EDRA:A Hardware-assisted Decoupled Access/Execute Framework on the Digital Market

EDRA was an Horizon 2020 FET Launchpad project that focused on the commercialization of the Decoupled Access Execution Reconfigurable (DAER) framework - developed within the FET-HPC EXTRA project - on Amazon's Elastic Cloud (EC2) Compute FPGA-based infrastructure. The delivered framework encapsulates DAER into a EC2 virtual machine (VM), and uses a simple, directive-based, high-level application programming interface (API) to facilitate application mapping to the underlying hardware architecture. EDRA's Minimum Viable Product (MVP) is an accelerator for the Phylogenetic Likelihood Function (PLF), one of the cornerstone functions in most phylogenetic inference tools, achieving up to 8x performance improvement compared to optimized software implementations. Towards entering the market, research revealed that Europe is an extremely promising geographic region for focusing the project efforts on dissemination, MVP promotion and advertisement

dReDBox: A Disaggregated Architectural Perspective for Data Centers

Data centers are currently constructed with fixed blocks (blades); the hard boundaries of this approach lead to suboptimal utilization of resources and increased energy requirements. The dReDBox (disaggregated Recursive Datacenter in a Box) project addresses the problem of fixed resource proportionality in next-generation, low-power data centers by proposing a paradigm shift toward finer resource allocation granularity, where the unit is the function block rather than the mainboard tray. This introduces various challenges at the system design level, requiring elastic hardware architectures, efficient software support and management, and programmable interconnect. Memory and hardware accelerators can be dynamically assigned to processing units to boost application performance, while high-speed, low-latency electrical and optical interconnect is a prerequisite for realizing the concept of data center disaggregation. This chapter presents the dReDBox hardware architecture and discusses design aspects of the software infrastructure for resource allocation and management. Furthermore, initial simulation and evaluation results for accessing remote, disaggregated memory are presented, employing benchmarks from the Splash-3 and the CloudSuite benchmark suites.This work was supported in part by EU H2020 ICT project dRedBox, contract #687632.Peer ReviewedPostprint (author's final draft

Deep learning for diabetic retinopathy detection and classification based on fundus images: A review.

Diabetic Retinopathy is a retina disease caused by diabetes mellitus and it is the leading cause of blindness globally. Early detection and treatment are necessary in order to delay or avoid vision deterioration and vision loss. To that end, many artificial-intelligence-powered methods have been proposed by the research community for the detection and classification of diabetic retinopathy on fundus retina images. This review article provides a thorough analysis of the use of deep learning methods at the various steps of the diabetic retinopathy detection pipeline based on fundus images. We discuss several aspects of that pipeline, ranging from the datasets that are widely used by the research community, the preprocessing techniques employed and how these accelerate and improve the models' performance, to the development of such deep learning models for the diagnosis and grading of the disease as well as the localization of the disease's lesions. We also discuss certain models that have been applied in real clinical settings. Finally, we conclude with some important insights and provide future research directions

DeSyRe: on-Demand System Reliability

The DeSyRe project builds on-demand adaptive and reliable Systems-on-Chips (SoCs). As fabrication technology scales down, chips are becoming less reliable, thereby incurring increased power and performance costs for fault tolerance. To make matters worse, power density is becoming a significant limiting factor in SoC design, in general. In the face of such changes in the technological landscape, current solutions for fault tolerance are expected to introduce excessive overheads in future systems. Moreover, attempting to design and manufacture a totally defect and fault-free system, would impact heavily, even prohibitively, the design, manufacturing, and testing costs, as well as the system performance and power consumption. In this context, DeSyRe delivers a new generation of systems that are reliable by design at well-balanced power, performance, and design costs. In our attempt to reduce the overheads of fault-tolerance, only a small fraction of the chip is built to be fault-free. This fault-free part is then employed to manage the remaining fault-prone resources of the SoC. The DeSyRe framework is applied to two medical systems with high safety requirements (measured using the IEC 61508 functional safety standard) and tight power and performance constraints

In Vivo Aortic Valve Thermal Heterogeneity in Patients With Nonrheumatic Aortic Valve Stenosis The First In Vivo Experience in Humans

ObjectivesWe investigated in vivo in aortic valve stenosis (AVS) whether there is: 1) thermal heterogeneity within the valve leaflets; 2) temperature difference between the leaflets and the ascending aortic wall; and 3) a possible correlation between heat production, inflammation, and neoangiogenesis.BackgroundHistological studies have demonstrated a potential role of inflammation and neoangiogenesis in AVS.MethodsWe examined 96 leaflets scheduled for aortic valve replacement. Twenty-five patients had AVS, and 7 had aortic valve insufficiency (AVI). Temperature measurements were performed right before hypothermic cardioplegia. Temperature difference (ΔT) was assigned as the mean temperature of each leaflet minus the temperature of the aortic wall. Histological, immunohistological analysis, and vascular endothelial growth factor (VEGF) immunoreactivity was performed.ResultsSignificant thermal heterogeneity was recorded within the leaflets of AVS, compared with AVI (1.52 ± 1.35°C vs. 0.13 ± 0.11°C, p < 0.01). In AVS ΔT was greater in all leaflets compared with the AVI group (p < 0.01). Leaflets of AVS had increased inflammatory cell infiltration, calcium deposit, and anti-VEGF expression compared with AVI (p < 0.01).ConclusionsThermal heterogeneity is increased in AVS and correlates with inflammatory mononuclear cell infiltration, expression of pro-inflammatory cytokines and neoangiogenic factors

The AXIOM software layers

AXIOM project aims at developing a heterogeneous computing board (SMP-FPGA).The Software Layers developed at the AXIOM project are explained.OmpSs provides an easy way to execute heterogeneous codes in multiple cores. People and objects will soon share the same digital network for information exchange in a world named as the age of the cyber-physical systems. The general expectation is that people and systems will interact in real-time. This poses pressure onto systems design to support increasing demands on computational power, while keeping a low power envelop. Additionally, modular scaling and easy programmability are also important to ensure these systems to become widespread. The whole set of expectations impose scientific and technological challenges that need to be properly addressed.The AXIOM project (Agile, eXtensible, fast I/O Module) will research new hardware/software architectures for cyber-physical systems to meet such expectations. The technical approach aims at solving fundamental problems to enable easy programmability of heterogeneous multi-core multi-board systems. AXIOM proposes the use of the task-based OmpSs programming model, leveraging low-level communication interfaces provided by the hardware. Modular scalability will be possible thanks to a fast interconnect embedded into each module. To this aim, an innovative ARM and FPGA-based board will be designed, with enhanced capabilities for interfacing with the physical world. Its effectiveness will be demonstrated with key scenarios such as Smart Video-Surveillance and Smart Living/Home (domotics).Peer ReviewedPostprint (author's final draft

The AXIOM platform for next-generation cyber physical systems

Cyber-Physical Systems (CPSs) are widely used in many applications that require interactions between humans and their physical environment. These systems usually integrate a set of hardware-software components for optimal application execution in terms of performance and energy consumption. The AXIOM project (Agile, eXtensible, fast I/O Module), presented in this paper, proposes a hardware-software platform for CPS coupled with an easy parallel programming model and sufficient connectivity so that the performance can scale-up by adding multiple boards. AXIOM supports a task-based programming model based on OmpSs and leverages a high-speed, inexpensive communication interface called AXIOM-Link. The board also tightly couples the CPU with reconfigurable resources to accelerate portions of the applications. As case studies, AXIOM uses smart video surveillance, and smart home living applicationsThis work is partially supported by the European Union H2020 program through the AXIOM project (grant ICT-01-2014 GA 645496) and HiPEAC (GA 687698), by the Spanish Government through Programa Severo Ochoa (SEV-2015-0493), by the Spanish Ministry of Science and Technology through TIN2015-65316-P project, and by the Generalitat de Catalunya (contracts 2014-SGR-1051 and 2014-SGR-1272). We also thank the Xilinx University Program for its hardware and software donations.Peer ReviewedPostprint (author's final draft

Corrigendum to "Recognition motifs for importin 4 [(L)PPRS(G/P)P] and importin 5 [KP(K/Y)LV] binding, identified by bio-informatic simulation and experimental in vitro validation" [Comput Struct Biotechnol J 20 (2022) 5952-5961]

Nuclear translocation of large proteins is mediated through karyopherins, carrier proteins recognizing specific motifs of cargo proteins, known as nuclear localization signals (NLS). However, only few NLS signals have been reported until now. In the present work, NLS signals for Importins 4 and 5 were identified through an unsupervised in silico approach, followed by experimental in vitro validation. The sequences LPPRS(G/P)P and KP(K/Y)LV were identified and are proposed as recognition motifs for Importins 4 and 5 binding, respectively. They are involved in the trafficking of important proteins into the nucleus. These sequences were validated in the breast cancer cell line T47D, which expresses both Importins 4 and 5. Elucidating the complex relationships of the nuclear transporters and their cargo proteins is very important in better understanding the mechanism of nuclear transport of proteins and laying the foundation for the development of novel therapeutics, targeting specific importins