IceT users' guide and reference.

The Image Composition Engine for Tiles (IceT) is a high-performance sort-last parallel rendering library. In addition to providing accelerated rendering for a standard display, IceT provides the unique ability to generate images for tiled displays. The overall resolution of the display may be several times larger than any viewport that may be rendered by a single machine. This document is an overview of the user interface to IceT

IceT users' guide and reference.

The Image Composition Engine for Tiles (IceT) is a high-performance sort-last parallel rendering library. In addition to providing accelerated rendering for a standard display, IceT provides the unique ability to generate images for tiled displays. The overall resolution of the display may be several times larger than any viewport that may be rendered by a single machine. This document is an overview of the user interface to IceT

Massive graph visualization : LDRD final report.

Graphs are a vital way of organizing data with complex correlations. A good visualization of a graph can fundamentally change human understanding of the data. Consequently, there is a rich body of work on graph visualization. Although there are many techniques that are effective on small to medium sized graphs (tens of thousands of nodes), there is a void in the research for visualizing massive graphs containing millions of nodes. Sandia is one of the few entities in the world that has the means and motivation to handle data on such a massive scale. For example, homeland security generates graphs from prolific media sources such as television, telephone, and the Internet. The purpose of this project is to provide the groundwork for visualizing such massive graphs. The research provides for two major feature gaps: a parallel, interactive visualization framework and scalable algorithms to make the framework usable to a practical application. Both the frameworks and algorithms are designed to run on distributed parallel computers, which are already available at Sandia. Some features are integrated into the ThreatView{trademark} application and future work will integrate further parallel algorithms

Data co-processing for extreme scale analysis level II ASC milestone (4745).

Exascale supercomputing will embody many revolutionary changes in the hardware and software of high-performance computing. A particularly pressing issue is gaining insight into the science behind the exascale computations. Power and I/O speed con- straints will fundamentally change current visualization and analysis work ows. A traditional post-processing work ow involves storing simulation results to disk and later retrieving them for visualization and data analysis. However, at exascale, scien- tists and analysts will need a range of options for moving data to persistent storage, as the current o ine or post-processing pipelines will not be able to capture the data necessary for data analysis of these extreme scale simulations. This Milestone explores two alternate work ows, characterized as in situ and in transit, and compares them. We nd each to have its own merits and faults, and we provide information to help pick the best option for a particular use

Post-processing V&V Level II ASC Milestone (2843) results.

The 9/30/2008 ASC Level 2 Post-Processing V&V Milestone (Milestone 2843) contains functionality required by the user community for certain verification and validation tasks. These capabilities include fragment detection from CTH simulation data, fragment characterization and analysis, and fragment sorting and display operations. The capabilities were tested extensively both on sample and actual simulations. In addition, a number of stretch criteria were met including a comparison between simulated and test data, and the ability to output each fragment as an individual geometric file

Post-processing V&V level II ASC milestone (2360) results.

The 9/30/2007 ASC Level 2 Post-Processing V&V Milestone (Milestone 2360) contains functionality required by the user community for certain verification and validation tasks. These capabilities include loading of edge and face data on an Exodus mesh, run-time computation of an exact solution to a verification problem, delivery of results data from the server to the client, computation of an integral-based error metric, simultaneous loading of simulation and test data, and comparison of that data using visual and quantitative methods. The capabilities were tested extensively by performing a typical ALEGRA HEDP verification task. In addition, a number of stretch criteria were met including completion of a verification task on a 13 million element mesh

EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2016 update

Recent insights in rheumatoid arthritis (RA) necessitated updating the European League Against Rheumatism (EULAR) RA management recommendations. A large international Task Force based decisions on evidence from 3 systematic literature reviews, developing 4 overarching principles and 12 recommendations (vs 3 and 14, respectively, in 2013). The recommendations address conventional synthetic (cs) disease-modifying antirheumatic drugs (DMARDs) (methotrexate (MTX), leflunomide, sulfasalazine); glucocorticoids (GC); biological (b) DMARDs (tumour necrosis factor (TNF)-inhibitors (adalimumab, certolizumab pegol, etanercept, golimumab, infliximab), abatacept, rituximab, tocilizumab, clazakizumab, sarilumab and sirukumab and biosimilar (bs) DMARDs) and targeted synthetic (ts) DMARDs (Janus kinase (Jak) inhibitors tofacitinib, baricitinib). Monotherapy, combination therapy, treatment strategies (treat-to-target) and the targets of sustained clinical remission (as defined by the American College of Rheumatology-(ACR)-EULAR Boolean or index criteria) or low disease activity are discussed. Cost aspects were taken into consideration. As first strategy, the Task Force recommends MTX (rapid escalation to 25 mg/week) plus short-term GC, aiming at >50% improvement within 3 and target attainment within 6 months. If this fails stratification is recommended. Without unfavourable prognostic markers, switching to—or adding—another csDMARDs (plus short-term GC) is suggested. In the presence of unfavourable prognostic markers (autoantibodies, high disease activity, early erosions, failure of 2 csDMARDs), any bDMARD (current practice) or Jak-inhibitor should be added to the csDMARD. If this fails, any other bDMARD or tsDMARD is recommended. If a patient is in sustained remission, bDMARDs can be tapered. For each recommendation, levels of evidence and Task Force agreement are provided, both mostly very high. These recommendations intend informing rheumatologists, patients, national rheumatology societies, hospital officials, social security agencies and regulators about EULAR's most recent consensus on the management of RA, aimed at attaining best outcomes with current therapies

A genome-wide association study identifies risk alleles in plasminogen and P4HA2 associated with giant cell arteritis

Giant cell arteritis (GCA) is the most common form of vasculitis in individuals older than 50 years in Western countries. To shed light onto the genetic background influencing susceptibility for GCA, we performed a genome-wide association screening in a well-powered study cohort. After imputation, 1,844,133 genetic variants were analysed in 2,134 cases and 9,125 unaffected controls from ten independent populations of European ancestry. Our data confirmed HLA class II as the strongest associated region (independent signals: rs9268905, P = 1.94E-54, per-allele OR = 1.79; and rs9275592, P = 1.14E-40, OR = 2.08). Additionally, PLG and P4HA2 were identified as GCA risk genes at the genome-wide level of significance (rs4252134, P = 1.23E-10, OR = 1.28; and rs128738, P = 4.60E-09, OR = 1.32, respectively). Interestingly, we observed that the association peaks overlapped with different regulatory elements related to cell types and tissues involved in the pathophysiology of GCA. PLG and P4HA2 are involved in vascular remodelling and angiogenesis, suggesting a high relevance of these processes for the pathogenic mechanisms underlying this type of vasculitis

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

A pervasive parallel framework for visualization: final report for FWP 10-014707

We are on the threshold of a transformative change in the basic architecture of highperformance computing. The use of accelerator processors, characterized by large core counts, shared but asymmetrical memory, and heavy thread loading, is quickly becoming the norm in high performance computing. These accelerators represent significant challenges in updating our existing base of software. An intrinsic problem with this transition is a fundamental programming shift from message passing processes to much more fine thread scheduling with memory sharing. Another problem is the lack of stability in accelerator implementation; processor and compiler technology is currently changing rapidly. This report documents the results of our three-year ASCR project to address these challenges. Our project includes the development of the Dax toolkit, which contains the beginnings of new algorithms for a new generation of computers and the underlying infrastructure to rapidly prototype and build further algorithms as necessary