Asynchronous Snapshots of Actor Systems for Latency-Sensitive Applications

The actor model is popular for many types of server applications. Efficient snapshotting of applications is crucial in the deployment of pre-initialized applications or moving running applications to different machines, e.g for debugging purposes. A key issue is that snapshotting blocks all other operations. In modern latency-sensitive applications, stopping the application to persist its state needs to be avoided, because users may not tolerate the increased request latency. In order to minimize the impact of snapshotting on request latency, our approach persists the application’s state asynchronously by capturing partial heaps, completing snapshots step by step. Additionally, our solution is transparent and supports arbitrary object graphs. We prototyped our snapshotting approach on top of the Truffle/Graal platform and evaluated it with the Savina benchmarks and the Acme Air microservice application. When performing a snapshot every thousand Acme Air requests, the number of slow requests ( 0.007% of all requests) with latency above 100ms increases by 5.43%. Our Savina microbenchmark results detail how different utilization patterns impact snapshotting cost. To the best of our knowledge, this is the first system that enables asynchronous snapshotting of actor applications, i.e. without stop-the-world synchronization, and thereby minimizes the impact on latency. We thus believe it enables new deployment and debugging options for actor systems

FfDL : A Flexible Multi-tenant Deep Learning Platform

Deep learning (DL) is becoming increasingly popular in several application domains and has made several new application features involving computer vision, speech recognition and synthesis, self-driving automobiles, drug design, etc. feasible and accurate. As a result, large scale on-premise and cloud-hosted deep learning platforms have become essential infrastructure in many organizations. These systems accept, schedule, manage and execute DL training jobs at scale. This paper describes the design, implementation and our experiences with FfDL, a DL platform used at IBM. We describe how our design balances dependability with scalability, elasticity, flexibility and efficiency. We examine FfDL qualitatively through a retrospective look at the lessons learned from building, operating, and supporting FfDL; and quantitatively through a detailed empirical evaluation of FfDL, including the overheads introduced by the platform for various deep learning models, the load and performance observed in a real case study using FfDL within our organization, the frequency of various faults observed including unanticipated faults, and experiments demonstrating the benefits of various scheduling policies. FfDL has been open-sourced.Comment: MIDDLEWARE 201

Antibiotic prescribing by age, sex, race, and ethnicity for patients admitted to the hospital with community-acquired bacterial pneumonia (CABP) in the All of Us database

Abstract Purpose: To assess the proportion of inpatients who received guideline-concordant antibiotics for community-acquired bacterial pneumonia (CABP) in special populations of the All of Us database. Background: CABP contributes significantly to healthcare burden worldwide. The American Thoracic Society and Infectious Disease Society of America jointly published guidelines for the treatment of CABP. Guideline-concordant antibiotics for CABP are associated with better patient and cost outcomes. Methods: This was a retrospective cohort study of patients with pneumonia (n = 1608; SNOMED 233604007) from 10/1/2018 to 1/01/22 in the All of Us database. Cases were excluded for treatment setting other than inpatient, prior (within 90 days) pneumonia, receipt of intravenous antibiotics, respiratory isolation of methicillin-resistant Staphylococcus aureus (MRSA) or Pseudomonas aeruginosa, and/or other non-community-acquired types of pneumonia. Patients were grouped based on patient age, sex, race, and ethnicity. The proportion of patients on guideline-concordant therapy was compared within groups using chi-square statistics. Significant associations were assessed using multivariate logistic regression models. Results: A total of 1608 cases were included, and 45% of these patients received guideline-concordant antibiotics. Non-Hispanic White (NHW) patients vs. Black patients were associated with a 36% higher likelihood for receiving guideline-concordant antibiotics (adjusted OR, 1.36; 95% CI 1.02–1.81), whereas NHW vs. Hispanic patients were associated with a 34% lower likelihood for receiving guideline-concordant antibiotics (aOR 0.66; 0.48–0.91). Conclusion: Black patients with CABP in the All of Us database were less likely to receive guideline-concordant antibiotics, and Hispanic patients were more likely to receive guideline-concordant antibiotics, than NHW patients

State of the art 2015: a literature review of social media intelligence capabilities for counter-terrorism

Overview This paper is a review of how information and insight can be drawn from open social media sources. It focuses on the specific research techniques that have emerged, the capabilities they provide, the possible insights they offer, and the ethical and legal questions they raise. These techniques are considered relevant and valuable in so far as they can help to maintain public safety by preventing terrorism, preparing for it, protecting the public from it and pursuing its perpetrators. The report also considers how far this can be achieved against the backdrop of radically changing technology and public attitudes towards surveillance. This is an updated version of a 2013 report paper on the same subject, State of the Art. Since 2013, there have been significant changes in social media, how it is used by terrorist groups, and the methods being developed to make sense of it.  The paper is structured as follows: Part 1 is an overview of social media use, focused on how it is used by groups of interest to those involved in counter-terrorism. This includes new sections on trends of social media platforms; and a new section on Islamic State (IS). Part 2 provides an introduction to the key approaches of social media intelligence (henceforth ‘SOCMINT’) for counter-terrorism. Part 3 sets out a series of SOCMINT techniques. For each technique a series of capabilities and insights are considered, the validity and reliability of the method is considered, and how they might be applied to counter-terrorism work explored. Part 4 outlines a number of important legal, ethical and practical considerations when undertaking SOCMINT work

Applying Event Sourcing to Occasionally Connected Systems

As an information storing technique, event sourcing provides some useful properties over more traditional techniques. There is value for both application developers and end-users to be able to inspect the whole history of the application states. Event sourcing is usually used in environments with a constant network connection and a centralized database. This thesis aimed to provide necessary means to allow use of event sourcing in occasionally connected systems. This thesis started off the research by assuming an occasionally connected, event sourced system with a distributed multi-leader database. Problems emerging from this approach were first identified, and then solved on a conceptual level by using methods from existing literature and research. At last, a fictional case study was conducted to produce a system showcasing that the concepts introduced can be applied in practice. There were a total of three primary problems that were identified. By making event sourcing data model bi-temporal, retroactive sharing of events proved to be achievable without violating the immutability and append-only principle of event sourcing. Conflict and concurrency detection and handling emerging from moving from single leader to multi-leader replication revealed to be a well-known problem in distributed system research around data replication. Last problem was how the system can give guarantees that information it provides to external systems will not change. This proved to be solvable by applying stability properties of distributed systems to the event sourced data model, which allowed to identify a point in the event log dividing the log into stable and unstable parts. These results together provide a foundation for building occasionally connected event sourced systems

Closing the gap between science and management of cold-water refuges in rivers and streams

Human activities and climate change threaten coldwater organisms in freshwater eco-systems by causing rivers and streams to warm, increasing the intensity and frequency of warm temperature events, and reducing thermal heterogeneity. Cold-water refuges are discrete patches of relatively cool water that are used by coldwater organisms for thermal relief and short-term survival. Globally, cohesive management approaches are needed that consider interlinked physical, biological, and social factors of cold-water refuges. We review current understanding of cold-water refuges, identify gaps between science and management, and evaluate policies aimed at protecting thermally sensitive species. Existing policies include designating cold-water habitats, restricting fishing during warm periods, and implementing threshold temperature standards or guidelines. However, these policies are rare and uncoordinated across spatial scales and often do not consider input from Indigenous peoples. We propose that cold-water refuges be managed as dis-tinct operational landscape units, which provide a social and ecological context that is relevant at the watershed scale. These operational landscape units provide the founda-tion for an integrated framework that links science and management by (1) mapping and characterizing cold-water refuges to prioritize management and conservation actions, (2) leveraging existing and new policies, (3) improving coordination across jurisdictions, and (4) implementing adaptive management practices across scales. Our findings show that while there are many opportunities for scientific advancement, the current state of the sciences is sufficient to inform policy and management. Our proposed framework pro-vides a path forward for managing and protecting cold-water refuges using existing and new policies to protect coldwater organisms in the face of global change. behavioral thermoregulation, climate change adaptation, lotic ecosystem management, refugia, salmonids, temperature, thermal heterogeneity, thermal refugespublishedVersio

Record Linkage Techniques: Exploring and developing data matching methods to create national record linkage infrastructure to support population level research

In a world where the growth in digital information and systems continues to expand, researchers have access to unprecedented amounts of data. These large and complex data reservoirs require creative, innovative and scalable tools to unlock the potential of this ‘big data’. Record linkage is a powerful tool in the ‘big data’ arsenal. This thesis demonstrates the value of national record linkage infrastructure and how this has been achieved for the Australian research community

Curriculum implementation exploratory studies: Final report

Throughout the history of schooling in New Zealand the national curriculum has been revised at fairly regular intervals. Consequently, schools are periodically faced with having to accommodate to new curriculum. In between major changes other specifically-focused changes may arise; for example, the increased recent emphasis upon numeracy and literacy