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Optimal parallel algorithms for Dendrogram Computation and Single-Linkage Clustering 24

Optimal Parallel Algorithms for Dendrogram Computation and S...

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36th acm symposium on parallelism in algorithms and architectures (SPAA)

作者： Dhulipala, Laxman Dong, Xiaojun Gowda, Kishen N. Gu, Yan Univ Maryland College Pk MD 20742 USA Univ Calif Riverside Riverside CA 92521 USA

ISBN: (纸本)9798400704161

Computing a Single-Linkage Dendrogram (SLD) is a key step in the classic single-linkage hierarchical clustering algorithm. Given an input edge-weighted tree), the SLD of) is a binary dendrogram that summarizes the n = 1 clusterings obtained by contracting the edges of T in order of weight. Existing algorithms for computing the SLD all require Omega(n log n) work where n = vertical bar T vertical bar. Furthermore, to the best of our knowledge no prior work provides a parallel algorithm obtaining non-trivial speedup for this problem. In this paper, we design faster parallel algorithms for computing SLDs both in theory and in practice based on new structural results about SLDs. In particular, we obtain a deterministic output-sensitive parallel algorithm based on parallel tree contraction that requires O(n log h) work and O(log(2) n log(2) h) depth, where h is the height of the output SLD. We also give a deterministic bottom-up algorithm for the problem inspired by the nearest-neighbor chain algorithm for hierarchical agglomerative clustering, and show that it achieves O(n log h) work and O(h log n) depth. Our results are based on a novel divide-and-conquer framework for building SLDs, inspired by divide-and-conquer algorithms for Cartesian trees. Our new algorithms can quickly compute the SLD on billion-scale trees, and obtain up to 150x speedup over the highly-efficient Union-Find algorithm typically used to compute SLDs in practice.

关键词： Single-Linkage Clustering Hierarchical Graph Clustering HAC Dendrograms parallel algorithms

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Dynamic load balancing framework for unstructured adaptive computations on distributed-memory multiprocessors

Dynamic load balancing framework for unstructured adaptive c...

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proceedings of the 1996 8th annual acm symposium on parallel algorithms and architectures

作者： Sohn, Andrew Biswas, Rupak Simon, Horst D. New Jersey Inst of Technology Newark United States

The computational requirements for an adaptive solution of unsteady problems change as the simulation progresses. This causes workload imbalance among processors on a parallel machine which, in turn, requires significant data movement at runtime. We present a dynamic load-balancing framework, called JOVE, that balances the workload across all processors with a global view each time the computational mesh is adapted. JOVE has been implemented on an SP2 in MPI for portability. Experimental results for two model meshes demonstrate that mesh adaption with load balancing gives more than a sixfold improvement over one without load balancing. Furthermore, JOVE gives a 24-fold speedup on 64 processors compared to sequential execution.

关键词： parallel processing systems

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SPAA 2020 - proceedings of the 32nd acm symposium on parallelism in algorithms and architectures

SPAA 2020 - Proceedings of the 32nd ACM Symposium on Paralle...

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32nd acm symposium on parallelism in algorithms and architectures, SPAA 2020

ISBN: (纸本)9781450369350

The proceedings contain 68 papers. The topics discussed include: faster deterministic all pairs shortest paths in congest model;contention resolution with message deadlines;memory tagging: minimalist synchronization for scalable concurrent data structures;work-efficient batch-incremental minimum spanning trees with applications to the sliding-window model;closing the gap between cache-oblivious and cache-adaptive analysis;optimal resource allocation for elastic and inelastic jobs;optimal parallel algorithms in the binary-forking model;randomized incremental convex hull is highly parallel;almost universal anonymous rendezvous in the plane;the online multi-commodity facility location problem;unconditional lower bounds for adaptive massively parallel computation;on the hardness of massively parallel computation;and graph sparsification for derandomizing massively parallel computation with low space.

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An implementation of the e-relaxation algorithm on the CM-5 5

An implementation of the e-relaxation algorithm on the CM-5

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5th annual acm symposium on parallel algorithms and architectures, SPAA 1993

作者： Narendran, B. De Leone, Renato Tiwari, Prasoon Computer Sciences Department University of Wisconsin-Madison MadisonWI53706 United States

ISBN: (纸本)0897915992

This paper discusses a parallel implementation of the e-relaxation algorithm for the min-cost flow problem on the CM-5. There is considerable loss in efficiency in going from one processor sequential implementation to one processor parallel implementation. While a naive parallelization is shown to have very low parallelism, we investigate the effectiveness of a set of algorithmic augmentations. These augmentations work by either eliminating non-parallel iterations or increasing the parallelism of the remaining iterations. Although the size of memory on the machine limits the size of problems used in our experiments, experimental scalability data shows that the parallel implementation may be able to beat the best sequential implementation on large enough problems. © 1993 acm.

关键词： parallel processing systems

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Efficient disk allocation for fast similarity searching 98

Efficient disk allocation for fast similarity searching

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proceedings of the 1998 10th annual acm symposium on parallel algorithms and architectures, SPAA

作者： Prabhakar, S. Agrawal, D. El Abbadi, A. Univ of California Santa Barbara CA United States

ISBN: (纸本)9780897919890

As databases increasingly integrate non-textual information it is becoming necessary to support efficient similarity searching in addition to range searching. Recently, declustering techniques have been proposed for improving the performance of similarity searches through parallel I/O. In this paper, we propose a new scheme which provides good declustering for similarity searching. In particular, it does global declustering as opposed to local declustering, exploits the availability of extra disks and does not limit the partitioning of the data space. Our technique is based upon the Cyclic declustering schemes which were developed for range and partial match queries. We establish, in general, that Cyclic declustering techniques outperform previously proposed techniques.

关键词： parallel algorithms

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Lower bounds for parallel computation on linked structures 90

Lower bounds for parallel computation on linked structures

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SPAA '90 - proceedings of the 2nd annual acm symposium on parallel algorithms and architectures

作者： Fich, Faith E. Univ of Toronto Toronto Ont Canada

ISBN: (纸本)0897913701

The time required to compute any function of a collection of circular doubly linked lists on a CROW PRAM is shown to be at most a constant factor more than on a CREW PRAM, but this is not true for singly linked lists. A tight lower bound of Ω(log log n) for colouring an n node doubly linked list on a CROW PRAM using a constant number of colours is also obtained.

关键词： Computer programming

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Scan grammars: parallel attribute evaluation via data-parallelism 93

Scan grammars: Parallel attribute evaluation via data-parall...

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5th annual acm symposium on parallel algorithms and architectures, SPAA 1993

作者： Reps, Thomas University of Wisconsin United States

ISBN: (纸本)0897915992

This paper concerns the problem of how to exploit parallelism during the phases of compilation involving syntax-directed analysis and translation. In particular, we address the problem of how to exploit parallelism during the evaluation of the attributes of a derivation tree of a non-circular attribute grammar. What distinguishes the ideas presented in this paper from earlier work on parallel attribute evaluation is the use of a data-parallel model: We define a new variant of attribute grammars, called scan grammars, that incorporates a data-parallel attribution construct. © 1993 acm.

关键词： Context sensitive grammars

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Efficient parallel Reinforcement Learning Framework Using the Reactor Model 24

Efficient Parallel Reinforcement Learning Framework Using th...

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36th acm symposium on parallelism in algorithms and architectures (SPAA)

作者： Kwok, Jacky Lohstroh, Marten Lee, Edward A. Univ Calif Berkeley Berkeley CA 94720 USA

ISBN: (纸本)9798400704161

parallel Reinforcement Learning (RL) frameworks are essential for mapping RL workloads to multiple computational resources, allowing for faster generation of samples, estimation of values, and policy improvement. These computational paradigms require a seamless integration of training, serving, and simulation workloads. Existing frameworks, such as Ray, are not managing this orchestration efficiently, especially in RL tasks that demand intensive input/output and synchronization between actors on a single node. In this study, we have proposed a solution implementing the reactor model, which enforces a set of actors to have a fixed communication pattern. This allows the scheduler to eliminate work needed for synchronization, such as acquiring and releasing locks for each actor or sending and processing coordination-related messages. Our framework, Lingua Franca (LF), a coordination language based on the reactor model, also supports true parallelism in Python and provides a unified interface that allows users to automatically generate dataflow graphs for RL tasks. In comparison to Ray on a single-node multi-core compute platform, LF achieves 1.21x and 11.62x higher simulation throughput in OpenAI Gym and Atari environments, reduces the average training time of synchronized parallel Q-learning by 31.2%, and accelerates multi-agent RL inference by 5.12x.

关键词： parallel Computing Reinforcement Learning Programming Languages Machine Learning Model of Computation

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Unified approach to off-line permutation routing on parallel networks

Unified approach to off-line permutation routing on parallel...

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SPAA '90 - proceedings of the 2nd annual acm symposium on parallel algorithms and architectures

作者： Annexstein, Fred Baumslag, Marc Univ of Massachusetts Amherst United States

ISBN: (纸本)0897913701

A unified framework for finding efficient permutation routes on parallel networks in an off-line setting is presented. If the underlying graph of a parallel network contains an appropriate 'approximate' product structure then our method guarantees the existence of non-blocking near-optimal permutation routes. The routes in question can be determined in polynomial time. Furthermore, our results are extended to finding permutation routes among the remaining 'live' nodes in a faulty network.

关键词： Computer Systems, Digital

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Brief Announcement: Low Depth Cache-Oblivious Sorting 09

Brief Announcement: Low Depth Cache-Oblivious Sorting

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21st acm symposium on parallelism in algorithms and architectures

作者： Blelloch, Guy E. Gibbons, Phillip B. Simhadri, Harsha Vardhan Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781605586069

Cache-oblivious algorithms have the advantage of achieving good sequential cache complexity across all levels of a multi-level cache hierarchy, regardless of the specifies (cache size and cache line size) of each level. In this paper, we describe cache-oblivious sorting algorithms with optimal work, optimal cache complexity and polylogarithmic depth. Using known mappings, these lead to low cache complexities on shared-memory multiprocessors with a single level of private caches or a single shared cache. Moreover, the low cache complexities extend to shared-memory multiprocessors with common configurations of multi-level caches. The key factor in the low cache complexity on multiprocessors is the low depth of the algorithms we propose.

关键词： Cache-oblivious algorithms sorting parallel algorithms multiprocessors schedulers

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