Hierarchical energy monitoring for task mapping in many-core systems

This work addresses a research subject with a rich literature: task mapping in NoC-based systems. Task mapping is the process of selecting a processing element to execute a given task. The number of cores in many-core systems increases the complexity of the task mapping. The main concerns in task mapping in large systems include (i) scalability; (ii) dynamic workload; and (iii) reliability. It is necessary to distribute the mapping decision across the system to ensure scalability. The workload of emerging many-core systems may be dynamic, i.e., new applications may start at any moment, leading to different mapping scenarios. Therefore, it is necessary to execute the mapping process at runtime to support a dynamic workload assignment. The workload assignment plays an important role in the many-core system reliability. Load imbalance may generate hotspots zones and consequently thermal implications, which may generate hotspots zones and consequently thermal implications. More recently, task mapping techniques aiming at improving system reliability have been proposed in the literature. However, such approaches rely on centralized mapping decisions, which are not scalable. To address these challenges, the main goal of this work is to propose a hierarchical runtime mapping heuristic, which provides scalability and a fair workload distribution. Distributing the workload inside the system increases the system reliability in long-term, due to the reduction of hotspot regions. The proposed mapping heuristic considers the application workload as a function of the consumed energy in the processors and NoC routers. The proposal adopts a hierarchical energy monitoring scheme, able to estimate at runtime the consumption at each processing element. The mapping uses the energy estimated by the monitoring scheme to guide the mapping decision. Results compare the proposal against a mapping heuristic whose main cost function minimizes the communication energy. Results obtained in large systems, up to 256 cores, show improvements in the workload distribution (average value 59.2%) and a reduction in the maximum energy values spent by the processors (average value 32.2%). Such results demonstrate the effectiveness of the proposal

A Fast and Scalable Fault Injection Framework to Evaluate Multi/Many-core Soft Error Reliability

Increasing chip power densities allied to the continuous technology shrink is making emerging multiprocessor embedded systems more vulnerable to soft errors. Due the high cost and design time inherent to board-based fault injection approaches, more appropriate and efficient simulation-based fault injection frameworks become crucial to guarantee the adequate design exploration support at early design phase. In this scenario, this paper proposes a fast and flexible fault injector framework, called OVPSim-FIM, which supports parallel simulation to boost up the fault injection process. Aiming at validating OVPSim-FIM, several fault injection campaigns were performed in ARM processors, considering a market leading RTOS and benchmarks with up to 10 billions of object code instructions. Results have shown that OVPSim-FIM enables to inject faults at speed of up to 10,000 MIPS, depending on the processor and the benchmark profile, enabling to identify erros and exceptions according to different criteria and classifications

A platform-based design framework to boost many-core software development

Embedded software engineers are dealing with complex and large software codes, which will continue to grow. To achieve a cost-effective design, concomitant hardware and software development is required during early design phases. This paper presents an open-source platform based design framework that combines different ADLs and simulators aiming at improving embedded software productivity, targeting future many-core embedded systems. The proposed approach adopts three models: RTL-VHDL level; RTL-SystemC coupled to ISSs; PBD (Platform Based Design) using OVP. The software (operating system and user applications) is the same for both models. Therefore, the OVP modeling allows fast software validation and debuggability. With the SystemC-ISS, it is possible to accurate estimate performance and energy consumption. The low-level model enables, besides area estimation, the validation of low-level protocols, as the communication protocol, network interface or flow-control mechanisms between routers. Results evaluate execution time, simulation time, and the number of executed instructions for several benchmarks using the proposed approach. The OVP model presents in average five times faster than the RTL-SystemC model, and the RTL-SystemC up to 155 times faster than the RTL-VHDL model

Efficient Embedded Software Migration towards Clusterized Distributed-Memory Architectures

A large portion of existing multithreaded embedded sofware has been programmed according to symmetric shared memory platforms where a monolithic memory block is shared by all cores. Such platforms accommodate popular parallel programming models such as POSIX threads and OpenMP. However with the growing number of cores in modern manycore embedded architectures, they present a bottleneck related to their centralized memory accesses. This paper proposes a solution tailored for an efficient execution of applications defined with shared-memory programming models onto on-chip distributed-memory multicore architectures. It shows how performance, area and energy consumption are significantly improved thanks to the scalability of these architectures. This is illustrated in an open-source realistic design framework, including tools from ASIC to microkernel

Impact of Dynamic Voltage Scaling and Thermal Factors on FinFET-based SRAM Reliability

FinFET technology appears as an alternative solution to mitigate short-channel effects in traditional CMOS down-scaled technology. Emerging embedded systems are likely to employ FinFET and dynamic voltage scaling (DVS), aiming to improve system performance and energy-efficiency. This paper claims that the use of DVS increases the susceptibility of FinFET-based SRAM cells to soft errors under radiation effects. To investigate that, a methodology that allows determining the critical charge according to the dynamic behaviour of the temperature as a function of the voltage scaling is used. Obtained results support our claim by showing that both temperature and voltage scaling can increase up to five times the susceptibility of FinFET-based SRAM cells to the occurrence of soft errors

Novel Low Memory Footprint DNN Models for Edge Classification of Surgeons’ Postures

Skill assessment is fundamental to enhance current laparoscopic surgical training and reduce the incidence of musculoskeletal injuries from performing these procedures. Recently, deep neural networks (DNNs) have been used to improve human posture and surgeons’ skills training. While they work well in lab, they normally require significant computational power which makes it impossible to use them on edge devices. This paper presents two low memory footprint DNN models used for classifying laparoscopic surgical skill levels at the edge. Trained models were deployed on three Arm Cortex-M processors using the X-Cube-AI and TensorFlow Lite Micro (TFLM) libraries. Results show that the CUBE-AI-based models give the best relative performance, memory footprint, and accuracy trade-offs when executed on the Cortex-M7.</p

Images Of Research 2016

Images Of Research 2016 Winners: Damian Roland – ‘Spotting the Sick Child – Development of the ‘POPS’ tool‘ - Winner of the Best Image from the College of Medicine, Biological Sciences and Psychology Sarah Hainsworth – ‘Fly Pupae’ - Winner of the Best Image from the College of Science and Engineering Stevie-Jade Hardy – ‘A Human Right’ - Winner of the Best Image from the College of Social Sciences, Arts and Humanities Chris Nixon – ‘Star Eaters’ - Winner of the Peoples Choice Award Mark Williams – ‘Creature From the Black Lagoon’ - Winner of the Best Postgraduate Researcher Image Josephina Sampson – ‘Clustered centrosomes in cancer’ - Second Place for the Best Postgraduate Researcher Image Images Of Research 2016 successful submissions: Aarti Patel – ‘Untitled’ Alex Sutton – ‘Visualisations to assist the analysis of “Which treatment is best?”: a collaboration between medical statisticians and computer scientists from academia and industry’ Andrew Fry – ‘Understanding the mechanics of cancer cell division’ Andrew Hopper – ‘Leicester historians with the wheelchair of Sir Thomas Fairfax at the National Civil War Centre’ Benjamin Hall – ‘The Martian Space Plasma Environment’ Chee Kay Cheung – ‘Shining a light into the kidney’ Christine Pulla – ‘The web of life’ Clare Gunby – ‘The Pocket‘ Dan Stewart – ‘Geophysical Survey of Roman Knossos’ David Siveter – ‘Spectacular 430 MILLION-YEAR-OLD ‘VIRTUAL FOSSILS’ help interpret the evolution of life’ Dawn Watkins – ‘Law in Children’s Lives ‘ Duncan Murdock – ‘Fossils Are Rotten’ Elizabeth Jones – ‘Small Town Urbanity in Nineteenth-Century Wales.’ Emma Jones – ‘An invitation to imagine a world where complete accounts of research are always published’ Emma Raven – ‘Iron Heart of the Crystal – Neutron crystal structure of ascorbate peroxidase compound II’ Geoff Belknap – ‘Citizen Science, and the Uncovering of History of Female Scientists’ Giannis Koukkidis – ‘Salads and Salmonellas’ Giovanna Puppin – ‘Advertising Cultures‘ Janet Nale – ‘Clostridium difficile bacteriophages are effective anti-biofilm agents’ John Goodwin – ‘Pearl Jephcott (1900-1980): The ‘Czechoslovakia’ Notebook’ Jun Li – ‘Untitled’ Kristina Wright – ‘Kenyan artist Michael Soi painting at an exhibition of his work in Seoul, South Korea.’ Laura Gray – ‘Are activity trackers telling us the truth about our physical activity level?’ Loveday Hodgeson – ‘Feminist International Judgments Project: Women’s Voices in International Law’ Luciano Ost – ‘Embedding smart and runtime techniques to improve multi-core systems’ reliability’ Maria Theresia Walach – ‘The Auroral Heart’ Mesut Erzurumluoglu – ‘Breathtaking genes’ Michael Barer – ‘SURVIVAL OF THE FATTEST – a TB bacterium (approximately 0.003 mm in length)’ Nicholas Vass – ‘Visual Community Organising’ Paul Dickinson – ‘A Brightspot on a glass darkly’ Emmanuel Georgoulis, Dr Andrew Norozov and Andrea Cangiani – ‘Chaotic Ice Cream Cones’ Ravi Purohit, Dr Zhanhan Tu, Helen Kuht – ‘Infants’ eye scan’ Rob Hirst – ‘Transmission Electron Microscope image of the unusual case of swollen human respiratory cilia’ Rona Aldo – ‘Supersonic flow modelling thrusts forward airframe-engine design integration of large twin aircraft’ Rozita Adib – ‘The microtubule cytoskeleton‘ Ruslan Davidchack – ‘Tadpole’ Sarah Johnson – ‘Persistence of Flood Waters - Vale of York - Autumn 2015’ Sarah Thornton – ‘Senyum‘ Tu Zhanhan – ‘Hope’ Wendy Fitzgibbon – ‘Supervisible’ Yewande Okuleye – ‘Sense about Cannabis’ </p