Inter-cluster Thread-to-core Mapping and DVFS on Heterogeneous Multi-cores

Heterogeneous multi-core platforms that contain different types of cores, organized as clusters, are emerging, e.g. ARM's big.LITTLE architecture. These platforms often need to deal with multiple applications, having different performance requirements, executing concurrently. This leads to generation of varying and mixed workloads (e.g. compute and memory intensive) due to resource sharing. Run-time management is required for adapting to such performance requirements and workload variabilities and to achieve energy efficiency. Moreover, the management becomes challenging when the applications are multi-threaded and the heterogeneity needs to be exploited. The existing run-time management approaches do not efficiently exploit cores situated in different clusters simultaneously (referred to as inter-cluster exploitation) and DVFS potential of cores, which is the aim of this paper. Such exploitation might help to satisfy the performance requirement while achieving energy savings at the same time. Therefore, in this paper, we propose a run-time management approach that first selects thread-to-core mapping based on the performance requirements and resource availability. Then, it applies online adaptation by adjusting the voltage-frequency (V-f) levels to achieve energy optimization, without trading-off application performance. For thread-to-core mapping, offline profiled results are used, which contain performance and energy characteristics of applications when executed on the heterogeneous platform by using different types of cores in various possible combinations. For an application, thread-to-core mapping process defines the number of used cores and their type, which are situated in different clusters. The online adaptation process classifies the inherent workload characteristics of concurrently executing applications, incurring a lower overhead than existing learning-based approaches as demonstrated in this paper. The classification of workload is performed using the metric Memory Reads Per Instruction (MRPI). The adaptation process pro-actively selects an appropriate V-f pair for a predicted workload. Subsequently, it monitors the workload prediction error and performance loss, quantified by instructions per second (IPS), and adjusts the chosen V-f to compensate. We validate the proposed run-time management approach on a hardware platform, the Odroid-XU3, with various combinations of multi-threaded applications from PARSEC and SPLASH benchmarks. Results show an average improvement in energy efficiency up to 33% compared to existing approaches while meeting the performance requirements

Wearable and autonomous computing for future smart cities: open challenges

The promise of smart cities offers the potential to change the way we live, and refers to the integration of IoT systems for people-centred applications, together with the collection and processing of data, and associated decision making. Central to the realization of this are wearable and autonomous computing systems. There are considerable challenges that exist in this space that require research across different areas of electronics and computer science; it is this multidisciplinary consideration that is novel to this paper. We consider these challenges from different perspectives, involving research in devices, infrastructure and software. Specifically, the challenges considered are related to IoT systems and networking, autonomous computing, wearable sensors and electronics, and the coordination of collectives comprising human and software agents

A fast and accurate energy source emulator for wireless sensor networks

The capability to either minimize energy consumption in battery-operated devices, or to adequately exploit energy harvesting from various ambient sources, is central to the development and engineering of energy-neutral wireless sensor networks. However, the design of effective networked embedded systems targeting unlimited lifetime poses several challenges at different architectural levels. In particular, the heterogeneity, the variability, and the unpredictability of many energy sources, combined to changes in energy required by powered devices, make it difficult to obtain reproducible testing conditions, thus prompting the need of novel solutions addressing these issues. This paper introduces a novel embedded hardware-software solution aimed at emulating a wide spectrum of energy sources usually exploited to power sensor networks motes. The proposed system consists of a modular architecture featuring small factor form, low power requirements, and limited cost. An extensive experimental characterization confirms the validity of the embedded emulator in terms of flexibility, accuracy, and latency while a case study about the emulation of a lithium battery shows that the hardware-software platform does not introduce any measurable reduction of the accuracy of the model. The presented solution represents therefore a convenient solution for testing large-scale testbeds under realistic energy supply scenarios for wireless sensor networks

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Energy-neutral wireless-powered networks

The Internet of Things (IoT) is a key enabler for remote monitoring and control of any medium with wireless devices deployed in substantial numbers. However, these devices often lack the desired lifetimes due to their incompetent batteries. If the envisaged scale of the IoT is realized, replenishing millions of batteries will become impractical. To address this issue, joint utilization of two prominent technologies, energy harvesting (EH) and wireless power transfer (WPT), is explored in this letter. By coupling data from empirical measurements on EH profiles with federal communications commission (FCC) regulations on indoor WPT, we propose and numerically evaluate design guidelines for energy-neutral wireless-powered networks, in which a source first extracts energy from its medium and then uses the collected energy to operate wireless devices via WPT. The initial findings reveal that the IoT devices in a 100 m2 office building can be remotely energized by only three EH-enabled wireless power transmitting sources validating the proposed architecture