, on comparing Wilson and staggeredfermion results we find that 8=5.3 is far from the scaling region.
For many F ortran90 and HPF programs performing dense matrix computations, the main computational portion of the program belongs to a class of k ernels kno wn as stencils. Stencil computations are commonly used in solving partial di eren tial equations, image processing, and geometric modeling. The e cien t handling of such stencils is critical for achieving high performance on distributed-memory mac hines. Compiling stencils into e cient c o d e i s v i e w ed as so important that some companies have built special-purpose compilers for handling them and others ha ve added stencilrecognizers to existing compilers.In this paper we present a general compilation strategy for stencils written using Fortran90 array constructs. Our strategy is capable of optimizing single or m ultistatement stencils and is applicable to stencils speci ed with shift intrinsics or with array-syntax all equally well. The strategy eliminates the need for pattern-recognition algorithms by o r c hestrating a set of optimizations that address the overhead of both intraprocessor and interprocessor data movement that results from the translation of Fortran90 array constructs. Our experimen tal results show that code produced by this strategy beats or matches the best code produced by the special-purpose compilers or pattern-recognition schemes that are known to us. In addition, our strategy produces highly optimized code in situations where the others fail, producing several orders of magnitude performance impro vement, and thus provides a stencil compilation strategy that is more robust than its predecessors.
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