1,720,970 research outputs found
Dataflow-based adaptation framework with coarse-grained reconfigurable accelerators
No full textToday, the demand of adaptive systems is constantly growing, especially in hard-constrained contexts such as Cyber-Physical Systems. However, the efficient management of such platforms requires dealing with several issues such as the real-time execution, energy saving and dynamic context changes. Such strict requirements imply a high flexibility of the application and of the architecture on which it is executed. Runtime managers offer the possibility to dynamically schedule and map an application on the available software processing units. However, hardware acceleration may also be necessary for computationally-intensive workloads that depend on the running functionality, additionally complicating runtime management. Coarse-Grained Reconfigurable (CGR) accelerators have the ability to switch among different domain-specific functionalities with a small overhead. To support energy and time adaptivity in heterogeneous systems, and to exploit multi-core architectures and CGR accelerators, this work proposes the combination of the SPIDER software runtime manager and the dataflow-to-hardware MDC design suite for CGR accelerators
A Custom dual-processor System for Real-time Neural Signal Processing
No full textThis paper presents a custom dual-processor SoC architecture, studied and customized to support information extraction from signals acquired from Peripheral Neural System, for prosthetic applications. The main tasks accomplished by the processing implemented on the computing platform are noise removal and identification of neural spikes. On-board execution of such tasks allows to identify which samples actually contain useful information. Thus, it reduces required input/output bandwidth, so that connection to the external environment can be implemented using a Bluetooth Low Energy device. The overall SoC architecture has power consumption compliant with implant-related constraints with a battery lifetime of around one-day. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved
Extending architecture modeling for signal processing towards GPUs
No full textEfficient usage of heterogeneous computing architectures requires distribution of the workload to available processing elements. Traditionally, this mapping is done based on information acquired from application profiling. To reduce the high amount of manual work related to mapping, statistical application and architecture modeling can be applied for automating mapping exploration. Application modeling has been studied extensively, whereas architecture modeling has received less attention. Originally developed for signal processing systems, Linear System Level Architecture (LSLA) is the first architecture modeling approach that clearly distinguishes the underlying computation hardware from software. Up to now, LSLA has covered the modeling of multicore CPUs. This work proposes extending the LSLA model with GPU support, by including the notion of parallelism. The proposed GPU modeling extension is evaluated by performance estimation of three signal processing applications with various workload distributions on a desktop GPU, and a mobile GPU. The measured average fidelity of the proposed model is 93%
PathTracing: Raising the level of understanding of processing latency in heterogeneous MPSoCs
No full textUnderstanding and predicting response time is a major concern in most systems. However, the complexity of heterogeneous Multiprocessor Systems-on-Chipss (MPSoCss) makes it difficult to provide early evaluation of system execution latency when executing parallel applications. In particular, knowledge about the factors that determine latency is a must in order to effectively drive system-level scheduling and applicative design decisions.
In this paper, we aim at demonstrating that a novel knowledge level is required for analyzing the key factors that influence system execution latency. For that purpose, we propose the concept of Jaccard Gantt similarity score and demonstrate that the straightforward method consisting in scheduling a Directed Acyclic Graph (DAG) of tasks, each with a Deterministic Actor Execution Time (DAET) set from individual task characterization, leads to low Jaccard Gantt similarity scores. We thus propose a new level of system analysis, called PathTracing, that relies on an evaluation of the application critical path and on an analysis of the interferences caused both by scheduling and by architectural costs
The Multi-Dataflow Composer tool: An open-source tool suite for optimized coarse-grain reconfigurable hardware accelerators and platform design
Full text linkModern embedded and cyber-physical systems require every day more performance, power efficiency and flexibility, to execute several profiles and functionalities targeting the ever growing adaptivity needs and preserving execution efficiency. Such requirements pushed designers towards the adoption of heterogeneous and reconfigurable substrates, which development and management is not that straightforward. Despite acceleration and flexibility are desirable in many domains, the barrier of hardware deployment and operation is still there since specific advanced expertise and skills are needed. Related challenges are effectively tackled by leveraging on automation strategies that in some cases, as in the proposed work, exploit model-based approaches. This paper is focused on the Multi-Dataflow Composer (MDC) tool, that intends to solve issues related to design, optimization and operation of coarse-grain reconfigurable hardware accelerators and their easy adoption in modern heterogeneous substrates. MDC latest features and improvements are introduced in detail and have been assessed on the so far unexplored robotics application field. A multi-profile trajectory generator for a robotic arm is implemented over a Xilinx FPGA board to show in which cases coarse-grain reconfiguration can be applied and which can be the parameters and trade-offs MDC will allow users to play with
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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