At the end of CMOS-scaling, the role of architecture design is increasingly gaining importance. Supporting this trend, customizable embedded FPGAs are an ingredient in ASIC architectures to provide the advantages of reconfigurable hardware exactly where and how it is most beneficial. To enable this, we are introducing the FABulous embedded open-source FPGA framework. FABulous is designed to fulfill the objectives of ease of use, maximum portability to different process nodes, good control for customization, and delivering good area, power, and performance characteristics of the generated FPGA fabrics. The framework provides templates for logic, arithmetic, memory, and I/O blocks that can be easily stitched together, whilst enabling users to add their own fully customized blocks and primitives. The FABulous ecosystem generates the embedded FPGA fabric for chip fabrication, integrates Yosys, ABC, VPR and nextpnr as FPGA CAD tools, deals with the bitstream generation and after fabrication tests. Additionally, we provide an emulation path for system development. FABulous was demonstrated for an ASIC integrating a RISC-V core with an embedded FPGA fabric for custom instruction set extensions using a TSMC 180nm process and an open-source 45nm process node.

This demonstration shows the steps a designer has to take to specify and implement a chip with an embedded FPGA (eFPGA) using the FABulous open-source toolchain. We also show how the architecture graph is automatically generated for the open-source FPGA CAD tools (Yosys, ABC, nextpnr) to compile Verilog all the way to a bitstream. Ultimately, we demonstrate such bitstreams running on our FlexBex chip, which integrates an Ibex RISC-V core from lowRISC together with a FABulous eFPGA. The system supports multiple partially reconfigurable regions for hosting reconfigurable instruction set extensions, and the fabric provides logic, DSP, and memory slices.

Summary Ongoing transistor scaling and the growing complexity of embedded system designs has led to the rise of MPSoCs (Multi‐Processor System‐on‐Chip), combining multiple hard‐core CPUs and accelerators (FPGA, GPU) on the same physical die. These devices are of great interest to the supercomputing community, who are increasingly reliant on heterogeneity to achieve power and performance goals in these closing stages of the race to exascale. In this paper, we present a network interface architecture and networking infrastructure, designed to sit inside the FPGA fabric of a cutting‐edge MPSoC device, enabling networks of these devices to communicate within both a distributed and shared memory context, with reduced need for costly software networking system calls. We will present our implementation and prototype system and discuss the main design decisions relevant to the use of the Xilinx Zynq Ultrascale+, a state‐of‐the‐art MPSoC, and the challenges to be overcome given the device's limitations and constraints. We demonstrate the working prototype system connecting two MPSoCs, with communication between processor and remote memory region and accelerator. We then discuss the limitations of the current implementation and highlight areas of improvement to make this solution production‐ready.

Summary The convergence between computing‐ and data‐centric workloads and platforms is imposing new challenges on how to best use the resources of modern computing systems. In this paper, we investigate alternatives for the storage subsystem of a novel exascale‐capable system with special emphasis on how allocation strategies would affect the overall performance. We consider several aspects of data‐aware allocation such as the effect of spatial and temporal locality, the affinity of data to storage sources, and the network‐level traffic prioritization for different types of flows. In our experimental set‐up, temporal locality can have a substantial effect on application runtime (up to a 10% reduction), whereas spatial locality can be even more significant (up to one order of magnitude faster with perfect locality). The use of structured access patterns to the data and the allocation of bandwidth at the network level can also have a significant impact (up to 20% and 17% reduction of runtime, respectively). These results suggest that scheduling policies exposing data‐locality information can be essential for the appropriate utilization of future large‐scale systems. Finally, we found that the distributed storage system we are implementing can outperform traditional SAN architectures, even with a much smaller (in terms of I/O servers) back‐end.

Exascale performance will be delivered by systems composed of millions of interconnected computing cores. The way these computing elements are connected with each other (network topology) has a strong impact on many performance characteristics. In this work we propose a multi-objective optimization-based framework to explore possible network topologies to be implemented in the EU-funded ExaNeSt project. The modular design of this system's interconnect provides great flexibility to design topologies optimized for specific performance targets such as communications locality, fault tolerance or energy-consumption. The generation procedure of the topologies is formulated as a three-objective optimization problem (minimizing some topological characteristics) where solutions are searched using evolutionary techniques. The analysis of the results, carried out using simulation, shows that the topologies meet the required performance objectives. In addition, a comparison with a well-known topology reveals that the generated solutions can provide better topological characteristics and also higher performance for parallel applications.

Despite their proliferation as a dominant computing paradigm, cloud computing systems lack effective mechanisms to manage their vast amounts of resources efficiently. Resources are stranded and fragmented, ultimately limiting cloud systems' applicability to large classes of critical applications that pose non-moderate resource demands. Eliminating current technological barriers of actual fluidity and scalability of cloud resources is essential to strengthen cloud computing's role as a critical cornerstone for the digital economy. ACTiCLOUD proposes a novel cloud architecture that breaks the existing scale-up and share-nothing barriers and enables the holistic management of physical resources both at the local cloud site and at distributed levels. Specifically, it makes advancements in the cloud resource management stacks by extending state-of-the-art hypervisor technology beyond the physical server boundary and localized cloud management system to provide a holistic resource management within a rack, within a site, and across distributed cloud sites. On top of this, ACTiCLOUD will adapt and optimize system libraries and runtimes (e.g., JVM) as well as ACTiCLOUD-native applications, which are extremely demanding, and critical classes of applications that currently face severe difficulties in matching their resource requirements to state-of-the-art cloud offerings.

The Internet of Things (IoT) will result in the deployment of many billions of wireless embedded systems creating interactive pervasive environments. It is envisaged that devices will cooperate to provide greater system knowledge than the sum of its parts. In an emergency situation, the flow of data across the IoT may be disrupted, giving rise to a requirement for machine-to-machine interaction within the remaining ubiquitous environment. Geographic hash tables (GHTs) provide an efficient mechanism to support fault-tolerant rendezvous communication between devices. However, current approaches either rely on devices being equipped with a GPS or being manually assigned an identity. This is unrealistic when the majority of these systems will be located inside buildings and will be too numerous to expect manual configuration. Additionally, when using GHT as a distributed data store, imbalance in the topology can lead to storage and routing overhead. This causes unfair work load, exhausting limited power supplies as well as causing poor data redundancy. To deal with these issues, we propose an approach that balances graph-based layout identity assignment, through the application of multifitness genetic algorithms. Our experiments show through simulation that our multifitness evolution technique improves on the initial graph-based layout, providing devices with improved balance and reachability metrics.

It is generally agreed, that an active lifestyle promotes healthy living across different age groups. It helps to combat obesity, reduce the risk of diabetes and heart disease, and support independent living as we age. However, it is difficult to quantify a direct correlation between physical activity and health outcomes. Given that obesity and lifestyle-related illnesses occur over years in contrast to days, weeks or months seeing the effects activity and sedentary behaviour has on individuals in the short term is not always possible. The ubiquitous nature of physical activity makes it extremely difficult to capture as people go about their lives. Consequently, there has been a great deal of debate on the frequency intensity time, and the type of physical activity required by different groups (pre-schoolers, children, adults, older adults, obese, infirm, disabled, and depressed). There is a need to provide effective mechanisms to monitor and manipulate physical activity and sedentary behaviour. Whilst several commercially available products exist to achieve this, compliance is poor. The challenge is to use new and novel technologies that are unobtrusive and natural adjunct to a persons day-to-day activity. This paper builds on existing ideas and explores how activity and sedentary behaviour information can be collected from different environments. We have developed an initial working prototype to evaluate the applicability of our approach.

Critical infrastructures play important roles in ensuring the wellbeing of the populace. Protecting critical infrastructures and ensuring their continued operation will be an important part of future Smart City ecosystems. Minimising the destruction of failing critical infrastructure components or system components that are geographically close critical services is essential. Equally important are the system of systems relationships that a failing system has, as these could render a minor system critical under certain circumstances. Infrastructure failure is usually brought under control through system adaptation e.g. using sensor area networks to close valves or by emergency response e.g. extinguishing fires. Current response procedures rely on antiquated information sharing techniques and provide little or no opportunity to effect change within the failing infrastructures systems. There may also be minimal understanding of the important systems of systems role that is being provided by components of the failing system. This paper details our initial work on the Smart Cities Critical Infrastructure response framework. The goal of our framework is to provide a response strategy to first responders based on smart cities information flows. Where these information flows have been compromised we propose a robust infrastructure state preservation system as to provide an interface to a failing critical infrastructure.