SEAD Virtual Archive: Building a Federation of Institutional Repositories for Long Term Data Preservation

Major research universities are grappling with their response to the deluge of scientific data emerging through research by their faculty. Many are looking to their libraries and the institutional repository as a solution. Scientific data introduces substantial challenges that the document-based institutional repository may not be suited to deal with. The Sustainable Environment - Actionable Data (SEAD) Virtual Archive specifically addresses the challenges of “long tail” scientific data. In this paper, we propose requirements, policy and architecture to support not only the preservation of scientific data today using institutional repositories, but also its rich access and use into the future

Development of feed for blue swimmer crab, Portunus pelagicus to reduce the dependency on fresh feeds for sustainable mariculture

Development of feed for blue swimmer crab, Portunus pelagicus to reduce the dependency on fresh feeds for sustainable maricultur

SEAD: Preserving Data for Environmental Sciences in Areas of Climate, Land-Use, and Environmental Management

SEAD is funded by the National Science Foundation under cooperative agreement #OCI094082

Runtime-guided management of stacked DRAM memories in task parallel programs

Stacked DRAM memories have become a reality in High-Performance Computing (HPC) architectures. These memories provide much higher bandwidth while consuming less power than traditional off-chip memories, but their limited memory capacity is insufficient for modern HPC systems. For this reason, both stacked DRAM and off-chip memories are expected to co-exist in HPC architectures, giving raise to different approaches for architecting the stacked DRAM in the system. This paper proposes a runtime approach to transparently manage stacked DRAM memories in task-based programming models. In this approach the runtime system is in charge of copying the data accessed by the tasks to the stacked DRAM, without any complex hardware support nor modifications to the application code. To mitigate the cost of copying data between the stacked DRAM and the off-chip memory, the proposal includes an optimization to parallelize the copies across idle or additional helper threads. In addition, the runtime system is aware of the reuse pattern of the data accessed by the tasks, and can exploit this information to avoid unworthy copies of data to the stacked DRAM. Results on the Intel Knights Landing processor show that the proposed techniques achieve an average speedup of 14% against the state-of-the-art library to manage the stacked DRAM and 29% against a stacked DRAM architected as a hardware cache.This work has been supported by the RoMoL ERC Advanced Grant (GA 321253), by the European HiPEAC Network of Excellence, by the Spanish Ministry of Economy and Competitiveness (contract TIN2015-65316-P), by the Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272) and by the European Union’s Horizon 2020 research and innovation programme (grant agreement 779877). M. Moreto has been partially supported by the Spanish Ministry of Economy, Industry and Competitiveness under Ramon y Cajal fellowship number RYC-2016-21104.Peer ReviewedPostprint (author's final draft

SEAD Virtual Archive: Building a Federation of Institutional Repositories for Long-Term Data Preservation in Sustainability Science

Major research universities are grappling with their response to the deluge of scientific data emerging through research by their faculty. Many are looking to their libraries and the institutional repositories for a solution. Scientific data introduces substantial challenges that the document-based institutional repository may not be suited to deal with. The Sustainable Environment - Actionable Data (SEAD) Virtual Archive (VA) specifically addresses the challenges of ‘long tail’ scientific data. In this paper, we propose requirements, policy and architecture to support not only the preservation of scientific data today using institutional repositories, but also rich access to data and their use into the future

Antioxidant defence system based oxidative stress mitigation through dietary jamun tree leaf in experimentally infected snubnose pompano, Trachinotus blochii

A 45-day feeding trial was conducted to evaluate the effect of dietary jamun tree leaf (JL) on the antioxidant defence system-based disease resistance in juveniles of Trachinotus blochii. The juveniles of snubnose pompano were distributed into four treatment groups in triplicates. Each treatment was fed with a diet containing either 0 (0JL), 0.5 (0.5JL), 1 (1JL) and 1.5% JL (1.5JL) in the feed. After feeding trial, the fishes were experimentally infected with Vibrio parahaemolyticus. The activities of oxidative stress enzymes such as superoxide dismutase and catalase were found to be increasing with increasing level of dietary JL incorporation, and the lower value was witnessed in control group in pre- and post-challenge. After challenge, the alanine and aspartate aminotransferase activities in all the treatments were significantly increased (P < 0.05) than the pre-challenge condition and exhibited reverse trend with the antioxidant enzymes. The alkaline and acid phosphatase activities were found higher in 1.5JL group and showed significant difference (P < 0.05) among the treatments. The respiratory burst activity and liver glycogen content showed an increasing trend as the level of inclusion of JL increased in the diet. The acetylcholinesterase activity was significantly plunged (P < 0.05) after experimental infection, and JL diet fed groups showed better activity. After experimental infection with V. parahaemolyticus, the highest relative percentage of survival was observed in 1JL and 1.5JL groups. Hence, dietary supplementation of jamun tree leaf at the level of 1% is adequate to reduce the oxidative stress and improved the innate immune status through antioxidant defence system

A performance model to execute workflows on high-bandwidth-memory architectures

International audienceThis work presents a realistic performance model to execute scientific workflows on high-bandwidth-memory architectures such as the Intel Knights Landing. We provide a detailed analysis of the execution time on such platforms, taking into account transfers from both fast and slow memory and their overlap with computations. We discuss several scheduling and mapping strategies: not only tasks must be assigned to computing resources, but also one has to decide which fraction of input and output data will reside in fast memory and which will have to stay in slow memory. We use extensive simulations to assess the impact of the mapping strategies on performance. We also conduct experiments for a simple 1D Gauss-Seidel kernel, which assess the accuracy of the model and further demonstrate the importance of a tuned memory management. Our model and results lay the foundations for further studies and experiments on dual-memory systems