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74743

Published
**1986** by Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, National Technical Information Service, distributor in Hampton, VA, [Springfield, Va .

Written in English

Read online**Edition Notes**

Statement | David M. Nicol |

Series | ICASE report -- no. 86-53, ICASE report -- no. 86-53, NASA contractor report -- 178159, NASA contractor report -- NASA CR-178159 |

Contributions | Institute for Computer Applications in Science and Engineering |

The Physical Object | |
---|---|

Format | Microform |

Pagination | 1 v |

ID Numbers | |

Open Library | OL14985342M |

**Download Optimal partitioning of random programs across two processors**

Indurkhya et al. () concluded that the optimal partitioning of a homogeneous random program over a homogeneous distributed system either assigns all modules to a single processor or.

Get this from a library. Optimal partitioning of random programs across two processors. [David M Nicol; Institute for Computer Applications in Science and Engineering.].

DeFlumere, A., Lastovetsky, A.: Theoretical results on optimal partitioning for matrix matrix multiplication on three fully connected heterogeneous processors. School of Computer Science and Informatics, University College Dublin, Tech.

Rep. UCD-CSI () Google ScholarCited by: 5. Optimal Partitioning for Parallel Matrix Computation on a Small Number of Abstract Heterogeneous Processors Ashley DeFlumere UCD Student Number: This thesis is submitted to University College Dublin in ful lment of the requirements for the degree of Doctor of Philosophy in Computer Science School of Computer Science and Informatics.

Carlson. Department of Computer Science, Vanderbilt University, P.O. BoxStation B, Nashville, TN. MBR stands for Master Boot Record. Most legacy disks are MBR disks. MBR disks store partition information in the MBR, hence the name. This information is generally stored in the first sector of the disk.

rithm that ﬁnds an optimal partition Pmax ∈ P∗: V(Pmax) ≥ V(P) for all partitions P ∈ P∗. Scargle [21] proposed two greedy iterative algorithms for ﬁnding near-optimal partitions: one top-down (optimally di-vide I into two parts; recursively do the same to each such.

Figure 5 shows an example of generating a partition-ing graph. The two root nodes represent two partitions of the sampled input data. The Cost Optimization module inserts an additional partition stage into the current EPG to greedily search for an optimized partitioning scheme.

First, the two inputs are split into 8 initial partitions by. One of the key problems in hardware/software codesign is hardware/software partitioning. This paper describes a new approach to hardware/software partitioning using integer programming (IP).

The advantage of using IP is that optimal results are calculated for a chosen objective function. The partitioning approach works fully automatic and supports multi-processor systems, Cited by: For GraphX, all partitioning strategies have similar par-titioning speed, i.e., the partitioning phases took roughly the same amount of time.

So, the choice of partitioning strat-egy is based primarily on computation time. Our results indicate that Canonical Random works well with low degree graphs, and 2D edge partitioning with power-law graphs. Graph partitioning has several important applications in Computer Science, including VLSI circuit layout [8], image processing [43], solving sparse linear systems, computing ﬁll-reducing orderings for sparse matrices, and distributing workloads for parallel computation.

Unfortunately, graph partitioning is an NP-hardproblem [13], and. An Experimental Comparison of Partitioning Strategies in Distributed Graph Processing Shiv Verma1, Luke M.

Leslie1, Yosub Shin2, Indranil Gupta1 1 University of Illinois at Urbana-Champaign, Urbana, IL, USA 2 Samsara Inc., San Francisco, CA, USA fsverma11, [email protected], [email protected], [email protected] y ABSTRACT In this paper, we study the problem of choosing among par-Cited by: The book presents two approaches to automatic partitioning and scheduling so that the same parallel program can be made to execute efficiently on widely different multiprocessors.

The first approach is based on a macro dataflow model in which the program is partitioned into tasks at compile time and the tasks are scheduled on processors at run by: Optimal design of an elec-tric water pump demonstrate the ideas on a physically meaning-ful design problem.

2 Partitioning and Coordination Decision-Making System partitioning often follows physical or disciplinary system boundaries [13]; or product, process, or organization divisions [9] [10]. Formal partitioning approaches using FDT. Thanks for contributing an answer to Computer Science Stack Exchange.

Please be sure to answer the question. Provide details and share your research. But avoid Asking for help, clarification, or responding to other answers.

Making statements based on opinion; back them up with references or personal experience. Use MathJax to format equations. The concept of partition was first proposed by Sacca and Wiederhold. Their study, which focusses on a cluster of processors, indicated that "in a distributed database system, the partitioning and.

We develop an optimal partitioning strategy based on dynamic programming and a distribution function (DF) of non-zero elements to improve the performance of SpMV. We present a reordering algorithm in which the time complexity is only O (N log 2 k), where k is the number of partitions and far less than the number of by: 4.

The idea of a two processor partition composed of a small square and the non-rectangular remainder of the matrix is discussed previously in [9] and [10]. In this paper, however, we approach this not as a problem of whether the Square-Corner partition is superior to the rectangular under certain conﬁgurations, but what is the optimal partition.

1 Spinner: Scalable Graph Partitioning in the Cloud Claudio Martella, Dionysios Logothetis, Andreas Loukas, and Georgos Siganos Abstract—Several organizations, like social networks, store and routinely analyze large graphs as part of their daily operation.

Such graphs are typically distributed across multiple servers, and. On an MBR disk, the partitioning and boot data is stored in one place. If this data is overwritten or corrupted, you’re in trouble.

In contrast, GPT stores multiple copies of this data across the disk, so it’s much more robust and can recover if the data is corrupted. GPT also stores cyclic redundancy check (CRC) values to check that its.

I've created a topic in Kafka with 9 partitions, naming it aptly 'test', and knocked together two simple applications in C# .NET Core), using client library: a producer and a consumer.

I did little more than tweak examples from the documentation. I am running two instances of the consumer application and one instance of the producer. So count_partitions(n, limit) counts the number of partitions of n into parts less than or equal to limit.

Okay, I see how you're counting that. And then, given a bijection between the integers 1,count_partitions(n,n) and the partitions of n, random_partition chooses one of those integers and constructs the corresponding partition. And, in this case, the only time the data has to be moved is when the final reduce values have to be sent back from the worker nodes to the driver node.

The other common scenario here has to do with pre-partitioning before doing joins. So, we can completely avoid shuffling by pre-partitioning the two joined RDDs with the same partitioner. So for optimal performance, create partitions, or subpartitions per partition, using a power of two.

For example, 2, 4, 8, 16, 32, 64,and so on. The following example creates four hashed partitions for the table Sales using the column s_productid as the partition key. programs with arbitrary nestings and sequences of loops, whose array indices and loop bounds are affine expressions of outer loop indices.

In this model, every instruction is given its own affine partition that divides the instances of the instruction across the processors or across time stages. More specifically, instances of each instruction are.

In number theory and computer science, the partition problem, or number partitioning, is the task of deciding whether a given multiset S of positive integers can be partitioned into two subsets S 1 and S 2 such that the sum of the numbers in S 1 equals the sum of the numbers in S gh the partition problem is NP-complete, there is a pseudo-polynomial time dynamic programming solution.

Physical table partitioning involves the division of one table into two or more smaller tables. This requires application changes to use the new names of the smaller tables. Report programs must also change so they can join the smaller tables as needed to provide data.

However, Oracle can automatically manage partition independence for you. Database Partitioning, Table Partitioning, and MDC for DB2 9 Whei-Jen Chen Alain Fisher Aman Lalla Andrew D McLauchlan Doug Agnew Differentiating database partitioning, table partitioning, and MDC Examining implementation examples Discussing best practices Front coverFile Size: 2MB.

Select the best way to determine your RAM allocation. Monitor RAM usage in performance monitor and calculate an average of RAM used over 10 random periods. List all programs you would run simultaneously and the amount of RAM each needs and add together.

Divide the number of used memory slots by the number of total memory slots. Abstract—Hardware/software (HW/SW) partitioning and task scheduling are the crucial steps of HW/SW co-design.

It is very difficult to achieve the optimal solution as both scheduling and partitioning are combinatorial optimization problems.

In this paper a heuristic solution is proposed for scheduling and partitioning on multi-processor system. An alternate method of load balancing, which does not require a dedicated software or hardware node, is called round-robin this technique, multiple IP addresses are associated with a single domain name; clients are given IP in a round-robin is assigned to clients with a short expiration so the client is more likely to use a different IP the next time they access the Internet.

Given an array and a range [lowVal, highVal], partition the array around the range such that array is divided in three parts.1) All elements smaller than lowVal come first. 2) All elements in range lowVal to highVVal come next. 3) All elements greater than highVVal appear in the end.

The individual elements of three sets can appear in any order/5. For a given set of random networks, we consider two performance metrics: first, the fraction of networks, Θ, for which the QCQP approach saves the same number of susceptible nodes from infection as the optimal partition, which provides a measure of how often our method identifies an optimal partition; and second, the fraction of susceptible Cited by: We introduce the Convex Hull of Admissible Modularity Partitions (CHAMP) algorithm to prune and prioritize different network community structures identified across multiple runs of possibly various computational heuristics.

Given a set of partitions, CHAMP identifies the domain of modularity optimization for each partition—i.e., the parameter-space domain where it has the largest modularity Cited by: $\begingroup$ This algorithm can generate each partition with their elements ordered from greatest to least - it's just a matter of prepending x to the partitions obtained from the recursive call.

Or it can generate them ordered from least to greatest - postpend. $\endgroup$ – Peter Taylor Jan 24 '11 at PostgreSQL offers a way to specify how to divide a table into pieces called partitions.

The table that is divided is referred to as a partitioned specification consists of the partitioning method and a list of columns or expressions to be used as the partition key. All rows inserted into a partitioned table will be routed to one of the partitions based on the value of the partition key.

An Experimental Comparison of Partitioning Strategies in Distributed Graph Processing [Experiments and Analyses] Shiv Verma1, Luke M. Leslie1, partitioning strategy is the best t for all situations, and Unlike edges which could be cut across only two partitions, a vertex can be cut across.

Efficient use of a distributed memory parallel computer requires that the computational load be balanced across processors in a way that minimizes interprocessor communication. Spectral Graph Partitioning Based on a Random Walk Diffusion Similarity Measure.

Computer Vision – ACCVSIAM Journal on Scientific Computing 21 Cited by: But I am not really interested in THE optimal solution. I am interested in a FAST algorithm that generates some good partition wrt the criterion.

Let us say a set is [1,23,12,16,22] and needs to be divided 3-ways. When partitioning we try to minimize the max difference between the size of all subsets.

new approach to hardware/software partitioning for synchronous com-munication model. We transform the partitioning into a reachability problem of timed automata.

By means of an optimal reachability al-gorithm, an optimal solution can be obtained in terms of limited re-sources in hardware. To relax the initial condition of the partitioning. Optimal Partitioning and Coordination Decisions in Decomposition-based Design Optimization by James T.

Allison A dissertation submitted in partial fulﬁllment of the requirements for the degree of Doctor of Philosophy (Mechanical Engineering) in The University of Michigan Doctoral Committee: Professor Panos Y. Papalambros, Chair Professor.This paper presents the first results of our research on the problem of optimal partitioning shapes for parallel matrix-matrix multiplication on heterogeneous processors.

Namely, the case of two interconnected processors is comprehensively studied. We prove that, depending on performance characteristics of the processors and the communication Cited by: T1 - Approximation algorithms for semi-random partitioning problems.

AU - Makarychev, Konstantin. AU - Makarychev, Yury. AU - Vijayaraghavan, Aravindan. PY - /6/ Y1 - /6/ N2 - In this paper, we propose and study a new semi-random model for graph partitioning problems.

We believe that it captures many properties of real-world Cited by: