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  1. ; ; ; ; ( , AISTATS 2021)
    Accepted Manuscript Full Text Available
  2. ; ; ; ; ( , ArXivorg)
    Accepted Manuscript Full Text Available
  3. ; ; ; ( , ArXivorg)
    Accepted Manuscript Full Text Available
  4. ; ; ; ; ; ; ; ; ; ; et al ( , In Proceedings of the Neural Information Processing Systems Conference (Neurips))
    Accepted Manuscript Full Text Available
  5. ; ; ; ; ; ; ; ; ( , CLEO: QELS_Fundamental Science 2020)
    Full Text Available 
  6. ; ; ; ; ; ; ; ( , BMC biology)
    Background: Dinoflagellates are taxonomically diverse and ecologically important phytoplankton that are ubiquitously present in marine and freshwater environments. Mostly photosynthetic, dinoflagellates provide the basis of aquatic primary production; most taxa are free-living, while some can form symbiotic and parasitic associations with other organisms. However, knowledge of the molecular mechanisms that underpin the adaptation of these organisms to diverse ecological niches is limited by the scarce availability of genomic data, partly due to their large genome sizes estimated up to 250 Gbp. Currently available dinoflagellate genome data are restricted to Symbiodiniaceae (particularly symbionts of reef-building corals) and parasitic lineages, from taxamore »that have smaller genome size ranges, while genomic information from more diverse free living species is still lacking. Results: Here, we present two draft diploid genome assemblies of the free-living dinoflagellate Polarella glacialis, isolated from the Arctic and Antarctica. We found that about 68% of the genomes are composed of repetitive sequence, with long terminal repeats likely contributing to intra-species structural divergence and distinct genome sizes (3.0 and 2.7 Gbp). For each genome, guided using full-length transcriptome data, we predicted > 50,000 high-quality protein-coding genes, of which ~40% are in unidirectional gene clusters and ~25% comprise single exons. Multi-genome comparison unveiled genes specific to P. glacialis and a common, putatively bacterial origin of ice-binding domains in cold-adapted dinoflagellates. Conclusions: Our results elucidate how selection acts within the context of a complex genome structure to facilitate local adaptation. Because most dinoflagellate genes are constitutively expressed, Polarella glacialis has enhanced transcriptional responses via unidirectional, tandem duplication of single-exon genes that encode functions critical to survival in cold, low-light polar environments. These genomes provide a foundational reference for future research on dinoflagellate evolution.« less
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  7. ; ; ; ; ; ; ; ; ; ( , the 32nd IEEE International Parallel and Distributed Processing Symposium (IPDPS))
    NAND flash-based Solid State Devices (SSDs) offer the desirable features of high performance, energy efficiency, and fast growing capacity. Thus, the use of SSDs is increasing in distributed storage systems. A key obstacle in this context is that the natural unbalance in distributed I/O workloads can result in wear imbalance across the SSDs in a distributed setting. This, in turn can have significant impact on the reliability, performance, and lifetime of the storage deployment. Extant load balancers for storage systems do not consider SSD wear imbalance when placing data, as the main design goal of such balancers is to extractmore »higher performance. Consequently, data migration is the only common technique for tackling wear imbalance, where existing data is moved from highly loaded servers to the least loaded ones. In this paper, we explore an innovative holistic approach, Chameleon, that employs data redundancy techniques such as replication and erasure-coding, coupled with endurance-aware write offloading, to mitigate wear level imbalance in distributed SSD-based storage. Chameleon aims to balance the wear among different flash servers while meeting desirable objectives of: extending life of flash servers; improving I/O performance; and avoiding bottlenecks. Evaluation with a 50 node SSD cluster shows that Chameleon reduces the wear distribution deviation by 81% while improving the write performance by up to 33%.« less
    Accepted Manuscript Full Text Available
  8. ; ; ; ; ; ( , Proceedings of IEEE 16th International Conference on Data Mining)
    Full Text Available 
  9. ; ; ; ; ( , Physical Review A)
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  10. ; ; ; ; ; ; ; ; ; ; et al ( , Physical Review Letters)
    Free, publicly-accessible full text available March 1, 2023