Fast and Scalable Solvers for the Fluid Pressure Equations with Separating Solid Boundary Conditions

We propose and evaluate fast, scalable approaches for solving the linear complementarity problems (LCP) arising from the fluid pressure equations with separating solid boundary conditions. Specifically, we present a policy iteration method, a penalty method, and a modified multigrid method, and demonstrate that each is able to properly handle the desired boundary conditions. Moreover, we compare our proposed methods against existing approaches and show that our solvers are more efficient and exhibit better scaling behavior; that is, the number of iterations required for convergence is essentially independent of grid resolution, and thus they are faster at larger grid resolutions. For example, on a 256^3 grid our multigrid method was 30 times faster than the prior multigrid method in the literature

Implementations of iterative algorithms in Hadoop and Spark

Facing the challenges of large amounts of data generated by various companies (such as Facebook, Amazon, and Twitter), cloud computing frameworks such as Hadoop are used to store and process the Big Data. Hadoop, an open source cloud computing framework, is popular because of its scalability and fault tolerance. However, by frequently writing and reading data from the Hadoop Distributed File System (HDFS), Hadoop is quite slow in many applications. Apache Spark, a new cloud computing framework developed at AMPLab of UC Berkeley, solves this problem by caching data in memory. Spark develops a new abstraction called resilient distributed dataset (RDD) which is both scalable and fault-tolerant. In this thesis, we describe the architecture of Hadoop and Spark and discuss their differences. Properties of RDDs and how they work in Spark are discussed in detail, which gives a guide on how to use them efficiently. The main contribution of the thesis is to implement the PageRank algorithm and Conjugate Gradient (CG) method in Hadoop and Spark, and show how Spark out-performs Hadoop by taking advantage of memory caching.4 month

Fast and Scalable Solvers for the Fluid Pressure Equations with Separating Solid Boundary Conditions

This is the peer reviewed version of the following article: Lai, J., Chen, Y., Gu, Y., Batty, C. and Wan, J.W. (2020), Fast and Scalable Solvers for the Fluid Pressure Equations with Separating Solid Boundary Conditions. Computer Graphics Forum, 39: 23-33., which has been published in final form at https://doi.org/10.1111/cgf.13909. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.In this paper, we propose and evaluate fast, scalable approaches for solving the linear complementarity problems (LCP) arising from the fluid pressure equations with separating solid boundary conditions. Specifically, we present a policy iteration method, a penalty method, and a modified multigrid method, and demonstrate that each is able to properly handle the desired boundary conditions. Moreover, we compare our proposed methods against existing approaches and show that our solvers are more efficient and exhibit better scaling behavior; that is, the number of iterations required for convergence is essentially independent of grid resolution, and thus they are faster at larger grid resolutions. For example, on a 2563 grid our multigrid method was 30 times faster than the prior multigrid method in the literature

Effects of molecular contamination and sp2^2 carbon on oxidation of (100) single-crystal diamond surfaces

The efficacy of oxygen (O) surface terminations of specific moieties and densities on diamond depends on factors such as crystallinity, roughness, and crystal orientation. Given the wide breadth of diamond-like materials and O-termination techniques, it can be difficult to discern which method would yield the highest and most consistent O coverage on a particular subset of diamond. We first review the relevant physical parameters for O-terminating single-crystalline diamond (SCD) surfaces and summarize prior oxidation work on (100) SCD. We then report on our experimental study on X-ray Photoelectron Spectroscopy (XPS) characterization of (100) diamond surfaces treated with oxidation methods that include wet chemical oxidation, photochemical oxidation with UV illumination, and steam oxidation using atomic layer deposition. We describe a rigorous XPS peak-fitting procedure for measuring the functionalization of O-terminated samples and recommend that the reporting of peak energy positions, line shapes, and full-width-half-maximum values of the individual components, along with the residuals, are important for evaluating the quality of the peak fit. Two chemical parameters on the surface, sp$^2$ C and molecular contaminants, are also crucial towards interpreting the O coverage on the diamond surface and may account for the inconsistency in prior reported values in literature

Relevant domains, core outcome sets and measurements for implant dentistry clinical trials: The Implant Dentistry Core Outcome Set and Measurement (ID-COSM) international consensus report

AIM: Lack of consistently reported outcomes limits progress in evidence-based implant dentistry and quality of care. The objective of this initiative was to develop a core outcome set (COS) and measurements for implant dentistry clinical trials (ID-COSM). MATERIALS AND METHODS: This Core Outcome Measures in Effectiveness Trials (COMET)-registered international initiative comprised six steps over 24 months: (i) systematic reviews of outcomes reported in the last 10 years; (ii) international patient focus groups; (iii) a Delphi project with a broad range of stakeholders (care providers, clinical researchers, methodologists, patients and industry representatives); (iv) expert group discussions organizing the outcomes in domains using a theoretical framework and identifying the COSs; (v) identification of valid measurement systems to capture the different domains and (vi) final consensus and formal approval involving experts and patients. The methods were modified from the best practice approach following the Outcome Measures in Rheumatoid Arthritis Clinical Trial and COMET manuals. RESULTS: The systematic reviews and patient focus groups identified 754 (665 + 89, respectively) relevant outcome measures. After elimination of redundancies and duplicates, 111 were formally assessed in the Delphi project. By applying pre-specified filters, the Delphi process identified 22 essential outcomes. These were reduced to 13 after aggregating alternative assessments of the same features. The expert committee organized them into four core outcome areas: (i) pathophysiology, (ii) implant/prosthesis lifespan, (iii) life impact and (iv) access to care. In each area, core outcomes were identified to capture both the benefits and harms of therapy. Mandatory outcome domains included assessment of surgical morbidity and complications, peri-implant tissue health status, intervention-related adverse events, complication-free survival and overall patient satisfaction and comfort. Outcomes deemed mandatory in specific circumstances comprised function (mastication, speech, aesthetics and denture retention), quality of life, effort for treatment and maintenance and cost effectiveness. Specialized COSs were identified for bone and soft-tissue augmentation procedures. The validity of measurement instruments ranged from international consensus (peri-implant tissue health status) to early identification of important outcomes (patient-reported outcomes identified by the focus groups). CONCLUSIONS: The ID-COSM initiative reached a consensus on a core set of mandatory outcomes for clinical trials in implant dentistry and/or soft tissue/bone augmentation. Adoption in future protocols and reporting on the respective domain areas by currently ongoing trials will contribute to improving evidence-informed implant dentistry and quality of care