Today's heterogeneous architectures bring together multiple general-purpose CPUs and multiple domainspecific GPUs and FPGAs to provide dramatic speedup for many applications. However, the challenge lies in utilizing these heterogeneous processors to optimize overall application performance by minimizing workload completion time. Operating system and application development for these systems is in their infancy. In this article, we propose a new scheduling and workload balancing scheme, HDSS, for execution of loops having dependent or independent iterations on heterogeneous multiprocessor systems. The new algorithm dynamically learns the computational power of each processor during an adaptive phase and then schedules the remainder of the workload using a weighted self-scheduling scheme during the completion phase. Different from previous studies, our scheme uniquely considers the runtime effects of block sizes on the performance for heterogeneous multiprocessors. It finds the right trade-off between large and small block sizes to maintain balanced workload while keeping the accelerator utilization at maximum. Our algorithm does not require offline training or architecture-specific parameters. We have evaluated our scheme on two different heterogeneous architectures: AMD 64-core Bulldozer system with nVidia Fermi C2050 GPU and Intel Xeon 32-core SGI Altix 4700 supercomputer with Xilinx Virtex 4 FPGAs. The experimental results show that our new scheduling algorithm can achieve performance improvements up to over 200% when compared to the closest existing load balancing scheme. Our algorithm also achieves full processor utilization with all processors completing at nearly the same time which is significantly better than alternative current approaches.
With recent advancements in techniques for cellular data acquisition, information on cellular processes has been increasing at a dramatic rate. Visualization is critical to analyzing and interpreting complex information; representing cellular processes or pathways is no exception. VISIBIOweb is a free, open-source, web-based pathway visualization and layout service for pathway models in BioPAX format. With VISIBIOweb, one can obtain well-laid-out views of pathway models using the standard notation of the Systems Biology Graphical Notation (SBGN), and can embed such views within one's web pages as desired. Pathway views may be navigated using zoom and scroll tools; pathway object properties, including any external database references available in the data, may be inspected interactively. The automatic layout component of VISIBIOweb may also be accessed programmatically from other tools using Hypertext Transfer Protocol (HTTP). The web site is free and open to all users and there is no login requirement. It is available at: http://visibioweb.patika.org.
We present a new algorithm for automatic layout of clustered graphs using a circular style. The algorithm tries to determine optimal location and orientation of individual clusters intrinsically within a modified spring embedder. Heuristics such as reversal of the order of nodes in a cluster and swap of neighboring node pairs in the same cluster are employed intermittently to further relax the spring embedder system, resulting in reduced inter-cluster edge crossings. Unlike other algorithms generating circular drawings, our algorithm does not require the quotient graph to be acyclic, nor does it sacrifice the edge crossing number of individual clusters to improve respective positioning of the clusters. Moreover, it reduces the total area required by a cluster by using the space inside the associated circle. Experimental results show that the execution time and quality of the produced drawings with respect to commonly accepted layout criteria are quite satisfactory, surpassing previous algorithms. The algorithm has also been successfully implemented and made publicly available as part of a compound and clustered graph editing and layout tool named CHISIO.
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