We expect that many-core microprocessors will push performance per chip from the 10 gigaflop to the 10 teraflop range in the coming decade. To support this increased performance, memory and inter-core bandwidths will also have to scale by orders of magnitude. Pin limitations, the energy cost of electrical signaling, and the non-scalability of chip-length global wires are significant bandwidth impediments. Recent developments in silicon nanophotonic technology have the potential to meet these off-and on-stack bandwidth requirements at acceptable power levels.Corona is a 3D many-core architecture that uses nanophotonic communication for both inter-core communication and off-stack communication to memory or I/O devices. Its peak floating-point performance is 10 teraflops. Dense wavelength division multiplexed optically connected memory modules provide 10 terabyte per second memory bandwidth. A photonic crossbar fully interconnects its 256 low-power multithreaded cores at 20 terabyte per second bandwidth. We have simulated a 1024 thread Corona system running synthetic benchmarks and scaled versions of the SPLASH-2 benchmark suite. We believe that in comparison with an electrically-connected many-core alternative that uses the same on-stack interconnect power, Corona can provide 2 to 6 times more performance on many memoryintensive workloads, while simultaneously reducing power.

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Age-Related Eye Disease Study Research Group* Objective: To evaluate the association of lipid intake with baseline severity of age-related macular degeneration (AMD) in the Age-Related Eye Disease Study (AREDS). Methods: Age-Related Eye Disease Study participants aged 60 to 80 years at enrollment (N = 4519) provided estimates of habitual nutrient intake through a selfadministered semiquantitative food frequency questionnaire. Stereoscopic color fundus photographs were used to categorize participants into 4 AMD severity groups and a control group (participants with Ͻ15 small drusen). Results: Dietary total-3 long-chain polyunsaturated fatty acid (LCPUFA) intake was inversely associated with neovascular (NV) AMD (odds ratio [OR], 0.61; 95% con

64Expression quantitative trait locus (eQTL) mapping provides a powerful means to identify func-65 tional variants influencing gene expression and disease pathogenesis. We report the identification 66 of cis-eQTLs from 7,051 post-mortem samples representing 44 tissues and 449 individuals as part 67 of the Genotype-Tissue Expression (GTEx) project. We find a cis-eQTL for 88% of all annotated 68 protein-coding genes, with one-third having multiple independent effects. We identify numerous 69 tissue-specific cis-eQTLs, highlighting the unique functional impact of regulatory variation in di-70 verse tissues. By integrating large-scale functional genomics data and state-of-the-art fine-mapping 71 algorithms, we identify multiple features predictive of tissue-specific and shared regulatory effects. 72 We improve estimates of cis-eQTL sharing and effect sizes using allele specific expression across tis-73 sues. Finally, we demonstrate the utility of this large compendium of cis-eQTLs for understanding 74 the tissue-specific etiology of complex traits, including coronary artery disease. The GTEx project 75 provides an exceptional resource that has improved our understanding of gene regulation across 76 tissues and the role of regulatory variation in human genetic diseases. 77 Introduction 78 Genome-wide association studies (GWAS) have identified a wealth of genetic variants associated 79 with complex traits and disease risk. However, characterizing the molecular and cellular mechanisms 80 through which these variants act remains a major challenge that limits our understanding of disease 81 pathogenesis and the development of therapeutic interventions. Expression quantitative trait locus 82 (eQTL) studies provide a systematic approach to characterize the molecular consequences of genetic 83 variation across tissues and cell types 1-4 . Multiple studies have identified eQTLs for thousands of 84 genes 5-7 , providing novel insights into gene regulation and enabling the interpretation of GWAS 85 signals 8-12 . These studies have largely been performed in a few easily accessible cell types and cell 86 lines, precluding interpretation of the systemic and tissue-specific consequences of genetic variation. 87To overcome these limitations, the Genotype Tissue Expression (GTEx) project was designed to 88 identify and characterize eQTLs across a broad range of tissues. During the pilot phase, which 89 focused on nine tissues, the GTEx project highlighted patterns of eQTL tissue-specificity and 90 demonstrated the value of multi-tissue study designs for identifying causal genes and tissues for 91 trait-associated variants 1 . These results indicated that the identification of eQTLs across an even 92 broader range of tissues would drastically improve characterization of the gene-and tissue-specific 93 consequences of genetic variants. 94Here, we report on the discovery of cis-eQTLs across an expanded collection of 44 tissues in 95 the GTEx V6p study. This dataset consists of 7,051 transcriptomes from 449 individuals and 96 4...

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