Machine Learning inference using PYNQ environment in a AWS EC2 F1 Instance

In the past few years, using Machine and Deep Learning techniques has become more and more viable, thanks to the availability of tools which make the need of specific knowledge in the realm of data science and complex networks less vital to achieve a satisfactory final result in a variety of research fields. This process has caused an explosion in the adoption of such techniques, e.g. in the context of High Energy Physics. The range of applications for ML becomes even larger if we consider the implementation of these algorithms on low-latency hardware like FPGAs which promise smaller latency with respect to traditional inference algorithms running on general purpose CPUs. This paper presents and discusses the activity running at the University of Bologna and INFN-Bologna where a new open-source project from Xilinx called PYNQ is being tested. Its purpose is to grant designers the possibility to exploit the benefits of programmable logic and microprocessors using the Python language and libraries. This new software environment can be deployed on a variety of Xilinx platforms, from the simplest ones like ZYNQ boards, to more advanced and high performance ones, like Alveo accelerator cards and AWS EC2 F1 instances. The use of cloud computing in this work lets us test the capabilities of this new workflow, from the creation and training of a Neural Network and the creation of a HLS project using HLS4ML, to testing the predictions of the NN using PYNQ APIs and functions written in Pytho

INDIGO-Datacloud: foundations and architectural description of a Platform as a Service oriented to scientific computing

Software Engineering.-- et al.In this paper we describe the architecture of a Platform as a Service (PaaS) oriented to computing and data analysis. In order to clarify the choices we made, we explain the features using practical examples, applied to several known usage patterns in the area of HEP computing. The proposed architecture is devised to provide researchers with a unified view of distributed computing infrastructures, focusing in facilitating seamless access. In this respect the Platform is able to profit from the most recent developments for computing and processing large amounts of data, and to exploit current storage and preservation technologies, with the appropriate mechanisms to ensure security and privacy.INDIGO-DataCloud is co-founded by the Horizon 2020Framework Programme.Peer reviewe

a web based portal to access and manage wnodes virtualized cloud resources

The Worker Nodes on Demand Service (WNoDeS), developed by INFN, is a framework designed to offer local, grid or cloud-based access to computing and storage resources, preserving maximum compatibility with existing computing center policies and workflows. WNoDeS has been running in production at the INFN Tier-1 located at CNAF since November 2009, where it currently manages several thousands of dynamically created Virtual Machines; WNoDeS is also being deployed at several other Italian sites. This presentation shows the current state of the WNoDeS Web portal, aimed at end users for the instantiation of WNoDeS cloud resources and at site administrators for graphical management of the WNoDeS infrastructure. The portal is scheduled to be released in the next major version of WNoDeS (WNoDeS 2), expected by Fall 2011

performance improvements in a large scale virtualization system

This work shows the optimizations we have been investigating and implementing at the KVM virtualization layer in our research institute based on more than a year of experience in running thousands of VMs in a production environment used by several international collaborations. These optimizations increase the adaptability of virtualization solutions to demanding applications like those run in our institute (High-Energy Physics). In particular we will show what is the best solution to share storage space from an hypervisor to the virtual machines running on top of it, trying to avoid problems that modern storage cluster have. We will also show how different the performance can be comparing real and virtual machines, measuring access to computing, storage and network resources, trying to provide hints on server configuration where possible. This work has been driven by the project called Worker Nodes on Demand Service (WNoDeS), developed by INFN, a framework designed to offer local, grid or cloud-based access to computing and storage resources, preserving maximum compatibility with existing computing center policies and work-flows

Improved Cloud resource allocation: how INDIGO-Datacloud is overcoming the current limitations in Cloud schedulers

Trabajo presentado a: 22nd International Conference on Computing in High Energy and Nuclear Physics (CHEP2016) 10–14 October 2016, San Francisco.Performing efficient resource provisioning is a fundamental aspect for any resource provider. Local Resource Management Systems (LRMS) have been used in data centers for decades in order to obtain the best usage of the resources, providing their fair usage and partitioning for the users. In contrast, current cloud schedulers are normally based on the immediate allocation of resources on a first-come, first-served basis, meaning that a request will fail if there are no resources (e.g. OpenStack) or it will be trivially queued ordered by entry time (e.g. OpenNebula). Moreover, these scheduling strategies are based on a static partitioning of the resources, meaning that existing quotas cannot be exceeded, even if there are idle resources allocated to other projects. This is a consequence of the fact that cloud instances are not associated with a maximum execution time and leads to a situation where the resources are under-utilized. These facts have been identified by the INDIGO-DataCloud project as being too simplistic for accommodating scientific workloads in an efficient way, leading to an underutilization of the resources, a non desirable situation in scientific data centers. In this work, we will present the work done in the scheduling area during the first year of the INDIGO project and the foreseen evolutions.The authors want to acknowledge the support of the INDIGO-DataCloud (grant number 653549) project, funded by the European Commission’s Horizon 2020 Framework Programme.Peer Reviewe

Survey of the main causal agents of fusarium head blight of durum wheat around Bologna, northern Italy

Several Fusarium species and Microdochium nivale are involved in fusarium head blight (FHB), which in Italy has been constantly present on wheat since 1995. This study was carried out from 1995 to 2007 on FHB-infected durum wheat heads collected in the Bologna countryside, Emilia-Romagna, northern Italy. The most frequent Fusarium species found were: Fusarium graminearum (32.1%), F. culmorum (25.2%) and F. poae (17.8%), while F. avenaceum and M. nivale occurred discontinuously. Other Fusarium species were also found, but only sporadically. It is important to identify and characterize the main species involved in the FHB syndrome for this will help us to establish control strategies that will contain the disease and the content of mycotoxins in food and animal feed

Development of broad‐spectrum human monoclonal antibodies for rabies post‐exposure prophylaxis

Currently available rabies post‐exposure prophylaxis (PEP) for use in humans includes equine or human rabies immunoglobulins (RIG). The replacement of RIG with an equally or more potent and safer product is strongly encouraged due to the high costs and limited availability of existing RIG. In this study, we identified two broadly neutralizing human monoclonal antibodies that represent a valid and affordable alternative to RIG in rabies PEP. Memory B cells from four selected vaccinated donors were immortalized and monoclonal antibodies were tested for neutralizing activity and epitope specificity. Two antibodies, identified as RVC20 and RVC58 (binding to antigenic site I and III, respectively), were selected for their potency and broad‐spectrum reactivity. In vitro, RVC20 and RVC58 were able to neutralize all 35 rabies virus (RABV) and 25 non‐RABV lyssaviruses. They showed higher potency and breath compared to antibodies under clinical development (namely CR57, CR4098, and RAB1) and commercially available human RIG. In vivo, the RVC20–RVC58 cocktail protected Syrian hamsters from a lethal RABV challenge and did not affect the endogenous hamster post‐vaccination antibody response

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

INDIGO-DataCloud: A data and computing platform to facilitate seamless access to e-infrastructures

This paper describes the achievements of the H2020 project INDIGO-DataCloud. The project has provided e-infrastructures with tools, applications and cloud framework enhancements to manage the demanding requirements of scientific communities, either locally or through enhanced interfaces. The middleware developed allows to federate hybrid resources, to easily write, port and run scientific applications to the cloud. In particular, we have extended existing PaaS (Platform as a Service) solutions, allowing public and private e-infrastructures, including those provided by EGI, EUDAT, and Helix Nebula, to integrate their existing services and make them available through AAI services compliant with GEANT interfederation policies, thus guaranteeing transparency and trust in the provisioning of such services. Our middleware facilitates the execution of applications using containers on Cloud and Grid based infrastructures, as well as on HPC clusters. Our developments are freely downloadable as open source components, and are already being integrated into many scientific applications

Relatório de estágio em farmácia comunitária

Relatório de estágio realizado no âmbito do Mestrado Integrado em Ciências Farmacêuticas, apresentado à Faculdade de Farmácia da Universidade de Coimbr