In this paper, we study the tradeoffs between the time and the number of communication rounds of the best arm identification problem in the heterogeneous collaborative learning model, where multiple agents interact wi...
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ISBN:
(纸本)9798400704161
In this paper, we study the tradeoffs between the time and the number of communication rounds of the best arm identification problem in the heterogeneous collaborative learning model, where multiple agents interact with possibly different environments and they want to learn in parallel an objective function in the aggregated environment. By proving almost tight upper and lower bounds, we show that collaborative learning in the heterogeneous setting is inherently more difficult than that in the homogeneous setting in terms of the time-round tradeoff.
The proceedings contains 48 papers from Thirteen annualacmsymposium on parallelalgorithms and architectures. Topics discussed include: compact routing schemes;simple on-line algorithms for the maximum disjoint path...
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The proceedings contains 48 papers from Thirteen annualacmsymposium on parallelalgorithms and architectures. Topics discussed include: compact routing schemes;simple on-line algorithms for the maximum disjoint paths problem;competitive buffer management for shared-memory switches;attack propagation in networks;computational power of pipelined memory hierarchies;and a data tracking scheme for general networks.
We address optimal makespan-minimizing identical parallel machine scheduling (P vertical bar vertical bar C-max) by introducing new pruning rules for branch-and-bound (BnB) and integrating them into a prior BnB algori...
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ISBN:
(纸本)9798400704161
We address optimal makespan-minimizing identical parallel machine scheduling (P vertical bar vertical bar C-max) by introducing new pruning rules for branch-and-bound (BnB) and integrating them into a prior BnB algorithm. Experimental results indicate that the presented rules are inexpensive to evaluate, applicable frequently, and extremely beneficial to the BnB algorithm's overall performance.
We present the first (randomized) parallel dynamic algorithm for maximal matching, which can process an arbitrary number of updates simultaneously. Given a batch of edge deletion or insertion updates to the graph, our...
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ISBN:
(纸本)9798400704161
We present the first (randomized) parallel dynamic algorithm for maximal matching, which can process an arbitrary number of updates simultaneously. Given a batch of edge deletion or insertion updates to the graph, our parallel algorithm adjusts the maximal matching to these updates in poly(log n) depth and using poly(log n) amortized work per update. That is, the amortized work for processing a batch of k updates is k poly(log n), while all this work is done in poly(log n) depth, with high probability. This can be seen as a parallel counterpart of the sequential dynamic algorithms for constant-approximate and maximal matching [Onak and Rubinfeld STOC'10;Baswana, Gupta, and Sen FOCS'11;and Solomon FOCS'16]. Our algorithm readily generalizes to maximal matching in hypergraphs of rank r-where each hyperedge has at most r endpoints-with a poly(r) increase in work, while retaining the poly(log n) depth.
We introduce Autonomous SIMD (ASIMD) massively parallel architecture, then look at the flexibility, cost, and effectiveness of MIMD and ASIMD parallel systems. We show that ASIMD systems such as the MasPar MP-1 and MP...
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We introduce PASGAL (parallel And Scalable Graph Algorithm Library), a parallel graph library that scales to a variety of graph types, many processors, and large graphs. One special focus of PASGAL is the efficiency o...
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ISBN:
(纸本)9798400704161
We introduce PASGAL (parallel And Scalable Graph Algorithm Library), a parallel graph library that scales to a variety of graph types, many processors, and large graphs. One special focus of PASGAL is the efficiency on large-diameter graphs, which is a common challenge for many existing parallel graph processing systems due to the high overhead in synchronizing threads when traversing the graph in the breadth-first order. The core idea in PASGAL is a technique called vertical granularity control (VGC) to hide synchronization overhead by careful algorithm redesign and new data structures. We compare PASGAL with existing parallel implementations on several fundamental graph problems. PASGAL is always competitive on small-diameter graphs, and is significantly faster on large-diameter graphs.
Energy consumption by computer systems has emerged as an important concern However, the energy consumed in executing an algorithm cannot be inferred from its performance alone it must be modeled explicitly This paper ...
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ISBN:
(纸本)9781450300797
Energy consumption by computer systems has emerged as an important concern However, the energy consumed in executing an algorithm cannot be inferred from its performance alone it must be modeled explicitly This paper analyzes energy consumption of parallelalgorithms executed on shared memory multicore processors Specifically, we develop a methodology to evaluate how energy consumption of a given parallel algorithm changes as the number of cores and their frequency is varied We use this analysis to establish the optimal number of cores to minimize the energy consumed by the execution of a parallel algorithm for a specific problem size while satisfying a given performance requirement We study the sensitivity of our analysis to changes in parameters such as the ratio of the power consumed by a computation step versus the power consumed in accessing memory The results show that the relation between the problem size and the optimal number of cores is relatively unaffected for a wide range of these parameters.
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