Distributed Maple: parallel computer algebra in networked environments

AbstractWe describe the design and use of Distributed Maple, an environment for executing parallel computer algebra programs on multiprocessors and heterogeneous clusters. The system embeds kernels of the computer algebra system Maple as computational engines into a networked coordination layer implemented in the programming language Java. On the basis of a comparatively high-level programming model, one may write parallel Maple programs that show good speedups in medium-scaled environments. We report on the use of the system for the parallelization of various functions of the algebraic geometry library CASA and demonstrate how design decisions affect the dynamic behaviour and performance of a parallel application. Numerous experimental results allow comparison of Distributed Maple with other systems for parallel computer algebra

The Impact of Link Arbitration on Switch Performance

Switch design for interconnection networks plays an important role in the overall performance of multiprocessors and computer networks. In this paper we study the impact of one parameter in the switch design space, link arbitration. We demonstrate that link arbitration can be a determining factor in the performance of current networks. Moreover, we expect increased research focus on arbitration techniques to become a trend in the future, as switch architectures evolve towards increasing the number of virtual channels and input ports. In the context of a state-of-the-art switch design we use both synthetic workload and execution driven simulations to compare several arbitration policies. Furthermore, we devise a new arbitration method, Look-Ahead arbitration. Under heavy traffic conditions the Look-Ahead policy provides significant improvements over traditional arbitration schemes without a significant increase in hardware complexity. Also, we propose a priority based policy that is ca..