Parallel Option Research Articles

A branch-and-bound algorithm for the solution of chemical production scheduling MIP models using parallel computing

Exploiting multiple cores in a computer or grid of computers can reduce the time required to solve a mixed-integer programming (MIP) model. Here, we develop a parallel branch-and-bound algorithm for a chemical production scheduling problem using a discrete-time model. The algorithm consists of initialization, submission, branching, collection, bounding, and pruning steps. We branch by adding a constraint to bound the total number of times each task runs. Each subproblem is solved as an MIP on a single core of a computer, so that many sub problems can be solved simultaneously. Also, we propose an algorithm, executed at each node of our branch-and-bound tree, to improve the bounds on the number of times a task is run based on the current objective value. We present computational results for several instances to show the parallel algorithm with the proposed branching strategy can solve more challenging problems than simply using the default parallel option.

Parallelism orchestration using DoPE

In writing parallel programs, programmers expose parallelism and optimize it to meet a particular performance goal on a single platform under an assumed set of workload characteristics. In the field, changing workload characteristics, new parallel platforms, and deployments with different performance goals make the programmer's development-time choices suboptimal. To address this problem, this paper presents the Degree of Parallelism Executive (DoPE), an API and run-time system that separates the concern of exposing parallelism from that of optimizing it. Using the DoPE API, the application developer expresses parallelism options. During program execution, DoPE's run-time system uses this information to dynamically optimize the parallelism options in response to the facts on the ground. We easily port several emerging parallel applications to DoPE's API and demonstrate the DoPE run-time system's effectiveness in dynamically optimizing the parallelism for a variety of performance goals.

Comparative Family Law, Korean Family Law and the Missing Definitions of Family

This article uses comparative law to analyze the concept of ‘family’. In particular, the research focuses on how is defined when a group assembles outside of a nuclear marital family. The article discovers that ‘family’ is rarely defined outside of the concept of marriage in modern legal codes. That family is rarely defined per se requires additional legal scrutiny in the context of providing for non-traditional nuclear families.A definition of family can be developed from the material found in law. Eight characteristics and identifying behaviors of families can be found in the analysis of law. These eight concepts are used to rebuild a potential definition of that does not require the act of marriage.This article proposes that law should include a parallel definition for families that do not meet current marital definitions of family. This article does not advocate changing current marriage codes; it merely suggests adding room for non-nuclear families in law. These other, non-nuclear families deserve legal support and recognition. It is time for law to recognize that all families need legal protection and legal affirmation as families.The reason to focus on outside of the concept of marriage is that many family-type groups today fulfill the role of life without legal recognition. These families serve broader societal goals of raising children, of providing for the elderly, and of sharing the burdens and responsibilities of life in a small group setting. Family law should extend the legal notion of to include a wider array of options for non-nuclear families. These types of families are all ‘normal’ families in some sense of the idea of family, but they may simply lack two central ingredients: marriage and a nuclear spousal pair. These types of families should have as much legal right to formally exist as families based in nuclear marriage and sexually-based procreation. Specifically, there should be a legal entity called a 'family' that serves a small group of individuals living in some form of interdependency under a common roof. The basic argument is to provide a parallel option for these types of alternative families alongside the traditional marriage-based option.

Parallel Binomial American Option Pricing under Proportional Transaction Costs

We present a parallel algorithm that computes the ask and bid prices of an American option when proportional transaction costs apply to trading in the underlying asset. The algorithm computes the prices on recombining binomial trees, and is designed for modern multi-core processors. Although parallel option pricing has been well studied, none of the existing approaches takes transaction costs into consideration. The algorithm that we propose partitions a binomial tree into blocks. In any round of computation a block is further partitioned into regions which are assigned to distinct processors. To minimise load imbalance the assignment of nodes to processors is dynamically adjusted before each new round starts. Synchronisation is required both within a round and between two successive rounds. The parallel speedup of the algorithm is proportional to the number of processors used. The parallel algorithm was implemented in C/C++ via POSIX Threads, and was tested on a machine with 8 processors. In the pricing of an American put option, the parallel speedup against an efficient sequential implementation was 5.26 using 8 processors and 1500 time steps, achieving a parallel efficiency of 65.75%.

Ranking of Strategic Management Indicators in Improvement of Urban Management by Using Multiple Attribute Decision Method of TOPSIS

Planning, investment and city management have been surprisingly become so complex and difficult because of the massive growth of cities and the dual role they play. Not only Complexity and importance of the problem are facing planners to this reality but also make them to quit outdated methods of urban management, and accept new ideas and updated methods. In this study, urban development strategy was considered by emphasizing on public participation, local government power and urban vision. Because urban vision is an ideal situation which society hopes to achieve in future. Certainly one of the most important goals of this project was citizen’s welfare. Thus we tried to explain and define these criteria’s such as development strategy plan and urban management. At the end the existing approaches has been evaluated by considering urban approaches as parallel options and determining its basic indicators and their efficiency. By considering existing approaches as a multi- dimensional approach, the multi- dimensional decision method like TOPSIS method has been used and consequently existing application ranked generally and since our country is developing so this could be an efficient step to the self- help of the cities.

Parallelism orchestration using DoPE

In writing parallel programs, programmers expose parallelism and optimize it to meet a particular performance goal on a single platform under an assumed set of workload characteristics. In the field, changing workload characteristics, new parallel platforms, and deployments with different performance goals make the programmer's development-time choices suboptimal. To address this problem, this paper presents the Degree of Parallelism Executive (DoPE), an API and run-time system that separates the concern of exposing parallelism from that of optimizing it. Using the DoPE API, the application developer expresses parallelism options. During program execution, DoPE's run-time system uses this information to dynamically optimize the parallelism options in response to the facts on the ground. We easily port several emerging parallel applications to DoPE's API and demonstrate the DoPE run-time system's effectiveness in dynamically optimizing the parallelism for a variety of performance goals.

Jefferson Medical College of Thomas Jefferson University

Jefferson Medical College of Thomas Jefferson University

Parallel option pricing with Fourier space time-stepping method on graphics processing units

With the evolution of graphics processing units (GPUs) into powerful and cost-efficient computing architectures, their range of application has expanded tremendously, especially in the area of computational finance. Current research in the area, however, is limited both in terms of the type of options priced and the complexity of stock price models. This paper presents algorithms, based on the Fourier space time-stepping (FST) method, for pricing single- and multi-asset European and American options with stock prices following exponential Lévy processes on a GPU. Furthermore, the single-asset pricing algorithm is parallelized to attain greater efficiency.

Parallel Option Price Valuations with the Explicit Finite Difference Method

We show how computations such as those involved in American or European-style option price valuations with the explicit finite difference method can be performed in parallel. Towards this we introduce a latency tolerant parallel algorithm for performing such computations efficiently that achieves optimal theoretical speedup p, where p is the number of processor of the parallel system. An implementation of the parallel algorithm has been undertaken, and an evaluation of its performance is carried out by performing an experimental study on a high-latency PC cluster, and at a smaller scale, on a multi-core processor using in addition the SWARM parallel computing framework for multi-core processors. Our implementation of the parallel algorithm is not only architecture but also communication library independent: the same code works under LAM-MPI and Open MPI and also BSPlib, two sets of library frameworks that facilitate parallel programming. The suitability of our approach to multi-core processors is also established.

Optimal Simultaneous Design and Operational Planning of Vegetable Extraction Processes

A general multiperiod linear optimization model is proposed in this study that targets the simultaneous design and operation planning decisions of a multiproduct batch plant for the production of vegetable extracts. A multiperiod environment is considered because of the market and/or seasonal fluctuations. Thereby, the model considers changes from period to period of demands, costs, prices and raw materials supplies. The objective function maximizes the net present value of the profit considering incomes, investments and resources costs, and both product and raw material inventory costs. In the plant design problem, the sequence of operations is already defined and the pursued goal is to determine both unit sizes and its configuration in the plant. Besides the usual duplication in parallel option, a novel design alternative is included which allows adding units in series to perform a given operation. The optimal design is determined by taking into account available discrete sizes of units which corresponds to the real procurement of equipments. The model is formulated by using the linear generalized disjunctive programming (LGDP). A particular plant that produces oleoresins (solvent extracts of herbs and spices) is used to illustrate the proposed approach. Nevertheless, the developed model is general and can thus be applied to any vegetable extraction process.

Parallel Option Pricing with Fourier Space Time-Stepping Method on Graphics Processing Units

With the evolution of Graphics Processing Units (GPUs) into powerful and cost-efficient computing architectures, their range of application has expanded tremendously, especially in the area of computational finance. Current research in the area, however, is limited in terms of options priced and complexity of stock price models. This paper presents algorithms, based on the Fourier Space Time-stepping (FST) method, for pricing single and multi-asset European and American options with Levy underliers on a GPU. Furthermore, the single-asset pricing algorithm is parallelized to attain greater efficiency.

Two-level parallelization for finite-element based design optimization via case studies

Computing clusters created with commodity chips are gaining popularity owing to relative ease of assembly and maintenance compared to a supercomputer. Such clusters are able to solve much larger problems owing to increased memory and reduced compute time. The challenge, however, is to develop new algorithms and software that can exploit multiple processors. In this paper we discuss the parallel processing options and their implementations in a gradient-based design optimization software system. The main objectives are as follows—(a) implement a design optimization methodology for sizing, shape and topology optimization using two-level parallelism and (b) provide a benchmark in the area of FEA-based design optimization for studying speedups with increasing number of processors to speed development of effective parallel algorithms. The two-level parallelism is implemented using nested parallel gradient calculations in conjunction with parallel FEA, and parallel line search with parallel FEA. Two case studies involving topology and shape optimization are studied in detail and they include three-dimensional finite element meshes with about 160 000 hexahedral elements and about 175 000 nodes. Furthermore, the case studies have been implemented using a workbench where the topology and shape optimization have an interface with a commercial CAD package, permitting a solid model representation of both the initial and the final optimized part.

Parallel CBIR implementations with load balancing algorithms

The purpose of content-based information retrieval (CBIR) systems is to retrieve, from real data stored in a database, information that is relevant to a query. When large volumes of data are considered, as it is very often the case with databases dealing with multimedia data, it may become necessary to look for parallel solutions in order to store and gain access to the available items in an efficient way. Among the range of parallel options available nowadays, clusters stand out as flexible and cost effective solutions, although the fact that they are composed of a number of independent machines makes it easy for them to become heterogeneous. This paper describes a heterogeneous cluster-oriented CBIR implementation. First, the cluster solution is analyzed without load balancing, and then, a new load balancing algorithm for this version of the CBIR system is presented. The load balancing algorithm described here is dynamic, distributed, global and highly scalable. Nodes are monitored through a load index which allows the estimation of their total amount of workload, as well as the global system state. Load balancing operations between pairs of nodes take place whenever a node finishes its job, resulting in a receptor-triggered scheme which minimizes the system's communication overhead. Globally, the CBIR cluster implementation together with the load balancing algorithm can cope effectively with varying degrees of heterogeneity within the cluster; the experiments presented within the paper show the validity of the overall strategy. Together, the CBIR implementation and the load balancing algorithm described in this paper span a new path for performant, cost effective CBIR systems which has not been explored before in the technical literature.

The principle of parallelism in the design of studies to estimate treatment effects.

An effect is a function of a cause as well as of 4 other factors: recipient, setting, time, and outcome variable. The principle of parallelism states that if a design option exists for any 1 of these 4 factors, a parallel option exists for each of the others. For example, effects are often estimated by drawing a comparison across recipients who receive different treatments. The principle of parallelism implies that an effect can also be estimated by drawing a comparison across settings, times, or outcome variables. Typologies of methodological options are derived from the principle of parallelism. The typologies can help researchers recognize a broader set of options than they would otherwise and thereby improve the quality of research designs.

Trinomial-tree Based Parallel Option Price Valuations

We examine how trinomial-tree based computations such as those involved in American or European-style option price valuations can be performed in parallel. Towards this we introduce a parallel algorithm for performing such computations on trinomial trees. The algorithm is described and analyzed in an architecture independent setting and achieves optimal theoretical speedup O( p) and is thus within a multiplicative factor of the corresponding sequential method. We verify the practicality and plausibility of the designed algorithm by carrying out an experimental study of an implementation of the algorithm on a high-latency parallel system, a cluster of PC workstations. The algorithmic and programming methodology used to design and analyze the algorithm allows its implementation to work with only recompilation of the source code under two parallel programming libraries: MPI (LAM-MPI) and BSPlib thus making the implementation not only architecture but also communication-library independent.

Modeling alpha-helical coiled-coil interactions: the axial and azimuthal alignment of 1B segments from vimentin intermediate filaments.

Attempts at predicting the relative axial alignments of fibrous protein molecules in filamentous structures have relied upon representing the (multichain) molecular structure by a one-dimensional sequence of amino acids. Potential intermolecular ionic and apolar interactions were counted and determined as a function of the relative axial stagger between the molecules. No attempts were made to consider the azimuthal aspect of the interacting molecules and neither were apolar or ionic energy terms used. Surprisingly, this simple approach proved remarkably informative and yielded accurate predictions of the axial periods present. However, a more comprehensive analysis involving the energetics of aggregation taking due regard for the relative azimuths of the molecules as well as their separation should decrease the noise level in the calculations and reveal other pertinent information. Toward that end, we have modeled the interaction between two alpha-helical coiled-coil segments in intermediate filament molecules (1B segments from human vimentin). The relative axial alignment and polarity of the molecules is already known from detailed crosslinking studies and this provides a criterion against which the success (or otherwise) of the modeling can be judged. The results confirm that an antiparallel alignment of two 1B segments is preferred over any of the parallel options (as observed experimentally). The calculated axial alignment, however, is not identical to that observed from detailed crosslinking studies indicating that other parts of the molecule (probably the head and tail domains as well as other coiled-coil segments) have a crucial role in determining the precise mode of axial aggregation. The results also show that the apolar interactions seem to be significantly less important in the alignment process than the ionic ones. This is consistent with the observation of a well-defined period in the linear disposition of the charged (but not apolar) residues along the length of the outer surface of the vimentin molecule.

Scalable Algorithms for Adaptive Statistical Designs

We present a scalable, high‐performance solution to multidimensional recurrences that arise in adaptive statistical designs. Adaptive designs are an important class of learning algorithms for a stochastic environment, and we focus on the problem of optimally assigning patients to treatments in clinical trials. While adaptive designs have significant ethical and cost advantages, they are rarely utilized because of the complexity of optimizing and analyzing them. Computational challenges include massive memory requirements, few calculations per memory access, and multiply‐nested loops with dynamic indices. We analyze the effects of various parallelization options, and while standard approaches do not work well, with effort an efficient, highly scalable program can be developed. This allows us to solve problems thousands of times more complex than those solved previously, which helps make adaptive designs practical. Further, our work applies to many other problems involving neighbor recurrences, such as generalized string matching.

Options and efficiency: Some experimental evidence

This paper examines the information aggregation role of options when agents possess diverse information about possible asset returns. We construct two identical experimental markets: one with and one without options. We find that options speed the information aggregation process. Asset markets that have parallel option markets aggregate traders' diverse information faster than markets where options trading is not available. Implied ranges were calculated from asset and option prices and compared to the actual ranges. These comparisons suggest that options may provide a means for agents to coordinate beliefs about asset values.

JOB QUITS AND JOB CHANGES:

This article conceptualizes labor force exits as a parallel option to employer changes in the gender-specific opportunity structure for employed young women. It argues that the same working conditions should predict both employment exits and employer changes. Family characteristics (including pregnancy and presence of preschool children), rather than working conditions, should differentiate between job changers and job leavers. These hypotheses were tested with 1970-1980 data from the National Longitudinal Survey. Results from logit analyses showed that employment conditions do affect young women's decisions to change jobs or exit the labor force, and influence them in similar ways, and that household factors affect labor force exits more strongly than they do job changes. While pregnant women are more likely to leave the labor force, both improved job conditions and existing preschool children (implying prior experience with substitute care) enhance the likelihood of continuous employment for pregnant women.