17 research outputs found
Comparative and demographic analysis of orang-utan genomes
Orang-utan- is derived from a Malay term meaning man of the forest- and aptly describes the southeast Asian great apes native to Sumatra and Borneo. The orang-utan species, Pongo abelii (Sumatran) and Pongo pygmaeus (Bornean), are the most phylogenetically distant great apes from humans, thereby providing an informative perspective on hominid evolution. Here we present a Sumatran orang-utan draft genome assembly and short read sequence data from five Sumatran and five Bornean orang-utan genomes. Our analyses reveal that, compared to other primates, the orang-utan genome has many unique features. Structural evolution of the orang-utan genome has proceeded much more slowly than other great apes, evidenced by fewer rearrangements, less segmental duplication, a lower rate of gene family turnover and surprisingly quiescent Alu repeats, which have played a major role in restructuring other primate genomes. We also describe a primate polymorphic neocentromere, found in both Pongo species, emphasizing the gradual evolution of orang-utan genome structure. Orang-utans have extremely low energy usage for a eutherian mammal, far lower than their hominid relatives. Adding their genome to the repertoire of sequenced primates illuminates new signals of positive selection in several pathways including glycolipid metabolism. From the population perspective, both Pongo species are deeply diverse; however, Sumatran individuals possess greater diversity than their Bornean counterparts, and more species-specific variation. Our estimate of Bornean/Sumatran speciation time, 400,000years ago, is more recent than most previous studies and underscores the complexity of the orang-utan speciation process. Despite a smaller modern census population size, the Sumatran effective population size (N e) expanded exponentially relative to the ancestral N e after the split, while Bornean N e declined over the same period. Overall, the resources and analyses presented here offer new opportunities in evolutionary genomics, insights into hominid biology, and an extensive database of variation for conservation efforts. © 2011 Macmillan Publishers Limited. All rights reserved
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Modeling the Office of Science Ten Year Facilities Plan: The PERI Architecture Tiger Team
The Performance Engineering Institute (PERI) originally proposed a tiger team activity as a mechanism to target significant effort optimizing key Office of Science applications, a model that was successfully realized with the assistance of two JOULE metric teams. However, the Office of Science requested a new focus beginning in 2008: assistance in forming its ten year facilities plan. To meet this request, PERI formed the Architecture Tiger Team, which is modeling the performance of key science applications on future architectures, with S3D, FLASH and GTC chosen as the first application targets. In this activity, we have measured the performance of these applications on current systems in order to understand their baseline performance and to ensure that our modeling activity focuses on the right versions and inputs of the applications. We have applied a variety of modeling techniques to anticipate the performance of these applications on a range of anticipated systems. While our initial findings predict that Office of Science applications will continue to perform well on future machines from major hardware vendors, we have also encountered several areas in which we must extend our modeling techniques in order to fulfill our mission accurately and completely. In addition, we anticipate that models of a wider range of applications will reveal critical differences between expected future systems, thus providing guidance for future Office of Science procurement decisions, and will enable DOE applications to exploit machines in future facilities fully
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Performance Engineering: Understanding and Improving the Performance of Large-Scale Codes
Achieving good performance on high-end computing systems is growing ever more challenging due to enormous scale, increasing architectural complexity, and increasing application complexity. To address these challenges in DOE's SciDAC-2 program, the Performance Engineering Research Institute (PERI) has embarked on an ambitious research plan encompassing performance modeling and prediction, automatic performance optimization and performance engineering of high profile applications. The principal new component is a research activity in automatic tuning software, which is spurred by the strong user preference for automatic tools