Peer-to-peer architectures for exascale computing : LDRD final report.

The goal of this research was to investigate the potential for employing dynamic, decentralized software architectures to achieve reliability in future high-performance computing platforms. These architectures, inspired by peer-to-peer networks such as botnets that already scale to millions of unreliable nodes, hold promise for enabling scientific applications to run usefully on next-generation exascale platforms ({approx} 10{sup 18} operations per second). Traditional parallel programming techniques suffer rapid deterioration of performance scaling with growing platform size, as the work of coping with increasingly frequent failures dominates over useful computation. Our studies suggest that new architectures, in which failures are treated as ubiquitous and their effects are considered as simply another controllable source of error in a scientific computation, can remove such obstacles to exascale computing for certain applications. We have developed a simulation framework, as well as a preliminary implementation in a large-scale emulation environment, for exploration of these 'fault-oblivious computing' approaches. High-performance computing (HPC) faces a fundamental problem of increasing total component failure rates due to increasing system sizes, which threaten to degrade system reliability to an unusable level by the time the exascale range is reached ({approx} 10{sup 18} operations per second, requiring of order millions of processors). As computer scientists seek a way to scale system software for next-generation exascale machines, it is worth considering peer-to-peer (P2P) architectures that are already capable of supporting 10{sup 6}-10{sup 7} unreliable nodes. Exascale platforms will require a different way of looking at systems and software because the machine will likely not be available in its entirety for a meaningful execution time. Realistic estimates of failure rates range from a few times per day to more than once per hour for these platforms. P2P architectures give us a starting point for crafting applications and system software for exascale. In the context of the Internet, P2P applications (e.g., file sharing, botnets) have already solved this problem for 10{sup 6}-10{sup 7} nodes. Usually based on a fractal distributed hash table structure, these systems have proven robust in practice to constant and unpredictable outages, failures, and even subversion. For example, a recent estimate of botnet turnover (i.e., the number of machines leaving and joining) is about 11% per week. Nonetheless, P2P networks remain effective despite these failures: The Conficker botnet has grown to {approx} 5 x 10{sup 6} peers. Unlike today's system software and applications, those for next-generation exascale machines cannot assume a static structure and, to be scalable over millions of nodes, must be decentralized. P2P architectures achieve both, and provide a promising model for 'fault-oblivious computing'. This project aimed to study the dynamics of P2P networks in the context of a design for exascale systems and applications. Having no single point of failure, the most successful P2P architectures are adaptive and self-organizing. While there has been some previous work applying P2P to message passing, little attention has been previously paid to the tightly coupled exascale domain. Typically, the per-node footprint of P2P systems is small, making them ideal for HPC use. The implementation on each peer node cooperates en masse to 'heal' disruptions rather than relying on a controlling 'master' node. Understanding this cooperative behavior from a complex systems viewpoint is essential to predicting useful environments for the inextricably unreliable exascale platforms of the future. We sought to obtain theoretical insight into the stability and large-scale behavior of candidate architectures, and to work toward leveraging Sandia's Emulytics platform to test promising candidates in a realistic (ultimately {ge} 10{sup 7} nodes) setting. Our primary example applications are drawn from linear algebra: a Jacobi relaxation solver for the heat equation, and the closely related technique of value iteration in optimization. We aimed to apply P2P concepts in designing implementations capable of surviving an unreliable machine of 10{sup 6} nodes

Functional activity of insulinoma cells (INS-1E) and pancreatic islets cultured in agarose cryogel sponges

Here, we describe the preparation, structure, and properties of cryogel sponges, which represent a new type of macroporous biomaterial for tissue engineering. Cryogels were produced through freeze-thawing techniques, either from agarose alone or from agarose with grafted gelatin. The aim of this study was to evaluate agarose cryogel sponges as scaffolds for Culturing both isolated pancreatic islets and insulinoma cells (INS-IE). In order to evaluate the effect of cell entrapment in artificial scaffolds, cell function reflected by insulin secretion and content was studied in cells cultivated for a 2-week period either in Culture plastic plates or in cryogel sponge disks. Our results show that tumor-derived INS-1E cells grown either on plastic or on cryogels do not differ in their proliferation, morphology, insulin release, and intracellular insulin content. However, isolated pancreatic islets cultivated on cryogels sponge show 15-fold higher basal insulin secretion at 3.0 mM glucose than islets cultivated on plastic plates and fail to respond to stimulation with 16.7 mM glucose. In addition, these islets have about 2-fold lower insulin content compared to those grown in plastic plates. It is possible that the cell dysfunction noted in these in vitro experiments is due to the effect of the limited oxygen supply to the islets cultivated in cryogel sponge. Further in vivo Studies are needed to clarify the nature of such an observation since according to previous reports, agarose and gelatin induce new vessel formation supporting enhanced oxygen supply. (c) 2005 Wiley Periodicals, Inc

Stochastic nash equilibrium problems: sample average approximation and applications

This paper presents a Nash equilibrium model where the underlying objective functions involve uncertainty and nonsmoothness. The well-known sample average approximation method is applied to solve the problem and the first order equilibrium conditions are characterized in terms of Clarke generalized gradients. Under some moderate conditions, it is shown that with probability one, a statistical estimator (a Nash equilibrium or a Nash-C-stationary point) obtained from sample average approximate equilibrium problem converges to its true counterpart. Moreover, under some calmness conditions of the Clarke generalized derivatives, it is shown that with probability approaching one exponentially fast by increasing sample size, the Nash-C-stationary point converges to a weak Nash-C-stationary point of the true problem. Finally, the model is applied to stochastic Nash equilibrium problem in the wholesale electricity market

Safety and efficacy of MD1003 (high-dose biotin) in patients with progressive multiple sclerosis (SPI2): a randomised, double-blind, placebo-controlled, phase 3 trial

Background: There is an unmet need to develop therapeutic interventions directed at the neurodegeneration that underlies progression in multiple sclerosis. High-dose, pharmaceutical-grade biotin (MD1003) might enhance neuronal and oligodendrocyte energetics, resulting in improved cell function, repair, or survival. The MS-SPI randomised, double-blind, placebo-controlled study found that MD1003 improved disability outcomes over 12 months in patients with progressive multiple sclerosis. The SPI2 study was designed to assess the safety and efficacy of MD1003 in progressive forms of multiple sclerosis in a larger, more representative patient cohort. / Methods: SPI2 was a randomised, double-blind, parallel-group, placebo-controlled trial done at 90 academic and community multiple sclerosis clinics across 13 countries. Patients were aged 18–65 years, had a diagnosis of primary or secondary progressive multiple sclerosis fulfilling the revised International Panel criteria and Lublin criteria, a Kurtzke pyramidal functional subscore of at least 2 (defined as minimal disability), an expanded disability status scale (EDSS) score of 3·5–6·5, a timed 25-foot walk (TW25) of less than 40 s, evidence of clinical disability progression, and no relapses in the 2 years before enrolment. Concomitant disease-modifying therapies were allowed. Patients were randomly assigned (1:1) by an independent statistician using an interactive web response system, with stratification by study site and disease history, to receive MD1003 (oral biotin 100 mg three times daily) or placebo. Participants, investigators, and assessors were masked to treatment assignment. The primary endpoint was a composite of the proportion of participants with confirmed improvement in EDSS or TW25 at month 12, confirmed at month 15, versus baseline. The primary endpoint was assessed in the intention-to-treat analysis set, after all participants completed the month 15 visit. Safety analyses included all participants who received at least one dose of MD1003. This trial is registered with ClinicalTrials.gov (NCT02936037) and the EudraCT database (2016-000700-29). / Findings: From Feb 22, 2017, to June 8, 2018, 642 participants were randomly assigned MD1003 (n=326) or placebo (n=316). The double-blind, placebo-controlled phase of the study ended when the primary endpoint for the last-entered participant was assessed on Nov 15, 2019. The mean time in the placebo-controlled phase was 20·1 months (SD 5·3; range 15–27). For the primary outcome, 39 (12%) of 326 patients in the MD1003 group compared with 29 (9%) of 316 in the placebo group improved at month 12, with confirmation at month 15 (odds ratio 1·35 [95% CI 0·81–2·26]). Treatment-emergent adverse events occurred in 277 (84%) of 331 participants in the MD1003 group and in 264 (85%) of 311 in the placebo group. 87 (26%) of 331 participants in the MD1003 group and 82 (26%) of 311 participants in the placebo group had at least one serious treatment-emergent adverse event. One (<1%) person died in the MD1003 group and there were no deaths in the placebo group. Despite use of mitigation strategies, MD1003 led to inaccurate laboratory results for tests using biotinylated antibodies. / Interpretation: This study showed that MD1003 did not significantly improve disability or walking speed in patients with progressive multiple sclerosis and thus, in addition to the potential of MD1003 for deleterious health consequences from interference of laboratory tests, MD1003 cannot be recommended for treatment of progressive multiple sclerosis. / Funding: MedDay Pharmaceuticals