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We explore the interplay between architectures and algorithm design in the context of shared-memory platforms and a specific graph problem of central importance in scientific and high-performance computing, distance-1 graph coloring. We introduce two different kinds of multithreaded heuristic algorithms for the stated, NP-hard, problem. The first algorithm(More)
Combinatorial problems such as those from graph theory pose serious challenges for parallel machines due to non-contiguous, concurrent accesses to global data structures with low degrees of locality. The hierarchical memory systems of symmetric multiprocessor (SMP) clusters optimize for local, contiguous memory accesses, and so are inefficient platforms for(More)
Operating the electrical power grid to prevent power blackouts is a complex task. An important aspect of this is contingency analysis, which involves understanding and mitigating potential failures in power grid elements such as transmission lines. When taking into account the potential for multiple simultaneous failures (known as the N-x contingency(More)
Triadic analysis encompasses a useful set of graph mining methods that are centered on the concept of a triad, which is a sub graph of three nodes. Such methods are often applied in the social sciences as well as many other diverse fields. Triadic methods commonly operate on a triad census that counts the number of triads of every possible edge(More)
The Tera MTA is a revolutionary commercial computer based on a multithreaded processor architecture. In contrast to many other parallel architectures, the Tera MTA can effectively use high amounts of parallelism on a single processor. By running multiple threads on a single processor, it can tolerate memory latency and to keep the processor saturated. If(More)
In Energy Management Systems, contingency analysis is commonly performed for identifying and mitigating potentially harmful power grid component failures. The exponentially increasing combinatorial number of failure modes imposes a significant computational burden for massive contingency analysis. It is critical to select a limited set of high-impact(More)