A Three Step Blind Approach for Improving HPC Systems' Energy Performance

International audienceNowadays, there is no doubt that energy consumption has become a limiting factor in the design and operation of high performance computing (HPC) systems. This is evidenced by the rise of efforts both from the academia and the industry to reduce the energy consumption of those systems. Unlike hardware solutions, software initiatives targeting HPC systems' energy consumption reduction despite their effectiveness are often limited for reasons including: (i) the program specific nature of the solution proposed; (ii) the need of deep understanding of applications at hand; (iii) proposed solutions are often difficult to use by novices and/or are designed for single task environments. This paper propose a three step blind system-wide, application independent, fine-grain, and easy to use (user friendly) methodology for improving energy performance of HPC systems. The methodology typically breaks into phase detection, phase characterization, and phase identification and system reconfiguration. And it is blind in the sense that it does not require any knowledge from users. It relies upon reconfigurable capabilities offered by the majority of HPC subsystems -- including the processor, storage, memory, and communication subsystems -- to reduce the overall energy consumption of the system (excluding network equipments) at runtime. We also present an implementation of our methodology through which we demonstrate its effectiveness via static analyses and experiments using benchmarks representative of HPC workloads

Distributed Management of Massive Data: an Efficient Fine-Grain Data Access Scheme

This paper addresses the problem of efficiently storing and accessing massive data blocks in a large-scale distributed environment, while providing efficient fine-grain access to data subsets. This issue is crucial in the context of applications in the field of databases, data mining and multimedia. We propose a data sharing service based on distributed, RAM-based storage of data, while leveraging a DHT-based, natively parallel metadata management scheme. As opposed to the most commonly used grid storage infrastructures that provide mechanisms for explicit data localization and transfer, we provide a transparent access model, where data are accessed through global identifiers. Our proposal has been validated through a prototype implementation whose preliminary evaluation provides promising results

Optimization in a Self-Stabilizing Service Discovery Framework for Large Scale Systems

Ability to find and get services is a key requirement in the development of large-scale distributed sys- tems. We consider dynamic and unstable environments, namely Peer-to-Peer (P2P) systems. In previous work, we designed a service discovery solution called Distributed Lexicographic Placement Table (DLPT), based on a hierar- chical overlay structure. A self-stabilizing version was given using the Propagation of Information with Feedback (PIF) paradigm. In this paper, we introduce the self-stabilizing COPIF (for Collaborative PIF) scheme. An algo- rithm is provided with its correctness proof. We use this approach to improve a distributed P2P framework designed for the services discovery. Significantly efficient experimental results are presented

Statistical Guidance for Experimental Design and Data Analysis of Mutation Detection in Rare Monogenic Mendelian Diseases by Exome Sequencing

Recently, whole-genome sequencing, especially exome sequencing, has successfully led to the identification of causal mutations for rare monogenic Mendelian diseases. However, it is unclear whether this approach can be generalized and effectively applied to other Mendelian diseases with high locus heterogeneity. Moreover, the current exome sequencing approach has limitations such as false positive and false negative rates of mutation detection due to sequencing errors and other artifacts, but the impact of these limitations on experimental design has not been systematically analyzed. To address these questions, we present a statistical modeling framework to calculate the power, the probability of identifying truly disease-causing genes, under various inheritance models and experimental conditions, providing guidance for both proper experimental design and data analysis. Based on our model, we found that the exome sequencing approach is well-powered for mutation detection in recessive, but not dominant, Mendelian diseases with high locus heterogeneity. A disease gene responsible for as low as 5% of the disease population can be readily identified by sequencing just 200 unrelated patients. Based on these results, for identifying rare Mendelian disease genes, we propose that a viable approach is to combine, sequence, and analyze patients with the same disease together, leveraging the statistical framework presented in this work

Exome Sequencing and Genetic Testing for MODY

Context: Genetic testing for monogenic diabetes is important for patient care. Given the extensive genetic and clinical heterogeneity of diabetes, exome sequencing might provide additional diagnostic potential when standard Sanger sequencing-based diagnostics is inconclusive. Objective: The aim of the study was to examine the performance of exome sequencing for a molecular diagnosis of MODY in patients who have undergone conventional diagnostic sequencing of candidate genes with negative results. Research Design and Methods: We performed exome enrichment followed by high-throughput sequencing in nine patients with suspected MODY. They were Sanger sequencing-negative for mutations in the HNF1A, HNF4A, GCK, HNF1B and INS genes. We excluded common, non-coding and synonymous gene variants, and performed in-depth analysis on filtered sequence variants in a pre-defined set of 111 genes implicated in glucose metabolism. Results: On average, we obtained 45 X median coverage of the entire targeted exome and found 199 rare coding variants per individual. We identified 0–4 rare non-synonymous and nonsense variants per individual in our a priori list of 111 candidate genes. Three of the variants were considered pathogenic (in ABCC8, HNF4A and PPARG, respectively), thus exome sequencing led to a genetic diagnosis in at least three of the nine patients. Approximately 91% of known heterozygous SNPs in the target exomes were detected, but we also found low coverage in some key diabetes genes using our current exome sequencing approach. Novel variants in the genes ARAP1, GLIS3, MADD, NOTCH2 and WFS1 need further investigation to reveal their possible role in diabetes. Conclusion: Our results demonstrate that exome sequencing can improve molecular diagnostics of MODY when used as a complement to Sanger sequencing. However, improvements will be needed, especially concerning coverage, before the full potential of exome sequencing can be realized

Altered translation of GATA1 in Diamond-Blackfan anemia

Ribosomal protein haploinsufficiency occurs in diverse human diseases including Diamond-Blackfan anemia (DBA)[superscript 1, 2], congenital asplenia[superscript 3] and T cell leukemia[superscript 4]. Yet, how mutations in genes encoding ubiquitously expressed proteins such as these result in cell-type– and tissue-specific defects remains unknown[superscript 5]. Here, we identify mutations in GATA1, encoding the critical hematopoietic transcription factor GATA-binding protein-1, that reduce levels of full-length GATA1 protein and cause DBA in rare instances. We show that ribosomal protein haploinsufficiency, the more common cause of DBA, can lead to decreased GATA1 mRNA translation, possibly resulting from a higher threshold for initiation of translation of this mRNA in comparison with other mRNAs. In primary hematopoietic cells from patients with mutations in RPS19, encoding ribosomal protein S19, the amplitude of a transcriptional signature of GATA1 target genes was globally and specifically reduced, indicating that the activity, but not the mRNA level, of GATA1 is decreased in patients with DBA associated with mutations affecting ribosomal proteins. Moreover, the defective hematopoiesis observed in patients with DBA associated with ribosomal protein haploinsufficiency could be partially overcome by increasing GATA1 protein levels. Our results provide a paradigm by which selective defects in translation due to mutations affecting ubiquitous ribosomal proteins can result in human disease.National Institutes of Health (U.S.) (Grant P01 HL32262)National Institutes of Health (U.S.) (Grant U54 HG003067-09

Chemotherapy is not needed when complete evacuation of gestational choriocarcinoma leads to hCG normalisation.

peer reviewe

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19

Background We previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15–20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in ~ 80% of cases. Methods We report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded. Results No gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5–528.7, P = 1.1 × 10−4) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR = 3.70[95%CI 1.3–8.2], P = 2.1 × 10−4). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR = 19.65[95%CI 2.1–2635.4], P = 3.4 × 10−3), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR = 4.40[9%CI 2.3–8.4], P = 7.7 × 10−8). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD] = 43.3 [20.3] years) than the other patients (56.0 [17.3] years; P = 1.68 × 10−5). Conclusions Rare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old

Modeling of Intermediate Structures and Chain Conformation in Silica-Latex Nanocomposites Observed by SANS During Annealing

The evolution of the polymer structure during nanocomposite formation and annealing of silica-latex nanocomposites is studied using contrast-variation small angle neutron scattering. The experimental system is made of silica nanoparticles (Rsi \approx 8 nm) and a mixture of purpose-synthesized hydrogenated and deuterated nanolatex (Rlatex \approx 12.5 nm). The progressive disappearance of the latex beads by chain interdiffusion and release in the nanocomposites is analyzed quantitatively with a model for the scattered intensity of hairy latex beads and an RPA description of the free chains. In silica-free matrices and nanocomposites of low silica content (7%v), the annealing procedure over weeks at up to Tg + 85 K results in a molecular dispersion of chains, the radius of gyration of which is reported. At higher silica content (20%v), chain interdiffusion seems to be slowed down on time-scales of weeks, reaching a molecular dispersion only at the strongest annealing. Chain radii of gyration are found to be unaffected by the presence of the silica filler

IL-12Rβ1 Deficiency in Two of Fifty Children with Severe Tuberculosis from Iran, Morocco, and Turkey

BACKGROUND AND OBJECTIVES: In the last decade, autosomal recessive IL-12Rβ1 deficiency has been diagnosed in four children with severe tuberculosis from three unrelated families from Morocco, Spain, and Turkey, providing proof-of-principle that tuberculosis in otherwise healthy children may result from single-gene inborn errors of immunity. We aimed to estimate the fraction of children developing severe tuberculosis due to IL-12Rβ1 deficiency in areas endemic for tuberculosis and where parental consanguinity is common. METHODS AND PRINCIPAL FINDINGS: We searched for IL12RB1 mutations in a series of 50 children from Iran, Morocco, and Turkey. All children had established severe pulmonary and/or disseminated tuberculosis requiring hospitalization and were otherwise normally resistant to weakly virulent BCG vaccines and environmental mycobacteria. In one child from Iran and another from Morocco, homozygosity for loss-of-function IL12RB1 alleles was documented, resulting in complete IL-12Rβ1 deficiency. Despite the small sample studied, our findings suggest that IL-12Rβ1 deficiency is not a very rare cause of pediatric tuberculosis in these countries, where it should be considered in selected children with severe disease. SIGNIFICANCE: This finding may have important medical implications, as recombinant IFN-γ is an effective treatment for mycobacterial infections in IL-12Rβ1-deficient patients. It also provides additional support for the view that severe tuberculosis in childhood may result from a collection of single-gene inborn errors of immunity