No abstract

We present load-balancing strategies to improve performances of parallel MPI applications running in a Grid environment. We analyze the data distribution constraints found in two scientific codes and propose adapted code transformations to load-balance computations. We present the general framework for our load-balancing techniques. We then describe these techniques as well as their application to our examples. Experimental results confirm that adapted source code transformations can improve Grid application performances.

In this paper we describe the design of a global machine independent low level optimizer for the Karlsruhe Ada Compiler. We give a short overview on the optimizations and data structures used in the optimizer as well as some experiences with the optimizer. Detailed measurements are provided for a collection of benchmarks. The average improvement of code speed is 40%.

No abstract