In this paper we develop models for and analyze several randomized work stealing algorithms in a dynamic setting. Our models represent the limiting behavior of systems as the number of processors grows to infinity usi...
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ISBN:
(纸本)9780897919890
In this paper we develop models for and analyze several randomized work stealing algorithms in a dynamic setting. Our models represent the limiting behavior of systems as the number of processors grows to infinity using differential equations. the advantages of this approach include the ability to model a large variety of systems and to provide accurate numerical approximations of system behavior even when the number of processors is relatively small. We show how this approach can yield significant intuition about the behavior of work stealing algorithms in realistic settings.
Partitioning a graph into blocks of roughly equal weight while cutting only few edges is a fundamental problem in computer science with numerous practical applications. While shared-memory parallel partitioners have r...
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ISBN:
(纸本)9798400704161
Partitioning a graph into blocks of roughly equal weight while cutting only few edges is a fundamental problem in computer science with numerous practical applications. While shared-memory parallel partitioners have recently matured to achieve the same quality as widely used sequential partitioners, there is still a pronounced quality gap between distributed partitioners and their sequential counterparts. In this work, we shrink this gap considerably by describing the engineering of an unconstrained local search algorithm suitable for distributed partitioners. We integrate the proposed algorithm in a distributed multilevel partitioner. Our extensive experiments show that the resulting algorithm scales to thousands of PEs while computing cuts that are, on average, only 3.5% larger than those of a state-of-the-art high-quality shared-memory partitioner. Compared to previous distributed partitioners, we obtain on average 6.8% smaller cuts than the best-performing competitor while being more than 9 times faster.
there are many algorithms to solve large sparse linear systems in parallel;however, most of them acquire synchronization and thus are lack of scalability. In this paper, we propose a new distributed numerical algorith...
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ISBN:
(纸本)9781595939739
there are many algorithms to solve large sparse linear systems in parallel;however, most of them acquire synchronization and thus are lack of scalability. In this paper, we propose a new distributed numerical algorithm, called Directed Transmission Method (DTM). DTM is a fully asynchronous, scalable and continuous-time iterative algorithm to solve the arbitrarily-large sparse linear system whose coefficient matrix is symmetric-positive-definite (SPD). DTM is able to be freely running on the heterogeneous parallel computer with arbitrary number of processors, which might be manycore microprocessors, clusters, grids, clouds, and the Internet. We proved that DTM is convergent by making use of the final value theorem of Laplacian Transformation. Numerical experiments show that DTM is efficient.
Dynamic trees are a well-studied and fundamental building block of dynamic graph algorithms dating back to the seminal work of Sleator and Tarjan [STOC'81, (1981), pp. 114-122]. the problem is to maintain a tree s...
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ISBN:
(纸本)9798400704161
Dynamic trees are a well-studied and fundamental building block of dynamic graph algorithms dating back to the seminal work of Sleator and Tarjan [STOC'81, (1981), pp. 114-122]. the problem is to maintain a tree subject to online edge insertions and deletions while answering queries about the tree, such as the heaviest weight on a path, etc. In the parallel batch-dynamic setting, the goal is to process batches of edge updates work efficiently in low (polylog n) span. Two work-efficient algorithms are known: batch-parallel Euler Tour Trees by Tseng et al. [ALENEX'19, (2019), pp. 92-106] and parallel Rake-Compress (RC) Trees by Acar et al. [ESA'20, (2020), pp. 2:1-2:23]. Both however are randomized and work efficient in expectation. Several downstream results that use these data structures (and indeed to the best of our knowledge, all known workefficient parallel batch-dynamic graph algorithms) are therefore also randomized. In this work, we give the first deterministic work-efficient solution to the problem. Our algorithm maintains a parallel RC-Tree on n vertices subject to batches of k edge updates deterministically in worst-case O(k log(1 + n/k)) work and O(log n log log k) span on the Common-CRCW PRAM. We also show how to improve the span of the randomized algorithm from O(log n log* n) to O(log n). Lastly, as a result of our new deterministic algorithm, we also derandomize several downstream results that make use of parallel batch-dynamic dynamic trees, previously for which the only efficient solutions were randomized.
Using the ideas from the NC algorithm of Ben-Or and Tiwari [Journal of Complexity 6, 417-442, 1990], we develop a practical parallel algorithm that approximates the roots of a polynomial whose roots are all real. A ne...
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ISBN:
(纸本)089791483X
Using the ideas from the NC algorithm of Ben-Or and Tiwari [Journal of Complexity 6, 417-442, 1990], we develop a practical parallel algorithm that approximates the roots of a polynomial whose roots are all real. A new elementary proof of correctness is provided and the complexity of the algorithm is analyzed. A particular implementation of the algorithm that performs well in practice is described and its run-time behaviour is compared withthe analytical predictions. Its performance is also compared withthat of the root-finding algorithm in the PARI package.
Recently there has been an increasing interest in models of parallel computation that account for the bandwidth limitations in communication networks. Some models (e.g., BSP and LOGP) account for bandwidth limitations...
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Recently there has been an increasing interest in models of parallel computation that account for the bandwidth limitations in communication networks. Some models (e.g., BSP and LOGP) account for bandwidth limitations using a per-processor parameter g>1, such that each processor can send/receive at most h messages in g·h time. Other models (e.g., PRAM(m)) account for bandwidth limitations as an aggregate parameter mΩ(√lg p) separation known previously.
Gang scheduling is a resource management scheme for parallel and distributed systems that combines time-sharing with space-sharing to ensure short response times for interactive tasks and high overall system throughpu...
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Gang scheduling is a resource management scheme for parallel and distributed systems that combines time-sharing with space-sharing to ensure short response times for interactive tasks and high overall system throughput. In this paper, we present and analyze a queueing theoretic model for a general gang scheduling scheme that forms the basis of a multiprogramming environment currently being developed for IBM's SP2 parallel system and for clusters of workstations. Our model and analysis can be used to tune our scheduler in order to maximize its performance on each hardware platform.
this paper describes the derivation of an empirically efficient parallel two-dimensional Delaunay triangulation program from a theoretically efficient CREW PRAM algorithm. Compared to previous work, the resulting impl...
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ISBN:
(纸本)9780897918909
this paper describes the derivation of an empirically efficient parallel two-dimensional Delaunay triangulation program from a theoretically efficient CREW PRAM algorithm. Compared to previous work, the resulting implementation is not limited to datasets with a uniform distribution of points, achieves significantly better speedups over good serial code, and is widely portable due to its use of MPI as a communication mechanism. Results are presented for a loosely-coupled cluster of workstations, a distributed-memory multicomputer, and a shared-memory multiprocessor. the Machiavelli toolkit used to transform the nested data parallelism inherent in the divide-and-conquer algorithm into achievable task and data parallelism is also described and compared to previous techniques.
this paper experimentally validates performance related issues for parallel computation models on several parallel platforms (a MasPar MP-1 with 1024 processors, a 64-node GCel and a CM-5 of 64 processors). Our work c...
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this paper experimentally validates performance related issues for parallel computation models on several parallel platforms (a MasPar MP-1 with 1024 processors, a 64-node GCel and a CM-5 of 64 processors). Our work consists of three parts. First, there is an evaluation part in which we investigate whether the models correctly predict the execution time of an algorithm implementation. Unlike previous work, which mostly demonstrated a close match between the measured and predicted running times, this paper shows that there are situations in which the models do not precisely predict the actual execution time of an algorithm implementation. Second, there is a comparison part in which the models are contrasted with each other in order to determine which model induces the fastest algorithms. Finally, there is an efficiency validation part in which the performance of the model derived algorithms are compared withthe performance of highly optimized library routines to show the effectiveness of deriving fast algorithmsthrough the formalisms of the models.
the issue of effectiveness of private caches for processors were studied. Since time for all processors to access the shared memory simultaneously is usually much longer than the time for a processor to access its own...
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ISBN:
(纸本)9780897918091
the issue of effectiveness of private caches for processors were studied. Since time for all processors to access the shared memory simultaneously is usually much longer than the time for a processor to access its own private cache, scheduling with private caches falls into the distributed memory model where the lower bound applies. the effectiveness of private caches were shown by proving that a version of Dynamic Equi-partition Scheduling Policy (DEQ) achieves a mean response time with five times the optimal mean response time in the cache clock time for a large class of parallel jobs well accepted in the parallel scheduling community. this shows an improvement of system performance by using private caches over that of purely shared memory.
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