作者：
Koo, JaehyunMIT
77 Massachusetts Ave Cambridge MA 02139 USA
We present an O(1)-round fully-scalable deterministic massively parallel algorithm for computing the min-plus matrix multiplication of unit-Monge matrices. We use this to derive a O(log n)-round fully-scalable massive...
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ISBN:
(纸本)9798400704161
We present an O(1)-round fully-scalable deterministic massively parallel algorithm for computing the min-plus matrix multiplication of unit-Monge matrices. We use this to derive a O(log n)-round fully-scalable massively parallel algorithm for solving the exact longest increasing subsequence (LIS) problem. For a fully-scalable MPC regime, this result substantially improves the previously known algorithm of O(log(4) n)-round complexity, and matches the best algorithm for computing the (1 + epsilon)-approximation of LIS.
We describe a new randomized parallel algorithm for computing the planar convex hull of n points on a p processor-memory pair machine communicating through a network for which O(log p) routing is possible. We show tha...
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We describe a new randomized parallel algorithm for computing the planar convex hull of n points on a p processor-memory pair machine communicating through a network for which O(log p) routing is possible. We show that the algorithm has optimal O(n log n/p) performance provided that p = o(n/log3n). We report extensive computational experience with the algorithm which supports its theoretical claims.
We describe a randomized CRCW PRAM algorithm that finds a minimum spanning forest of an n-vertex graph in O(log n) time and linear work. This shaves a factor of 2log* n off the best previous running time for a linear-...
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ISBN:
(纸本)9780897918091
We describe a randomized CRCW PRAM algorithm that finds a minimum spanning forest of an n-vertex graph in O(log n) time and linear work. This shaves a factor of 2log* n off the best previous running time for a linear-work algorithm. The novelty in our approach is to divide the computation into two phases, the first of which finds only a partial solution. This idea has been used previously in parallel connected components algorithms.
In this paper, we present a dynamic load-balancing algorithm for parallel digital logic simulation making use of reinforcement learning We first introduce two dynamic load-balancing algorithms oriented towards balanci...
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ISBN:
(纸本)9781450300797
In this paper, we present a dynamic load-balancing algorithm for parallel digital logic simulation making use of reinforcement learning We first introduce two dynamic load-balancing algorithms oriented towards balancing the computational and communication load respectively and then utilize reinforcement learning to create an algorithm which is a combination of the first two algorithms In addition, the algorithm determines the value of two important parameters the number of processors which participate in the algorithm and the load which is exchanged during its execution. We investigate the algorithms on gate level simulations of several open source VLSI circuits
作者：
AnonACM
Special Interest Group for Automata and Computability Theory New York NY USA ACM Special Interest Group for Automata and Computability Theory New York NY USA
This conference proceedings contains 50 papers. The topics covered include: algorithms;graph theory;parallel processing;automata;boolean circuits;computational geometry;cryptography;complexity;distributed computing.
This conference proceedings contains 50 papers. The topics covered include: algorithms;graph theory;parallel processing;automata;boolean circuits;computational geometry;cryptography;complexity;distributed computing.
This paper presents an engineering design for a low latency high bandwidth interconnection network which will form the switching substrate for a multi-model parallel processing system. The performance is enhanced with...
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This paper introduces the Asynchronous PRAM model of computation, a variant of the PRAM in which the processors run asynchronously and there is an explicit charge for synchronization. A family of asynchronous PRAM'...
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