BlastFunction: A Full-stack Framework Bringing FPGA Hardware Acceleration to Cloud-native Applications

“Cloud-native” is the umbrella adjective describing the standard approach for developing applications that exploit cloud infrastructures’ scalability and elasticity at their best. As the application complexity and user-bases grow, designing for performance becomes a first-class engineering concern. As an answer to these needs, heterogeneous computing platforms gained widespread attention as powerful tools to continue meeting SLAs for compute-intensive cloud-native workloads. We propose BlastFunction, an FPGA-as-a-Service full-stack framework to ease FPGAs’ adoption for cloud-native workloads, integrating with the vast spectrum of fundamental cloud models. At the IaaS level, BlastFunction time-shares FPGA-based accelerators to provide multi-tenant access to accelerated resources without any code rewriting. At the PaaS level, BlastFunction accelerates functionalities leveraging the serverless model and scales functions proactively, depending on the workload’s performance. Further lowering the FPGAs’ adoption barrier, an accelerators’ registry hosts accelerated functions ready to be used within cloud-native applications, bringing the simplicity of a SaaS-like approach to the developers. After an extensive experimental campaign against state-of-the-art cloud scenarios, we show how BlastFunction leads to higher performance metrics (utilization and throughput) against native execution, with minimal latency and overhead differences. Moreover, the scaling scheme we propose outperforms the main serverless autoscaling algorithms in workload performance and scaling operation amount.

Years of life lost estimates cannot always be taken at face value: Response to “COVID-19 – exploring the implications of long-term condition type and extent of multimorbidity on years of life lost: a modelling study”

In their recent analysis, Hanlon et al. estimated the years of life lost (YLL) in people who have died with COVID-19 by following and expanding on the WHO standard approach. We welcome this research as an attempt to draw a more accurate picture of the mortality burden of this disease which has been involved in the deaths of more than 300,000 people worldwide as of May 2020. However, we argue that obtained YLL estimates (13 years for men and 11 years for women) are interpreted in a misleading way. Even with the presented efforts to control for the role of multimorbidity in COVID-19 deaths, these estimates cannot be interpreted to imply “how long someone who died from COVID-19 might otherwise have been expected to live”. By example we analyze the underlying problem which renders such an interpretation of YLL estimates impossible, and outline potential approaches to control for the problem.

Adapting and validating the log quadratic model to derive under-five age- and cause-specific mortality (U5ACSM): a preliminary analysis

Background The mortality pattern from birth to age five is known to vary by underlying cause of mortality, which has been documented in multiple instances. Many countries without high functioning vital registration systems could benefit from estimates of age- and cause-specific mortality to inform health programming, however, to date the causes of under-five death have only been described for broad age categories such as for neonates (0–27 days), infants (0–11 months), and children age 12–59 months. Methods We adapt the log quadratic model to mortality patterns for children under five to all-cause child mortality and then to age- and cause-specific mortality (U5ACSM). We apply these methods to empirical sample registration system mortality data in China from 1996 to 2015. Based on these empirical data, we simulate probabilities of mortality in the case when the true relationships between age and mortality by cause are known. Results We estimate U5ACSM within 0.1–0.7 deaths per 1000 livebirths in hold out strata for life tables constructed from the China sample registration system, representing considerable improvement compared to an error of 1.2 per 1000 livebirths using a standard approach. This improved prediction error for U5ACSM is consistently demonstrated for all-cause as well as pneumonia- and injury-specific mortality. We also consistently identified cause-specific mortality patterns in simulated mortality scenarios. Conclusion The log quadratic model is a significant improvement over the standard approach for deriving U5ACSM based on both simulation and empirical results.

A threshold-free approach with age-dependency for estimating malaria seroprevalence

Background In malaria serology analysis, the standard approach to obtain seroprevalence, i.e the proportion of seropositive individuals in a population, is based on a threshold which is used to classify individuals as seropositive or seronegative. The choice of this threshold is often arbitrary and is based on methods that ignore the age-dependency of the antibody distribution. Methods Using cross-sectional antibody data from the Western Kenyan Highlands, this paper introduces a novel approach that has three main advantages over the current threshold-based approach: it avoids the use of thresholds; it accounts for the age dependency of malaria antibodies; and it allows us to propagate the uncertainty from the classification of individuals into seropositive and seronegative when estimating seroprevalence. The reversible catalytic model is used as an example for illustrating how to propagate this uncertainty into the parameter estimates of the model. Results This paper finds that accounting for age-dependency leads to a better fit to the data than the standard approach which uses a single threshold across all ages. Additionally, the paper also finds that the proposed threshold-free approach is more robust against the selection of different age-groups when estimating seroprevalence. Conclusion The novel threshold-free approach presented in this paper provides a statistically principled and more objective approach to estimating malaria seroprevalence. The introduced statistical framework also provides a means to compare results across studies which may use different age ranges for the estimation of seroprevalence.

On Modelling the Structural Quasiness of Complex Systems

Complex systems are usually represented by invariant models which at most admit only parametric variations. This approach assumes invariant idealized simplifications to model these systems. This standard approach is considered omitting crucial features of phenomenological interaction mechanisms related to processes of emergence of such systems. The quasiness of the structural dynamics that generate emergence of complex systems is considered as the main feature. Generation achieved through prevalently coherent sequences and combinations of interactions. Quasiness (dynamics of loss and recovery, equivalences, inhomogeneity, multiplicity, non-regularity, and partiality) represents the incompleteness of the interaction mechanisms, incompleteness necessary even if not sufficient for the establishment of processes of emergence. The emergence is extinguished by completeness. Complex systems possess local coherences corresponding to the phenomenological complexity. While quasi-systems are not necessarily complex systems, complex systems are considered quasi-systems, being not always systems, not always the same system, and not only systems. It is addressed the problem of representing the quasiness of coherence (quasicoherence), such as the ability to recover and tolerate temporary levels of incoherence. The main results of the study focus on research approaches to model quasicoherence through the changing of rules in models of emergence. It is presented a version of standard analytical approaches compatible with quasiness of systemic emergence and related mathematical issues. The same approach is considered for networks, artificial neural networks, and it is introduced the concept of quasification for fixed models. Finally, it is considered that suitable representations of structural dynamics and its quasiness are needed to model, simulate, and adopt effective interventions on emergence of complex systems.

Opinion on the Optimal Histologic Evaluation of the Bone Marrow in Nonclinical Toxicity Studies

Identification of bone marrow toxicity is an important issue in drug development and toxicologic pathologists play a critical role in that identification. Knowledge of the general components of bone marrow, relevant anatomical and species differences, and the standard approach (routine systematic histological evaluation of the bone marrow in conjunction with analysis of the peripheral complete blood count data) will be reviewed. Specific morphologic features that anatomic pathologists should look for in the various components of bone marrow as well as suggested terminology for bone marrow findings will be discussed. Finally, an opinion on the limitations of the standard approach to bone marrow evaluation will be provided including general recommendations on when additional methods (image analysis of hematoxylin and eosin stained slides, flow cytometry or Sysmex XT 2000iV analysis, cytological evaluation of bone marrow smears, in vitro models, and transmission electron microscopy) might be useful in the detection or further characterization of bone marrow toxicity. [Box: see text]

An alternative scheme for effective range corrections in pionless EFT

We discuss an alternative scheme for including effective range corrections in pionless effective field theory. The standard approach treats range terms as perturbative insertions in the T-matrix. In a finite volume this scheme can lead to singular behavior close to the unperturbed energies. We consider an alternative scheme that resums the effective range but expands the spurious pole of the T-matrix created by this resummation. We test this alternative expansion for several model potentials and observe good convergence.

Growing Together: An Analysis of Measurement Transparency Across 15 Years of Player Motivation Questionnaires

[Preprint Version] There are many questionnaires available to assess player motivation, originating from a diverse range of disciplines. Each discipline differs in their usage and reporting of questionnaires, but there has been no attempt to synthesise their application or create a standard way of using them. No standard approach leads to a lack of transparency in reporting their usage, which affects the ability of the field to build on one another. This has made it unclear whether player motivation research is a unified research community, or a collection of individuals with a similar goal. This work assesses the transparency of questionnaire reporting practices in papers published in the last 15 years of player motivation research (n=238). Overall, there is a lack of transparency in reporting questionnaires, driven by a lack of priority in presenting items alongside text. Many papers use questionnaires that are based on theory or have been used to measure specific factors in the past, but explicit justification is rare. This work concludes with a checklist for authors to use to ensure questionnaire reporting is transparent, so that the field can standardise and allow for more cohesive research synthesis.