![]() Prins, J., et al.: UPC implementation of an unbalanced tree search benchmark. PARAVER (2006), Available at Ĭhen, W., Iancu, C., Yelick, K.A.: Communication optimizations for fine-grained UPC applications. Springer, Heidelberg (2004)Įuropean Center for Parallelism. ACM Press, New York (2006)īerlin, K., et al.: Evaluating the impact of programming language features on the performance of parallel applications on cluster architectures. Marathe, J., Mueller, F.: Hardware profile-guided automatic page placement for ccnuma systems. of the benchmark The goal of the unbalanced tree search benchmark (UTS) is to. Comp./Int’l Workshop Algorithms, Models and Tools for Par. We then examine the performance of the UPC implementation on a number of. Marowka, A.: Analytic comparison of two advanced c language-based parallel programming models. LBNL-59208 (2005)įrigo, M., Leiserson, C.E., Randall, K.H.: The implementation of the Cilk-5 multithreaded language. Kumar, V., Rao, V.N.: Parallel depth first search. Kumar, V., Grama, A.Y., Vempaty, N.R.: Scalable load balancing techniques for parallel computers. ACM Press, New York (2005)īlumofe, R., Leiserson, C.: Scheduling multithreaded computations by work stealing. Leskovec, J., Kleinberg, J., Faloutsos, C.: Graphs over time: densification laws, shrinking diameters and possible explanations. Internet Engineering Task Force, RFC 3174 (Sept. Springer, Heidelberg (1963)Įastlake, D., Jones, P.: US secure hash algorithm 1 (SHA-1). Harris, T.: The Theory of Branching Processes. This process is experimental and the keywords may be updated as the learning algorithm improves. These keywords were added by machine and not by the authors. By varying key work stealing parameters, we expose important tradeoffs between the granularity of load balance, the degree of parallelism, and communication costs. Since dynamic load balancing requires intensive communication, performance portability remains difficult for applications such as UTS and performance degrades on PC clusters. However, UPC cannot alleviate the underlying communication costs of distributed-memory systems. Results show that both UPC and OpenMP can support efficient dynamic load balancing on shared-memory architectures. We found it simple to implement UTS in both UPC and OpenMP, due to UPC’s shared-memory abstractions. We benchmarked the performance of UTS on various parallel architectures, including shared-memory systems and PC clusters. We created versions of UTS in two parallel languages, OpenMP and Unified Parallel C (UPC), using work stealing as the mechanism for reducing load imbalance. Our approach demonstrates low overheads and improved performance (relative to MPI and UPC versions) for up to 12288 cores on the NERSC Edison system. ![]() as exempli ed by the UTS and NQueens benchmarks. We describe algorithms for building a variety of unbalanced search trees to simulate different forms of load imbalance. Lawrence Berkeley National Laboratory, Berkeley, California Vivek Sarkar. This paper presents an unbalanced tree search (UTS) benchmark designed to evaluate the performance and ease of programming for parallel applications requiring dynamic load balancing.
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