Inference and Declaration of Independence in Task-Parallel Programs

The inherent difficulty of thread-based shared-memory programming has recently motivated research in high-level, task-parallel programming models. Recent advances of Task-Parallel models add implicit synchronization, where the system automatically detects and satisfies data dependencies among spawned tasks. However, dynamic dependence analysis incurs significant runtime overheads, because the runtime must track task resources and use this information to schedule tasks while avoiding conflicts and races.
We present SCOOP, a compiler that effectively integrates static and dynamic analysis in code generation. SCOOP combines context-sensitive points-to, control-flow, escape, and effect analyses to remove redundant dependence checks at runtime. Our static analysis can work in combination with existing dynamic analyses and task-parallel runtimes that use annotations to specify tasks and their memory footprints. We use our static dependence analysis to detect non-conflicting tasks and an existing dynamic analysis to handle the remaining dependencies. We evaluate the resulting hybrid dependence analysis on a set of task-parallel programs.

BDDT: Block-level Dynamic Dependence Analysis for Task-Based Parallelism

We present BDDT, a task-parallel runtime system that dynamically discovers and resolves dependencies among parallel tasks. BDDT allows the programmer to specify detailed task footprints on any memory address range, multidimensional array tile or dynamic region. BDDT uses a block-based dependence analysis with arbitrary granularity. The analysis is applicable to existing C programs without having to restructure object or array allocation, and provides flexibility in array layouts and tile dimensions.
We evaluate BDDT using a representative set of benchmarks, and we compare it to SMPSs (the equivalent runtime system in StarSs) and OpenMP. BDDT performs comparable to or better than SMPSs and is able to cope with task granularity as much as one order of magnitude finer than SMPSs. Compared to OpenMP, BDDT performs up to 3.9× better for benchmarks that benefit from dynamic dependence analysis. BDDT provides additional data annotations to bypass dependence analysis. Using these annotations, BDDT outperforms OpenMP also in benchmarks where dependence analysis does not discover additional parallelism, thanks to a more efficient implementation of the runtime system.

Using Mesh-Geometry Relationships to Transfer Analysis Models between CAE Tools

Integrating analysis and design models is a complex task due to differences between the models and the architectures of the toolsets used to create them. This complexity is increased with the use of many different tools for specific tasks during an analysis process. In this work various design and analysis models are linked throughout the design lifecycle, allowing them to be moved between packages in a way not currently available. Three technologies named Cellular Modeling, Virtual Topology and Equivalencing are combined to demonstrate how different finite element meshes generated on abstract analysis geometries can be linked to their original geometry. Establishing the equivalence relationships between models enables analysts to utilize multiple packages for specialist tasks without worrying about compatibility issues or rework.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods.

Food web indicators under the Marine Strategy Framework Directive: From complexity to simplicity?

The Marine Strategy Framework Directive (MSFD) requires that European Union Member States achieve "Good Environmental Status" (GES) in respect of 11 Descriptors of the marine environment by 2020. Of those, Descriptor 4, which focuses on marine food webs, is perhaps the most challenging to implement since the identification of simple indicators able to assess the health of highly dynamic and complex interactions is difficult. Here, we present the proposed food web criteria/indicators and analyse their theoretical background and applicability in order to highlight both the current knowledge gaps and the difficulties associated with the assessment of GES. We conclude that the existing suite of indicators gives variable focus to the three important food web properties: structure, functioning and dynamics, and more emphasis should be given to the latter two and the general principles that relate these three properties. The development of food web indicators should be directed towards more integrative and process-based indicators with an emphasis on their responsiveness to multiple anthropogenic pressures. (C) 2013 Elsevier Ltd. All rights reserved.

Analysis of Dependence Tracking Algorithms for Task Dataflow Execution

Processor architectures has taken a turn towards many-core processors, which integrate multiple processing cores on a single chip to increase overall performance, and there are no signs that this trend will stop in the near future. Many-core processors are harder to program than multi-core and single-core processors due to the need of writing parallel or concurrent programs with high degrees of parallelism. Moreover, many-cores have to operate in a mode of strong scaling because of memory bandwidth constraints. In strong scaling increasingly finer-grain parallelism must be extracted in order to keep all processing cores busy.

Task dataflow programming models have a high potential to simplify parallel program- ming because they alleviate the programmer from identifying precisely all inter-task de- pendences when writing programs. Instead, the task dataflow runtime system detects and enforces inter-task dependences during execution based on the description of memory each task accesses. The runtime constructs a task dataflow graph that captures all tasks and their dependences. Tasks are scheduled to execute in parallel taking into account dependences specified in the task graph.

Several papers report important overheads for task dataflow systems, which severely limits the scalability and usability of such systems. In this paper we study efficient schemes to manage task graphs and analyze their scalability. We assume a programming model that supports input, output and in/out annotations on task arguments, as well as commutative in/out and reductions. We analyze the structure of task graphs and identify versions and generations as key concepts for efficient management of task graphs. Then, we present three schemes to manage task graphs building on graph representations, hypergraphs and lists. We also consider a fourth edge-less scheme that synchronizes tasks using integers. Analysis using micro-benchmarks shows that the graph representation is not always scalable and that the edge-less scheme introduces least overhead in nearly all situations.

Ecological Relevance Determines Task Priority in Older Adults' Multitasking

Objectives: Multitasking is a challenging aspect of human behavior, especially if the concurrently performed tasks are different in nature. Several studies demonstrated pronounced performance decrements (dual-task costs) in older adults for combinations of cognitive and motor tasks. However, patterns of costs among component tasks differed across studies and reasons for participants' resource allocation strategies remained elusive.
Method:We investigated young and older adults' multitasking of a working memory task and two sensorimotor tasks, one with low (finger force control) and one with high ecological relevance (postural control). The tasks were performed in single-, dual-, and triple-task contexts.
Results: Working memory accuracy was reduced in dual-task contexts with either sensorimotor task and deteriorated further under triple-task conditions. Postural and force performance deteriorated with age and task difficulty in dual-task contexts. However, in the triple-task context with its maximum resource demands, older adults prioritized postural control
over both force control and memory.
Discussion: Our results identify ecological relevance as the key factor in older adults’ multitasking.

Neural correlates of task switching in paternal 15q11-q13 deletion Prader-Willi syndrome

We report a first study of brain activity linked to task switching in individuals with Prader-Willi syndrome (PWS) PWS individuals show a specific cognitive deficit in task switching which may be associated with the display of temper outbursts and repetitive questioning The performance of participants with PWS and typically developing controls was matched in a cued task switching procedure and brain activity was contrasted on switching and non switching blocks using SARI Individuals with PWS did not show the typical frontal-parietal pattern of neural activity associated with switching blocks, with significantly reduced activation in regions of the posterior parietal and ventromedial prefrontal cortices We suggest that this is linked to a difficulty in PWS in setting appropriate attentional weights to enable task set reconfiguration In addition to this, PWS individuals did not show the typical pattern of deactivation, with significantly less deactivation in an anterior region of the ventromedial prefrontal cortex One plausible explanation for this is that individuals with PWS show dysfunction within the default mode network which has been linked to attentional control The data point to functional changes in the neural circuitry supporting task switching in PWS even when behavioural performance is matched to controls and thus highlight neural mechanisms that may be involved in a specific pathway between genes cognition and behaviour (C) 2010 Elsevier B V All rights reserved

Task-switching deficits and repetitive behaviour in genetic neurodevelopmental disorders: Data from children with Prader-Willi syndrome chromosome 15 q11-q13 deletion and boys with Fragile X syndrome

Prader-Willi syndrome (PWS) and Fragile X syndrome (FraX) are associated with distinctive cognitive and behavioural profiles. We examined whether repetitive behaviours in the two syndromes were associated with deficits in specific executive functions. PWS, FraX, and typically developing (TD) children were assessed for executive functioning using the Test of Everyday Attention for Children and an adapted Simon spatial interference task. Relative to the TD children, children with PWS and FraX showed greater costs of attention switching on the Simon task, but after controlling for intellectual ability, these switching deficits were only significant in the PWS group. Children with PWS and FraX also showed significantly increased preference for routine and differing profiles of other specific types of repetitive behaviours. A measure of switch cost from the Simon task was positively correlated to scores on preference for routine questionnaire items and was strongly associated with scores on other items relating to a preference for predictability. It is proposed that a deficit in attention switching is a component of the endophenotypes of both PWS and FraX and is associated with specific behaviours. This proposal is discussed in the context of neurocognitive pathways between genes and behaviour.