A Randomized Parallel Sorting Algorithm With an Experimental Study

Previous schemes for sorting on general-purpose parallel machines have had to choose between poor load balancing and irregular communication or multiple rounds of all-to-all personalized communication. In this paper, we introduce a novel variation on sample sort which uses only two rounds of regular all-to-all personalized communication in a scheme that yields very good load balancing with virtually no overhead. Moreover, unlike previous variations, our algorithm efficiently handles the presence of duplicate values without the overhead of tagging each element with a unique identifier. This algorithm was implemented in Split-C and run on a variety of platforms, including the Thinking Machines CM-5, the IBM SP-2, and the Cray Research T3D. We ran our code using widely different benchmarks to examine the dependence of our algorithm on the input distribution. Our experimental results illustrate the efficiency and scalability of our algorithm across different platforms. In fact, it seems to..

Sorting on Clusters of SMPs

Clusters of symmetric multiprocessors (SMPs) have emerged as the primary candidates for large scale multiprocessor systems. In this paper, we introduce an efficient sorting algorithm for clusters of SMPs. This algorithm relies on a novel scheme for stably sorting on a single SMP coupled with balanced regular communication on the cluster. Our SMP algorithm seems to be asymptotically faster than any of the published algorithms we are aware of. The algorithms were implemented in C using Posix Threads and the SIMPLE library of communication primitives and run on a cluster of DEC AlphaServer 2100A systems. Our experimental results verify the scalability and efficiency of our proposed solution and illustrate the importance of considering both memory hierarchy and the overhead of shifting to multiple nodes. (Also cross-reference as UMIACS-TR-97-6

Designing Practical Efficient Algorithms for Symmetric Multiprocessors

Symmetric multiprocessors (SMPs) dominate the high-end server market and are currently the primary candidate for constructing large scale multiprocessor systems. Yet, the design of efficient parallel algorithms for this platform currently poses several challenges. In this paper, we present a computational model for designing efficient algorithms for symmetric multiprocessors. We then use this model to create efficient solutions to two widely different types of problems - linked list prefix computations and generalized sorting. Our novel algorithm for prefix computations builds upon the sparse ruling set approach of Reid-Miller and Blelloch. Besides being somewhat simpler and requiring nearly half the number of memory accesses, we can bound our complexity with high probability instead of merely on average. Our algorithm for generalized sorting is a modification of our algorithm for sorting by regular sampling on distributed memory architectures. The algorithm is a stable sort which appears to be asymptotically faster than any of the published algorithms for SMPs. Both of our algorithms were implemented in C using POSIX threads and run on three symmetric multiprocessors - the DEC AlphaServer, the Silicon Graphics Power Challenge, and the HP-Convex Exemplar. We ran our code for each algorithm using a variety of benchmarks which we identified to examine the dependence of our algorithm on memory access patterns. In spite of the fact that the processors must compete for access to main memory, both algorithms still yielded scalable performance up to 16 processors, which was the largest platform available to us. For some problems, our prefix computation algorithm actually matched or exceeded the performance of the best sequential solution using only a single thread. Similarly, our generalized sorting algorithm always beat the performance of sequential merge sort by at least an order of magnitude, even with a single thread. (Also cross-referenced as UMIACS-TR-98-44

Practical Parallel Algorithms for Personalized Communication and Integer Sorting

A fundamental challenge for parallel computing is to obtain high-level, architecture independent, algorithms which efficiently execute on general-purpose parallel machines. With the emergence of message passing standards such as MPI, it has become easier to design efficient and portable parallel algorithms by making use of these communication primitives. While existing primitives allow an assortment of collective communication routines, they do not handle an important communication event when most or all processors have non-uniformly sized personalized messages to exchange with each other. We focus in this paper on the h-relation personalized communication whose efficient implementation will allow high performance implementations of a large class of algorithms. While most previous h-relation algorithms use randomization, this paper presents a new deterministic approach for h-relation personalized communication. As an application, we present an efficient algorithm for stable integer sorting. The algorithms presented in this paper have been coded in Split-C and run on a variety of platforms, including the Thinking Machines CM-5, IBM SP-1 and SP-2, Cray Research T3D, Meiko Scientific CS-2, and the Intel Paragon. Our experimental results are consistent with the theoretical analysis and illustrate the scalability and efficiency of our algorithms across different platforms. In fact, they seem to outperform all similar algorithms known to the authors on these platforms. (Also cross-referenced as UMIACS-TR-95-101.

‘I can die today, I can die tomorrow’: lay perceptions of sickle cell disease in Kumasi, Ghana at a point of transition

Objective. To describe the lay meanings of sickle cell disease (SCD) in the Ashanti region of Ghana

TEFM variants impair mitochondrial transcription causing childhood-onset neurological disease

Mutations in the mitochondrial or nuclear genomes are associated with a diverse group of human disorders characterized by impaired mitochondrial respiration. Within this group, an increasing number of mutations have been identified in nuclear genes involved in mitochondrial RNA biology. The TEFM gene encodes the mitochondrial transcription elongation factor responsible for enhancing the processivity of mitochondrial RNA polymerase, POLRMT. We report for the first time that TEFM variants are associated with mitochondrial respiratory chain deficiency and a wide range of clinical presentations including mitochondrial myopathy with a treatable neuromuscular transmission defect. Mechanistically, we show muscle and primary fibroblasts from the affected individuals have reduced levels of promoter distal mitochondrial RNA transcripts. Finally, tefm knockdown in zebrafish embryos resulted in neuromuscular junction abnormalities and abnormal mitochondrial function, strengthening the genotype-phenotype correlation. Our study highlights that TEFM regulates mitochondrial transcription elongation and its defect results in variable, tissue-specific neurological and neuromuscular symptoms

Signature-Based Small Molecule Screening Identifies Cytosine Arabinoside as an EWS/FLI Modulator in Ewing Sarcoma

BACKGROUND: The presence of tumor-specific mutations in the cancer genome represents a potential opportunity for pharmacologic intervention to therapeutic benefit. Unfortunately, many classes of oncoproteins (e.g., transcription factors) are not amenable to conventional small-molecule screening. Despite the identification of tumor-specific somatic mutations, most cancer therapy still utilizes nonspecific, cytotoxic drugs. One illustrative example is the treatment of Ewing sarcoma. Although the EWS/FLI oncoprotein, present in the vast majority of Ewing tumors, was characterized over ten years ago, it has never been exploited as a target of therapy. Previously, this target has been intractable to modulation with traditional small-molecule library screening approaches. Here we describe a gene expression–based approach to identify compounds that induce a signature of EWS/FLI attenuation. We hypothesize that screening small-molecule libraries highly enriched for FDA-approved drugs will provide a more rapid path to clinical application. METHODS AND FINDINGS: A gene expression signature for the EWS/FLI off state was determined with microarray expression profiling of Ewing sarcoma cell lines with EWS/FLI-directed RNA interference. A small-molecule library enriched for FDA-approved drugs was screened with a high-throughput, ligation-mediated amplification assay with a fluorescent, bead-based detection. Screening identified cytosine arabinoside (ARA-C) as a modulator of EWS/FLI. ARA-C reduced EWS/FLI protein abundance and accordingly diminished cell viability and transformation and abrogated tumor growth in a xenograft model. Given the poor outcomes of many patients with Ewing sarcoma and the well-established ARA-C safety profile, clinical trials testing ARA-C are warranted. CONCLUSIONS: We demonstrate that a gene expression–based approach to small-molecule library screening can identify, for rapid clinical testing, candidate drugs that modulate previously intractable targets. Furthermore, this is a generic approach that can, in principle, be applied to the identification of modulators of any tumor-associated oncoprotein in the rare pediatric malignancies, but also in the more common adult cancers

White Matter Hyperintensities in Vascular Contributions to Cognitive Impairment and Dementia (VCID): Knowledge Gaps and Opportunities

White matter hyperintensities (WMHs) are frequently seen on brain magnetic resonance imaging scans of older people. Usually interpreted clinically as a surrogate for cerebral small vessel disease, WMHs are associated with increased likelihood of cognitive impairment and dementia (including Alzheimer\u27s disease [AD]). WMHs are also seen in cognitively healthy people. In this collaboration of academic, clinical, and pharmaceutical industry perspectives, we identify outstanding questions about WMHs and their relation to cognition, dementia, and AD. What molecular and cellular changes underlie WMHs? What are the neuropathological correlates of WMHs? To what extent are demyelination and inflammation present? Is it helpful to subdivide into periventricular and subcortical WMHs? What do WMHs signify in people diagnosed with AD? What are the risk factors for developing WMHs? What preventive and therapeutic strategies target WMHs? Answering these questions will improve prevention and treatment of WMHs and dementia

Evaluating triple oxygen isotope estimates of gross primary production at the Hawaii Ocean Time-series and Bermuda Atlantic Time-series Study sites

Author Posting. © American Geophysical Union, 2012. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 117 (2012): C05012, doi:10.1029/2010JC006856.The triple oxygen isotopic composition of dissolved oxygen (17Δ) is a promising tracer of gross oxygen productivity (P) in the ocean. Recent studies have inferred a high and variable ratio of P to 14C net primary productivity (12–24 h incubations) (e.g., P:NPP(14C) of 5–10) using the 17Δ tracer method, which implies a very low efficiency of phytoplankton growth rates relative to gross photosynthetic rates. We added oxygen isotopes to a one-dimensional mixed layer model to assess the role of physical dynamics in potentially biasing estimates of P using the 17Δ tracer method at the Bermuda Atlantic Time-series Study (BATS) and Hawaii Ocean Time-series (HOT). Model results were compared to multiyear observations at each site. Entrainment of high 17Δ thermocline water into the mixed layer was the largest source of error in estimating P from mixed layer 17Δ. At both BATS and HOT, entrainment bias was significant throughout the year and resulted in an annually averaged overestimate of mixed layer P of 60 to 80%. When the entrainment bias is corrected for, P calculated from observed 17Δ and 14C productivity incubations results in a gross:net productivity ratio of 2.6 (+0.9 −0.8) at BATS. At HOT a gross:net ratio decreasing linearly from 3.0 (+1.0 −0.8) at the surface to 1.4 (+0.6 −0.6) at depth best reproduced observations. In the seasonal thermocline at BATS, however, a significantly higher gross:net ratio or large lateral fluxes of 17Δ must be invoked to explain 17Δ field observations.We acknowledge support from Center for Microbial Oceanography Research and Education (CMORE) (NSF EF-0424599) and NOAA Global Carbon Program (NA 100AR4310093). BL thanks the USA-Israel Binational Science Foundation for supporting his project at BATS.2012-11-0

Illness beliefs and the sociocultural context of diabetes self-management in British South Asians: a mixed methods study

Background: British South Asians have a higher incidence of diabetes and poorer health outcomes compared to the general UK population. Beliefs about diabetes are known to play an important role in self-management, yet little is known about the sociocultural context in shaping beliefs. This study aimed to explore the influence of sociocultural context on illness beliefs and diabetes self-management in British South Asians. Methods: A mixed methods approach was used. 67 participants recruited using random and purposive sampling, completed a questionnaire measuring illness beliefs, fatalism, health outcomes and demographics; 37 participants completed a social network survey interview and semi-structured interviews. Results were analysed using SPSS and thematic analysis. Results: Quantitative data found certain social network characteristics (emotional and illness work) were related to perceived concern, emotional distress and health outcomes (p < 0.05). After multivariate analysis, emotional work remained a significant predictor of perceived concern and emotional distress related to diabetes (p < 0.05). Analysis of the qualitative data suggest that fatalistic attitudes and beliefs influences self-management practices and alternative food ‘therapies’ are used which are often recommended by social networks. Conclusions: Diabetes-related illness beliefs and self-management appear to be shaped by the sociocultural context. Better understanding of the contextual determinants of behaviour could facilitate the development of culturally appropriate interventions to modify beliefs and support self-management in this population