Grindstone: A Test Suite for Parallel Performance Tools

We describe Grindstone, a suite of programs for testing and calibrating parallel performance measurement tools. The suite consists of nine simple SPMD style PVM programs that demonstrate common communication and computational bottlenecks that occur in parallel programs. In addition, we provide a short case study that demonstrates the use of the test suite on three performance tools for PVM. The results of the case study showed that we were able to uncover bugs or other anomalies in all three tools. The paper also describes how to acquire, compile, and use the test suite. (Also cross-referenced as UMIACS-TR-96-73

Load Balancing Factor (LBF): A Workload Migration Metric

We introduce a new performance metric, called Load Balancing Factor (LBF), to evaluate different tuning alternatives of workload migration within a distributed/parallel program. The metric is unique because it shows the performance implications of a specific tuning alternative rather than quantifying where time is spent in the program. Previously we developed a variation of the metric for coarse-grained process placement, and demonstrated that it accurately predicts the placement impact. In this paper we focus on a variation designed for fine-grained function shipping in a client/server environment and present its online algorithm. We use a synthetic application to show that LBF provides accurate guidance about procedure-level migration. (UMIACS-TR-2002-55

Automated Cluster-Based Web Service Performance Tuning

In this paper, we apply the Active Harmony system to improve the performance of a cluster-based web service system. The performance improvement cannot easily be achieved by tuning individual components for such a system. The experimental results show that there is no single configuration for the system that performs well for all kinds of workloads. By tuning the parameters, the Active Harmony helps the system adapt to different workloads and improve the performance up to 16%. For scalability, we demonstrate how to reduce the time when tuning a large system with many tunable parameters. Finally an algorithm is proposed to automatically adjust the structure of cluster-based web systems, and the system throughput is improved up to 70% using this technology. (UMIACS-TR-2003-84

ViPEr-HiSS: A Case for Storage Design Tools

The viability of large-scale multimedia applications, depends on the performance of storage systems. Providing cost-effective access to vast amounts of video, image, audio, and text data, requires (a) proper configuration of storage hierarchies as well as (b) efficient resource management techniques at all levels of the storage hierarchy. The resulting complexities of the hardware/software co-design in turn contribute to difficulties in making accurate predictions about performance, scalability, and cost-effectiveness of a storage system. Moreover, poor decisions at design time can be costly and problematic to correct in later stages of development. Hence, measurement of systems after they have been developed is not a desirable approach to predicting their performance. What is needed is the ability to evaluate the system's design while there are still opportunities to make corrections to fundamental design flaws. In this paper we describe the framework of ViPEr-HiSS, a tool which facilitates design, development, and subsequent performance evaluation of designs of multimedia storage hierarchies by providing mechanisms for relatively easy experimentation with (a) system configurations as well as (b) application- and media-aware resource management techniques. (Also cross-referenced as UMIACS-TR-99-69

A Pilot Study to Evaluate Development Effort for High Performance Computing

The ability to write programs that execute efficiently on modern parallel computers has not been fully studied. In a DARPA-sponsored project, we are looking at measuring the development time for programs written for high performance computers (HPC). To attack this relatively novel measurement problem, our goal is to initially measure such development time in student programming to evaluate our own experimental protocols. Based on these results, we will generate a set of feasible experimental methods that can then be applied with more confidence to professional expert programmers. This paper describes a first pilot study addressing those goals. We ran an observational study with 15 students in a graduate level High Performance Computing class at the University of Maryland. We collected data concerning development effort, developer activities and chronology, and resulting code performance, for two programming assignments using different HPC development approaches. While we did not find strong correlations between the expected factors, the primary outputs of this study are a set of experimental lessons learned and 12 wellformed hypotheses that will guard future study

Quantitative analyses and modelling to support achievement of the 2020 goals for nine neglected tropical diseases

Quantitative analysis and mathematical models are useful tools in informing strategies to control or eliminate disease. Currently, there is an urgent need to develop these tools to inform policy to achieve the 2020 goals for neglected tropical diseases (NTDs). In this paper we give an overview of a collection of novel model-based analyses which aim to address key questions on the dynamics of transmission and control of nine NTDs: Chagas disease, visceral leishmaniasis, human African trypanosomiasis, leprosy, soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. Several common themes resonate throughout these analyses, including: the importance of epidemiological setting on the success of interventions; targeting groups who are at highest risk of infection or re-infection; and reaching populations who are not accessing interventions and may act as a reservoir for infection,. The results also highlight the challenge of maintaining elimination ‘as a public health problem’ when true elimination is not reached. The models elucidate the factors that may be contributing most to persistence of disease and discuss the requirements for eventually achieving true elimination, if that is possible. Overall this collection presents new analyses to inform current control initiatives. These papers form a base from which further development of the models and more rigorous validation against a variety of datasets can help to give more detailed advice. At the moment, the models’ predictions are being considered as the world prepares for a final push towards control or elimination of neglected tropical diseases by 2020

Quantitative analyses and modelling to support achievement of the 2020 goals for nine neglected tropical diseases

Quantitative analysis and mathematical models are useful tools in informing strategies to control or eliminate disease. Currently, there is an urgent need to develop these tools to inform policy to achieve the 2020 goals for neglected tropical diseases (NTDs). In this paper we give an overview of a collection of novel model-based analyses which aim to address key questions on the dynamics of transmission and control of nine NTDs: Chagas disease, visceral leishmaniasis, human African trypanosomiasis, leprosy, soil-transmitted helminths, schistosomiasis, lymphatic filariasis, onchocerciasis and trachoma. Several common themes resonate throughout these analyses, including: the importance of epidemiological setting on the success of interventions; targeting groups who are at highest risk of infection or re-infection; and reaching populations who are not accessing interventions and may act as a reservoir for infection,. The results also highlight the challenge of maintaining elimination 'as a public health problem' when true elimination is not reached. The models elucidate the factors that may be contributing most to persistence of disease and discuss the requirements for eventually achieving true elimination, if that is possible. Overall this collection presents new analyses to inform current control initiatives. These papers form a base from which further development of the models and more rigorous validation against a variety of datasets can help to give more detailed advice. At the moment, the models' predictions are being considered as the world prepares for a final push towards control or elimination of neglected tropical diseases by 2020

Prevalence and architecture of de novo mutations in developmental disorders.

The genomes of individuals with severe, undiagnosed developmental disorders are enriched in damaging de novo mutations (DNMs) in developmentally important genes. Here we have sequenced the exomes of 4,293 families containing individuals with developmental disorders, and meta-analysed these data with data from another 3,287 individuals with similar disorders. We show that the most important factors influencing the diagnostic yield of DNMs are the sex of the affected individual, the relatedness of their parents, whether close relatives are affected and the parental ages. We identified 94 genes enriched in damaging DNMs, including 14 that previously lacked compelling evidence of involvement in developmental disorders. We have also characterized the phenotypic diversity among these disorders. We estimate that 42% of our cohort carry pathogenic DNMs in coding sequences; approximately half of these DNMs disrupt gene function and the remainder result in altered protein function. We estimate that developmental disorders caused by DNMs have an average prevalence of 1 in 213 to 1 in 448 births, depending on parental age. Given current global demographics, this equates to almost 400,000 children born per year