Predicting performance of non-contiguous I/O with machine learning

Data sieving in ROMIO promises to optimize individual non-contiguous I/O. However, making the right choice and parameterizing its buffer size accordingly are non-trivial tasks, since predicting the resulting performance is difficult. Since many performance factors are not taken into account by data sieving, extracting the optimal performance for a given access pattern and system is often not possible. Additionally, in Lustre, settings such as the stripe size and number of servers are tunable, yet again, identifying rules for the data-centre proves challenging indeed. In this paper, we (1) discuss limitations of data sieving, (2) apply machine learning techniques to build a performance predictor, and (3) learn and extract best practices for the settings from the data. We used decision trees as these models can capture non-linear behavior, are easy to understand and allow for extraction of the rules used. Even though this initial research is based on decision trees, with sparse training data, the algorithm can predict many cases sufficiently. Compared to a standard setting, the decision trees created are able to improve performance significantly and we can derive expert knowledge by extracting rules from the learned tree. Applying the scheme to a set of experimental data improved the average throughput by 25–50 % of the best parametrization’s gain. Additionally, we demonstrate the versatility of this approach by applying it to the porting system of DKRZ’s next generation supercomputer and discuss achievable performance gains

Beyond keratinocyte differentiation: emerging new biology of small proline-rich proteins.

Small proline-rich proteins (SPRRPs) are traditionally known for their function in keratinocyte homeostasis. Recent evidence demonstrates their involvement in additional diverse physiological processes ranging from p53 signaling and direct prevention of DNA damage to bactericidal activities. We highlight these novel, intriguing roles of SPRRPs and discuss them in the context of relevant pathological conditions

Monitoring energy consumption with SIOX

In the face of the growing complexity of HPC systems, their growing energy costs, and the increasing difficulty to run applications efficiently, a number of monitoring tools have been developed during the last years. SIOX is one such endeavor, with a uniquely holistic approach: Not only does it aim to record a certain kind of data, but to make all relevant data available for analysis and optimization. Among other sources, this encompasses data from hardware energy counters and trace data from different hardware/software layers. However, not all data that can be recorded should be recorded. As such, SIOX needs good heuristics to determine when and what data needs to be collected, and the energy consumption can provide an important signal about when the system is in a state that deserves closer attention. In this paper, we show that SIOX can use Likwid to collect and report the energy consumption of applications, and present how this data can be visualized using SIOX’s web-interface. Furthermore, we outline how SIOX can use this information to intelligently adjust the amount of data it collects, allowing it to reduce the monitoring overhead while still providing complete information about critical situations

DNA-PK in human malignant disorders: Mechanisms and implications for pharmacological interventions.

The DNA-PK holoenzyme is a fundamental element of the DNA damage response machinery (DDR), which is responsible for cellular genomic stability. Consequently, and predictably, over the last decades since its identification and characterization, numerous pre-clinical and clinical studies reported observations correlating aberrant DNA-PK status and activity with cancer onset, progression and responses to therapeutic modalities. Notably, various studies have established in recent years the role of DNA-PK outside the DDR network, corroborating its role as a pleiotropic complex involved in transcriptional programs that operate biologic processes as epithelial to mesenchymal transition (EMT), hypoxia, metabolism, nuclear receptors signaling and inflammatory responses. In particular tumor entities as prostate cancer, immense research efforts assisted mapping and describing the overall signaling networks regulated by DNA-PK that control metastasis and tumor progression. Correspondingly, DNA-PK emerges as an obvious therapeutic target in cancer and data pertaining to various pharmacological approaches have been published, largely in context of combination with DNA-damaging agents (DDAs) that act by inflicting DNA double strand breaks (DSBs). Currently, new generation inhibitors are tested in clinical trials. Several excellent reviews have been published in recent years covering the biology of DNA-PK and its role in cancer. In the current article we are aiming to systematically describe the main findings on DNA-PK signaling in major cancer types, focusing on both preclinical and clinical reports and present a detailed current status of the DNA-PK inhibitors repertoire

The SIOX architecture – coupling automatic monitoring and optimization of parallel I/O

Performance analysis and optimization of high-performance I/O systems is a daunting task. Mainly, this is due to the overwhelmingly complex interplay of the involved hardware and software layers. The Scalable I/O for Extreme Performance (SIOX) project provides a versatile environment for monitoring I/O activities and learning from this information. The goal of SIOX is to automatically suggest and apply performance optimizations, and to assist in locating and diagnosing performance problems. In this paper, we present the current status of SIOX. Our modular architecture covers instrumentation of POSIX, MPI and other high-level I/O libraries; the monitoring data is recorded asynchronously into a global database, and recorded traces can be visualized. Furthermore, we offer a set of primitive plug-ins with additional features to demonstrate the flexibility of our architecture: A surveyor plug-in to keep track of the observed spatial access patterns; an fadvise plug-in for injecting hints to achieve read-ahead for strided access patterns; and an optimizer plug-in which monitors the performance achieved with different MPI-IO hints, automatically supplying the best known hint-set when no hints were explicitly set. The presentation of the technical status is accompanied by a demonstration of some of these features on our 20 node cluster. In additional experiments, we analyze the overhead for concurrent access, for MPI-IO’s 4-levels of access, and for an instrumented climate application. While our prototype is not yet full-featured, it demonstrates the potential and feasibility of our approach

Correction: An oncogene addiction phosphorylation signature and its derived scores inform tumor responsiveness to targeted therapies.

ISSN:1420-682XISSN:1420-907

An oncogene addiction phosphorylation signature and its derived scores inform tumor responsiveness to targeted therapies.

PURPOSE Oncogene addiction provides important therapeutic opportunities for precision oncology treatment strategies. To date the cellular circuitries associated with driving oncoproteins, which eventually establish the phenotypic manifestation of oncogene addiction, remain largely unexplored. Data suggest the DNA damage response (DDR) as a central signaling network that intersects with pathways associated with deregulated addicting oncoproteins with kinase activity in cancer cells. EXPERIMENTAL DESIGN: We employed a targeted mass spectrometry approach to systematically explore alterations in 116 phosphosites related to oncogene signaling and its intersection with the DDR following inhibition of the addicting oncogene alone or in combination with irradiation in MET-, EGFR-, ALK- or BRAF (V600)-positive cancer models. An NSCLC tissue pipeline combining patient-derived xenografts (PDXs) and ex vivo patient organotypic cultures has been established for treatment responsiveness assessment. RESULTS We identified an 'oncogene addiction phosphorylation signature' (OAPS) consisting of 8 protein phosphorylations (ACLY S455, IF4B S422, IF4G1 S1231, LIMA1 S490, MYCN S62, NCBP1 S22, P3C2A S259 and TERF2 S365) that are significantly suppressed upon targeted oncogene inhibition solely in addicted cell line models and patient tissues. We show that the OAPS is present in patient tissues and the OAPS-derived score strongly correlates with the ex vivo responses to targeted treatments. CONCLUSIONS We propose a score derived from OAPS as a quantitative measure to evaluate oncogene addiction of cancer cell samples. This work underlines the importance of protein phosphorylation assessment for patient stratification in precision oncology and corresponding identification of tumor subtypes sensitive to inhibition of a particular oncogene

Lives without imagery:Congenital aphantasia

This is the author’s version of a work that was accepted for publication in Cortex. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published at doi:10.1016/j.cortex.2015.05.019

Studying Children's Intrapersonal Emotion Regulation Strategies from the Process Model of Emotion Regulation

peerreview_statement: The publishing and review policy for this title is described in its Aims & Scope. aims_and_scope_url: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=vgnt2

Construction of a Global Pain Systems Network Highlights Phospholipid Signaling as a Regulator of Heat Nociception

The ability to perceive noxious stimuli is critical for an animal's survival in the face of environmental danger, and thus pain perception is likely to be under stringent evolutionary pressure. Using a neuronal-specific RNAi knock-down strategy in adult Drosophila, we recently completed a genome-wide functional annotation of heat nociception that allowed us to identify α2δ3 as a novel pain gene. Here we report construction of an evolutionary-conserved, system-level, global molecular pain network map. Our systems map is markedly enriched for multiple genes associated with human pain and predicts a plethora of novel candidate pain pathways. One central node of this pain network is phospholipid signaling, which has been implicated before in pain processing. To further investigate the role of phospholipid signaling in mammalian heat pain perception, we analysed the phenotype of PIP5Kα and PI3Kγ mutant mice. Intriguingly, both of these mice exhibit pronounced hypersensitivity to noxious heat and capsaicin-induced pain, which directly mapped through PI3Kγ kinase-dead knock-in mice to PI3Kγ lipid kinase activity. Using single primary sensory neuron recording, PI3Kγ function was mechanistically linked to a negative regulation of TRPV1 channel transduction. Our data provide a systems map for heat nociception and reinforces the extraordinary conservation of molecular mechanisms of nociception across different species. © 2012 Neely et al