Academic literature on the topic 'Paralellization'

We present a lab-on-a-chip methodology for the enrichment of ultrasound contrast agents using pinched flow fractionation. We extend the modelling to include relatively large particles, by combining numerical and experimental results. Due to the simple operating principle, sorting devices based on this method are ideally suited for paralellization.

The parallelization aspect of the Ising Monte Carlo simulation is discussed. It is shown that most of the theoretically interesting simulations now are suitable for the trivial parallelization, that is, the Ising simulation is ideally parallelizable. Furthermore, presently most efficient simulation algorithm for single processor is also a kind of trivial paralellization. Results on the non-equilibrium critical relaxation study is included as an example.

A monitor is a widely-used concurrent programming abstraction that encapsulates all shared state between threads. Monitors can be classified as being either implicit or explicit depending on the primitives they provide. Implicit monitors are much easier to program but typically not as efficient. To address this gap, there has been recent research on automatically synthesizing explicit-signal monitors from an implicit specification, but prior work does not exploit all paralellization opportunities due to the use of a single lock for the entire monitor. This paper presents a new technique for synthesizing fine-grained explicit-synchronization protocols from implicit monitors. Our method is based on two key innovations: First, we present a new static analysis for inferring safe interleavings that allow violating mutual exclusion of monitor operations without changing its semantics. Second, we use the results of this static analysis to generate a MaxSAT instance whose models correspond to correct-by-construction synchronization protocols. We have implemented our approach in a tool called Cortado and evaluate it on monitors that contain parallelization opportunities. Our evaluation shows that Cortado can synthesize synchronization policies that are competitive with, or even better than, expert-written ones on these benchmarks.

Graph algorithms are concerned with the algorithmic aspects of solving graph problems. The problems are motivated from and have application to diverse areas of computer science, engineering and other disciplines. Problems arising from these areas of application are good candidates for parallelization since they often have both intense computational needs and stringent response time requirements. Motivated by these concerns, this thesis investigates parallel algorithms for these kinds of graph problems that have at least one of the following properties: the problems involve some type of dynamic updates; the sparsification technique is applicable; or the problems are closely related to communications network issues. The models of parallel computation used in our studies are the Parallel Random Access Machine (PRAM) model and the practical interconnection network models such as meshes and hypercubes. ¶ Consider a communications network which can be represented by a graph G = (V;E), where V is a set of sites (processors), and E is a set of links which are used to connect the sites (processors). In some cases, we also assign weights and/or directions to the edges in E. Associated with this network, there are many problems such as (i) whether the network is k-edge (k-vertex) connected withfixed k; (ii) whether there are k-edge (k-vertex) disjoint paths between u and v for a pair of given vertices u and v after the network is dynamically updated by adding and/or deleting an edge etc; (iii) whether the sites in the network can communicate with each other when some sites and links fail; (iv) identifying the first k edges in the network whose deletion will result in the maximum increase in the routing cost in the resulting network for fixed k; (v) how to augment the network at optimal cost with a given feasible set of weighted edges such that the augmented network is k-edge (k-vertex) connected; (vi) how to route messages through the network efficiently. In this thesis we answer the problems mentioned above by presenting efficient parallel algorithms to solve them. As far as we know, most of the proposed algorithms are the first ones in the parallel setting. ¶ Even though most of the problems concerned in this thesis are related to communications networks, we also study the classic edge-coloring problem. The outstanding difficulty to solve this problem in parallel is that we do not yet know whether or not it is in NC. In this thesis we present an improved parallel algorithm for the problem which needs [bigcircle]([bigtriangleup][superscript 4.5]log [superscript 3] [bigtriangleup] log n + [bigtriangleup][superscript 4] log [superscript 4] n) time using [bigcircle](n[superscript 2][bigtriangleup] + n[bigtriangleup][superscript 3]) processors, where n is the number of vertices and [bigtriangleup] is the maximum vertex degree. Compared with a previously known result on the same model, we improved by an [bigcircle]([bigtriangleup][superscript 1.5]) factor in time. The non-trivial part is to reduce this problem to the edge-coloring update problem. We also generalize this problem to the approximate edge-coloring problem by giving a faster parallel algorithm for the latter case. ¶ Throughout the design and analysis of parallel graph algorithms, we also find a technique called the sparsification technique is very powerful in the design of efficient sequential and parallel algorithms on dense undirected graphs. We believe that this technique may be useful in its own right for guiding the design of efficient sequential and parallel algorithms for problems in other areas as well as in graph theory.

Evolutionary algorithms are often used for hard optimization problems. Solving time of this problems is long, so we want effective parallelization for this algorithms. Unfortunately, classical methods of parallelization do not work very well in cases where the individual evaluations of problems take significantly different times. In this project, we will try to extend the evolu- tionary algorithm with interleaving generations, which offers a better use of computational resources than classical parallel evolutionary algorithms, by speculative evaluation. Speculative evaluation means the estimation of an in- dividual's fitness function and the prediction of the following steps, which we will use later in the case of a correct estimate. We compare the algorithm with speculative evaluation with the original version in a series of experi- ments and we look at the effect of accuracy in the speculative step on the performance of the algorithm. 1

Graph algorithms are concerned with the algorithmic aspects of solving graph problems. The problems are motivated from and have application to diverse areas of computer science, engineering and other disciplines. Problems arising from these areas of application are good candidates for parallelization since they often have both intense computational needs and stringent response time requirements. Motivated by these concerns, this thesis investigates parallel algorithms for these kinds of graph problems that have at least one of the following properties: the problems involve some type of dynamic updates; the sparsification technique is applicable; or the problems are closely related to communications network issues. The models of parallel computation used in our studies are the Parallel Random Access Machine (PRAM) model and the practical interconnection network models such as meshes and hypercubes. ¶ ...