Optimizing the MapReduce Framework on Intel Xeon Phi Coprocessor

With the ease-of-programming, flexibility and yet efficiency, MapReduce has become one of the most popular frameworks for building big-data applications. MapReduce was originally designed for distributed-computing, and has been extended to various architectures, e,g, multi-core CPUs, GPUs and FPGAs. In this work, we focus on optimizing the MapReduce framework on Xeon Phi, which is the latest product released by Intel based on the Many Integrated Core Architecture. To the best of our knowledge, this is the first work to optimize the MapReduce framework on the Xeon Phi. In our work, we utilize advanced features of the Xeon Phi to achieve high performance. In order to take advantage of the SIMD vector processing units, we propose a vectorization friendly technique for the map phase to assist the auto-vectorization as well as develop SIMD hash computation algorithms. Furthermore, we utilize MIMD hyper-threading to pipeline the map and reduce to improve the resource utilization. We also eliminate multiple local arrays but use low cost atomic operations on the global array for some applications, which can improve the thread scalability and data locality due to the coherent L2 caches. Finally, for a given application, our framework can either automatically detect suitable techniques to apply or provide guideline for users at compilation time. We conduct comprehensive experiments to benchmark the Xeon Phi and compare our optimized MapReduce framework with a state-of-the-art multi-core based MapReduce framework (Phoenix++). By evaluating six real-world applications, the experimental results show that our optimized framework is 1.2X to 38X faster than Phoenix++ for various applications on the Xeon Phi

Transcriptome Changes in Relation to Manic Episode

Bipolar disorder (BD) is highly heritable and well known for its recurrent manic and depressive episodes. The present study focused on manic episode in BD patients and aimed to investigate state-specific transcriptome alterations between acute episode and remission, including messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and micro-RNAs (miRNAs), using microarray and RNA sequencing (RNA-Seq) platforms. BD patients were enrolled with clinical information, and peripheral blood samples collected at both acute and remission status spanning for at least 2 months were confirmed by follow-ups. Symptom severity was assessed by Young Mania Rating Scale. We enrolled six BD patients as the discovery samples and used the Affymetrix Human Transcriptome Array 2.0 to capture transcriptome data at the two time points. For replication, expression data from Gene Expression Omnibus that consisted of 11 BD patients were downloaded, and we performed a mega-analysis for microarray data of 17 patients. Moreover, we conducted RNA sequencing (RNA-Seq) in additional samples of 7 BD patients. To identify intraindividual differentially expressed genes (DEGs), we analyzed data using a linear model controlling for symptom severity. We found that noncoding genes were of majority among the top DEGs in microarray data. The expression fold change of coding genes among DEGs showed moderate to high correlations (∼0.5) across platforms. A number of lncRNAs and two miRNAs (MIR181B1 and MIR103A1) exhibited high levels of gene expression in the manic state. For coding genes, we reported that the taste function-related genes, including TAS2R5 and TAS2R3, may be mania state-specific markers. Additionally, four genes showed a nominal p-value of less than 0.05 in all our microarray data, mega-analysis, and RNA-Seq analysis. They were upregulated in the manic state and consisted of MS4A14, PYHIN1, UTRN, and DMXL2, and their gene expression patterns were further validated by quantitative real-time polymerase chain reaction (PCR) (qRT-PCR). We also performed weight gene coexpression network analysis to identify gene modules for manic episode. Genes in the mania-related modules were different from the susceptible loci of BD obtained from genome-wide association studies, and biological pathways in relation to these modules were mainly related to immune function, especially cytokine–cytokine receptor interaction. Results of the present study elucidated potential molecular targets and genomic networks that are involved in manic episode. Future studies are needed to further validate these biomarkers for their roles in the etiology of bipolar illness

Pendekatan Lean Manufacturing Untuk Meningkatkan Efisiensi Dalam Proses Produksi Dengan Menggunakan Value Stream Mapping Pada CV. Indospice

CV. INDOSPICE merupakan Perusahaan yang bergerak pada produksi pala, untuk terus mengoptimalkan kinerja produktifitasnya dan meningkatkatkan laba Perusahaan dengan berusaha menurunkan biaya, meningkatkan kualitas dan tepat waktu dalam pengiriman ke pelanggan. Penelitian ini bertujuan untuk mengetahui berbagai bentuk pemborosan (waste) apa saja yang sering terjadi sehingga dapat meningkatkan efisiensi produksi, karena itu diperlukan suatu pendekatan lean manufacturing. Lean Manufacturing merupakan sebuah pendekatan untuk meminimisasi pemborosan yang terjadi dalam proses produksi melalui value stream mapping untuk meningkatkan efisiensi. Metode yang digunakan dalam penelitian ini adalah deskriptif yang dilakukan dengan meneliti analisa pekerjaan dan aktifitas pada suatu obyek. Hasil penelitian menunjukan bahwa dalam proses produksi yang terjadi masih terdapat bentuk pemborosan berupa proses yang berlebih dan penggunaan mesin yang belum optimal. Untuk itu perlu upaya untuk meningkatkan efisisen berupa penambahan mesin penggiling pala dan pengadaan teknologi modern agar pengerjaan menjadi lebih cepat

The Association Between the Sedative Loads and Clinical Severity Indicators in the First-Onset Major Depressive Disorder

Background: High sedative use in a major depressive episode may imply specific clinical features. This study aims to examine the correlation between sedative use and clinical severity indicators in the initial treatment phase of first-onset major depressive disorder.Methods: A study cohort in the first episode of major depressive disorder was used to conduct pharmacological dissection. All participants had at least a 2-year follow-up period with a complete treatment record. The defined daily dose of antidepressants and augmentation agents were calculated as the antidepressant load and augmentation load, respectively. Sedative use, which was calculated as the equivalent dosage of lorazepam, were defined as the sedative load. These psychotropic loads were measured monthly and the averaged psychotropic loads for each day were obtained.Results: A total of 106 individuals (75.5% female) were included. The mean duration of disease course in participants was 5.5 ± 3.5 years. In the multiple regression analysis, after controlling for other classes of psychotropics and comorbid anxiety disorders, the sedative load independently correlated with higher number of antidepressants used, higher number of antidepressant used with an adequate dose and duration, more psychiatric emergency and outpatient visits within 2 years of disease onset.Conclusion: High loading of sedatives correlated with several indicators of clinical severity in major depressive disorder. The sedative load may be used as a specifier to identify subgroups in patients with major depressive disorder

Integrated Analyses of Copy Number Variations and Gene Expression in Lung Adenocarcinoma

Numerous efforts have been made to elucidate the etiology and improve the treatment of lung cancer, but the overall five-year survival rate is still only 15%. Identification of prognostic biomarkers for lung cancer using gene expression microarrays poses a major challenge in that very few overlapping genes have been reported among different studies. To address this issue, we have performed concurrent genome-wide analyses of copy number variation and gene expression to identify genes reproducibly associated with tumorigenesis and survival in non-smoking female lung adenocarcinoma. The genomic landscape of frequent copy number variable regions (CNVRs) in at least 30% of samples was revealed, and their aberration patterns were highly similar to several studies reported previously. Further statistical analysis for genes located in the CNVRs identified 475 genes differentially expressed between tumor and normal tissues (p<10−5). We demonstrated the reproducibility of these genes in another lung cancer study (p = 0.0034, Fisher's exact test), and showed the concordance between copy number variations and gene expression changes by elevated Pearson correlation coefficients. Pathway analysis revealed two major dysregulated functions in lung tumorigenesis: survival regulation via AKT signaling and cytoskeleton reorganization. Further validation of these enriched pathways using three independent cohorts demonstrated effective prediction of survival. In conclusion, by integrating gene expression profiles and copy number variations, we identified genes/pathways that may serve as prognostic biomarkers for lung tumorigenesis

Down-Regulation of NDRG1 Promotes Migration of Cancer Cells during Reoxygenation

One characteristic of tumor microenvironment is oxygen fluctuation, which results from hyper-proliferation and abnormal metabolism of tumor cells as well as disorganized neo-vasculature. Reoxygenation of tumors can induce oxidative stress, which leads to DNA damage and genomic instability. Although the cellular responses to hypoxia are well known, little is known about the dynamic response upon reoxygenation. In order to investigate the transcriptional responses of tumor adaptation to reoxygenation, breast cancer MCF-7 cells were cultured under 0.5% oxygen for 24 h followed by 24 h of reoxygenation in normoxia. Cells were harvested at 0, 1, 4, 8, 12, and 24 h during reoxygenation. The transcriptional profile of MCF-7 cells upon reoxygenation was examined using Illumina Human-6 v3 BeadChips. We identified 127 differentially expressed genes, of which 53.1% were up-regulated and 46.9% were down-regulated upon reoxygenation. Pathway analysis revealed that the HIF-1-alpha transcription factor network and validated targets of C-MYC transcriptional activation were significantly enriched in these differentially expressed genes. Among these genes, a subset of interest genes was further validated by quantitative reverse-transcription PCR. In particular, human N-MYC down-regulated gene 1 (NDRG1) was highly suppressed upon reoxygenation. NDRG1 is associated with a variety of stress and cell growth-regulatory conditions. To determine whether NDRG1 plays a role in reoxygenation, NDRG1 protein was overexpressed in MCF-7 cells. Upon reoxygenation, overexpression of NDRG1 significantly inhibited cell migration. Our results revealed the dynamic nature of gene expression in MCF-7 cells upon reoxygenation and demonstrated that NDRG1 is involved in tumor adaptation to reoxygenation