Toward a group delay reduction in digital filtering

Finite impulse response (FIR) filters are often used in digital signal processing applications because their linear phase properties do not introduce group delay distortion. While this property is desirable, we may also desire that the filter exhibit zero group delay to suppress the causal time offset between the input and output of the filter. We can minimize the causal delay by the use of recursive minimum phase filters but these introduce an objectionable group delay distortion. We desire both zero group delay and a nonrecursive impulse response (IR). This filter can be applied to input signals indirectly through a modified overlap and save FFT based circular convolution. The desired result is obtained in our proposed new filtering technique: the modified overlap and save method (MOSM). We accomplish this by redefining the time origin of the prototype filter's impulse response by circularly shifting the response in the FFT filter time vector till the symmetry point coincides with the vector's zero index.     

Threshold temperature scaling: Heuristic to address temperature and power issues in MPSoCs

In this article, we propose a scheduling based temperature and power-aware heuristic for multi-core systems. Instead of using a fixed value of temperature threshold in load balancing techniques, the proposed heuristic suggests adjusting the value of threshold temperature as a function of the workload. As the workload reduces, the value of the threshold is lowered accordingly and vice versa. Lowering the value of threshold temperature decreases the temperature peaks, temperature spatial, and temporal gradients. Furthermore, it also reduces the total power consumed by the processing unit. The effectiveness of the approach is evaluated in a simulation-based environment that includes a scheduling and a thermal modeling tool. For evaluation, the heuristic is integrated with a state of the art load balancing technique based on global scheduling and a comparison is performed with the popular thermal-aware techniques. The results analysis shows that the use of proposed heuristic lowers the temperature peak by up to 7 °C, temperature spatial gradients by up to 35%, temporal gradient by 65%, and power utilization by up to 5.5% when compared with the state-of-the-art thermal balancing techniques and predictive thermal-aware models.     

Reliability-aware low energy scheduling in real time systems with shared resources

Dynamic voltage scaling (DVS) is a technique which is widely used to save energy in a real time system. Recent research shows that it has a negative impact on the system reliability. In this paper, we consider the problem of the system reliability and focus on a periodic task set that the task instance shares resources. Firstly, we present a static low power scheduling algorithm for periodic tasks with shared resources called SLPSR which ignores the system reliability. Secondly, we prove that the problem of the reliability-aware low power scheduling for periodic tasks with shared resources is NP-hard and present two heuristic algorithms called SPF and LPF respectively. Finally, we present a dynamic low power scheduling algorithm for periodic tasks with shared resources called DLPSR to reclaim the dynamic slack time to save energy while preserving the system reliability. Experimental results show that the presented algorithm can reduce the energy consumption while improving the system reliability.     

FERMAT: FPGA energy reduction method by approximation theory

The Journal of Supercomputing - Today’s field programmable gate arrays (FPGAs) offer a significant computational power and are commonly used in modern commercial digital designs. However,...     

Performance linked dynamic cache tuning: A static energy reduction approach in tiled CMPs

Advancement in semiconductor technology increases power density in recent Chip Multi-Processors (CMPs) which significantly increases the leakage energy consumptions of on-chip Last Level Caches (LLCs). Performance linked dynamic tuning in LLC size is a promising option for reducing the cache leakage.This paper reduces static power consumption by dynamically shutting down or turning on cache banks based upon system performance and cache bank usage statistics. Shutting down of a cache bank remaps its future requests to another active bank, called as target bank. The proposed method is evaluated on three different implementation policies, viz (1) The system can decide to shutdown or turn-on some cache banks periodically throughout the process execution. (2) The system allows to shutdown banks initially and once the bank restarting initiates, no more shutdown is permitted further. (3) This policy resizes cache like first policy with some predefined time slices, in which cache cannot be resized.For a 4MB 4 way set associative L2 cache, experimental analysis shows 66% reduction in static energy with 29% gain in Energy Delay Product (EDP) for first strategy; for the second policy, static power is reduced by 59% with 27% savings in EDP. Finally, last policy saves 65% in static power and 30% in EDP with minimal performance penalty.     

Socially shared regulation of learning in CSCL: understanding and prompting individual- and group-level shared regulatory activities

The field of computer supported collaborative learning (CSCL) is progressing instrumentally and theoretically. Nevertheless, few studies examine the effectiveness and efficiency of CSCL with respect to cognitive, motivational, emotional, and social issues, despite the fact that the role of regulatory processes is critical for the quality of students’ engagement in collaborative learning settings. We review the four earlier lines in developing support in CSCL and show how there has been a lack of work to support individuals in groups to engage in, sustain, and productively regulate their own and the group’s collaborative processes. Our aim is to discuss how our conceptual work in socially shared regulation of learning (SSRL) contributes to effective and efficient CSCL, what tools are presently available, and what the implications of research on these tools are for future tool development.     

CoQoS: Coordinating QoS-aware shared resources in NoC-based SoCs

Contention in performance-critical shared resources affects performance and quality-of-service (QoS) significantly. While this issue has been studied recently in CMP architectures, the same problem exists in SoC architectures where the challenge is even more severe due to the contention of shared resources between programmable cores and fixed-function IP blocks. In the SoC environment, efficient resource sharing and a guarantee of a certain level of QoS are highly desirable. Researchers have proposed different techniques to support QoS, but most existing works focus on only one individual resource. Coordinated management of multiple QoS-aware shared resources remains an open problem. In this paper, we propose a class-of-service based QoS architecture (CoQoS), which can jointly manage three performance-critical resources (cache, NoC, and memory) in a NoC-based SoC platform. We evaluate the interaction between the QoS-aware allocation of shared resources in a trace-driven platform simulator consisting of detailed NoC and cache/memory models. Our simulations show that the class-of-service based approach provides a low-cost flexible solution for SoCs. We show that assigning the same class-of-service to multiple resources is not as effective as tuning the class-of-service of each resource while observing the joint interactions. This demonstrates the importance of overall QoS support and the coordination of QoS-aware shared resources.     

Signalling regions: Multiprocessing in a shared memory reconsidered

The goal of this paper is to return attention to two problems that arise in the context of supporting the monitor as a mechanism for concurrent programming. This paper will re-examine the monitor concept in its original context—a multiprocessing environment implemented on a single processor sharing memory with and being interrupted by asynchronous peripheral devices—and will address the two previously unresolved problems. The first is the conflict between the immediate resumption requirement in explicit signalling and the policies and priorities of the process scheduler. The second is the possibility of deadlock inherent in nested monitors and in its most important instance, the dynamic resource allocation problem. After briefly describing the historical context of these two problems, the paper proposes a language structure called a signalling region that together with the notion of encapsulation by modules solves the immediate resumption problem and avoids the nested monitor problem. The former is done by a combination of the signal-and-return semantics of Concurrent Pascal and the signal-and-continue semantics of Mesa and StarMod. The latter is done by suggesting that mutual exclusion and data encapsulation are distinct concepts that, if separated, make nested encapsulation possible while avoiding the problems of nested mutual exclusion. Classical examples of the use of signalling regions in an extended Modula-2 are given as well as an implementation by translation to unextended Modula-2 together with a Kernel module.     

奇异值能量差分谱在信号降噪中的应用

为了提高现场采集信号的信噪比,针对奇异值分解中重构矩阵有效阶次确定难的问题,提出了一种基于奇异值能量差分谱的信号降噪方法。该方法根据有用信号与噪声能量的差异性,通过构造信号的奇异值能量差分谱,将能量差分谱曲线中最大峰值点作为重构信号的有效阶次来实现有用信号和噪声的分离,能够使信号奇异值降噪阶次得到合理确定,较好地保护了原始信号中有用信息的完整性,获得了较大的信噪比,对后续进行信号特征的准确提取和分析至关重要。仿真和实例分析结果验证了该方法的有效性。     

小波域能量谱和非线性降维的病理嗓音识别

提出了一种病理嗓音小波域建模分析方法并对病理嗓音进行识别。首先对病理嗓音进行多尺度连续小波变换时频分析,然后对沿尺度轴方向的能量谱进行高斯混合建模,采用最大似然估计方法求解得到模型统计学参数作为特征参数,并且使用改进的动态加权局部线性嵌入方法对特征参数进行非线性降维处理。实验结果表明,小波域能量谱特征经过非线性降维后对病理嗓音的识别率达到97.45%,改进的动态加权局部线性嵌入方法降维效果优于主成分分析和局部线性嵌入方法。     

Smart search space reduction for approximate computing: A low energy HEVC encoder case study

The approximate computing paradigm provides methods to optimize algorithms while considering both application quality of service and computational complexity. Approximate computing can be applied at different levels of abstraction, from algorithm level to application level. Approximate computing at algorithm level reduces the computational complexity by approximating or skipping computational blocks. A number of applications in the signal and image processing domain integrate algorithms based on discrete optimization techniques. These techniques minimize a cost function by exploring an application parameter search space. In this paper, a new methodology is proposed that exploits the computation-skipping approximate computing concept. The methodology, named Smart Search Space Reduction(Sssr), explores at design time the Pareto relationship between computational complexity and application quality. At run time, an approximation manager can then early select a good candidate configuration. Sssr reduces the run time search space and, in turn, reduces computational complexity. An efficient Sssr technique adjusts at design time the configuration selectivity while selecting at run time the most suitable functions to skip. The real time High Efficiency Video CodingHevc encoder in All Intra(AI) profile is used as a case study to illustrate the benefits of Sssr. In this application, two discrete optimizations are performed. They explore different coding parameters and select the values leading to the minimal cost in terms of a tradeoff between bitrate, quality and computational energy by acting on both the Hevc coding-tree partitioning and the intra-modes. Combining two Sssrs iterations on this use case, the energy consumption is reduced by up to 77%. Moreover, the combination of the two Sssrs iterations in comparison to using only one reduces the BD-BR bitrate/quality metric by 4% for the same energy consumption.     

Promoting socially shared regulation of learning in CSCL: Progress of socially shared regulation among high- and low-performing groups

Collaborative groups encounter many challenges in their learning. They need to recognize challenges that may hinder collaboration, and to develop appropriate strategies to strengthen collaboration. This study aims to explore how groups progress in their socially shared regulation of learning (SSRL) in the context of computer-supported collaborative learning (CSCL). Teacher education students (N = 103) collaborated in groups of three to four students during a two-month multimedia course. The groups used the Virtual Collaborative Research Institute (VCRI) learning environment along with regulation tools that prompted them to recognize challenges that might hinder their collaboration and to develop SSRL strategies to overcome these challenges.In the data analysis, the groups reported challenges, and the SSRL strategies they employed were analyzed to specify the focus and function of the SSRL. Process discovery was used to explore how groups progressed in their SSRL. The results indicated that depending on the phase of the course, the SSRL focus and function shifted from regulating external challenges towards regulating the cognitive and motivational aspects of their collaboration. However, the high-performing groups progressed in their SSRL in terms of evidencing temporal variety in challenges and SSRL strategies across time, which was not the case with low performing groups.     

Noise reduction in biomedical speech signal processing based on time and frequency Kalman filtering combined with spectral subtraction

The goal of this paper is to study and propose a new technique for noise reduction used during the reconstruction of speech signals, particularly for biomedical applications. The proposed method is based on Kalman filtering in the time domain combined with spectral subtraction. Comparison with discrete Kalman filter in the frequency domain shows better performance of the proposed technique. The performance is evaluated by using the segmental signal-to-noise ratio and the Itakura-Saito’s distance. Results have shown that Kalman’s filter in time combined with spectral subtraction is more robust and efficient, improving the Itakura-Saito’s distance by up to four times.     

新能源汽车节能减排技术研究进展(3)——传感器系统

描述了电动力汽车(EV)、混合动力汽车(HEV)和燃料电池汽车(FCV)节能减排技术的研究进展,主要从以下三方面论述:发动机系统、能量管理系统、传感器系统,并指出了存在问题和发展方向.本文介绍了传感器系统,包括新型汽车传感器、新的零部件和新的系统应用.     

Protected shared variables in VHDL: IEEE standard 1076a

In this article, we show a variety of problems that can arise from unprotected concurrent access to shared variables and review the idea of monitors, which forms the basis of the proposed language change. We then describe the new language feature, protected types, and give some guidelines on using them for hardware modeling. We also include examples to illustrate their use     

Sharc: managing CPU and network bandwidth in shared clusters

We argue the need for effective resource management mechanisms for sharing resources in commodity clusters. To address this issue, we present the design of Sharc-a system that enables resource sharing among applications in such clusters. Sharc depends on single node resource management mechanisms such as reservations or shares, and extends the benefits of such mechanisms to clustered environments. We present techniques for managing two important resources-CPU and network interface bandwidth-on a cluster-wide basis. Our techniques allow Sharc to 1) support reservation of CPU and network interface bandwidth for distributed applications, 2) dynamically allocate resources based on past usage, and 3) provide performance isolation to applications. Our experimental evaluation has shown that Sharc can scale to 256 node clusters running 100,000 applications. These results demonstrate that Sharc can be an effective approach for sharing resources among competing applications in moderate size clusters.     

The renaming problem in shared memory systems: An introduction

Exploring the power of shared memory communication objects and models, and the limits of distributed computability are among the most exciting research areas of distributed computing. In that spirit, this paper focuses on a problem that has received considerable interest since its introduction in 1987, namely the renaming problem. It was the first non-trivial problem known to be solvable in an asynchronous distributed system despite process failures. Many algorithms for renaming and variants of renaming have been proposed, and sophisticated lower bounds have been proved, that have been a source of new ideas of general interest to distributed computing. It has consequently acquired a paradigm status in distributed fault-tolerant computing.In the renaming problem, processes start with unique initial names taken from a large name space, then deciding new names such that no two processes decide the same new name and the new names are from a name space that is as small as possible.This paper presents an introduction to the renaming problem in shared memory systems, for non-expert readers. It describes both algorithms and lower bounds. Also, it discusses strong connections relating renaming and other important distributed problems such as set agreement and symmetry breaking.     

A Belgian Transect: Field Broadcast in the expanded field of ecology

Abstract

This article sets out the notion of a Field Broadcast from the dual perspective of Rebecca Birch, one of the developers of a bespoke version of Flash Media Live Encoder and Bram Thomas Arnold, an artist who uses a case study from Sideways Festival, Belgium, 2012. Field Broadcast enables an artist to be in a field, suitably equipped, and stream live footage to an audience. It is an experiment in place, site and the notion of a field. It is a new method of making work in the space between site-specific performance and the digital realm: a way of working that enables artists to generate new artworks within the non-place of the Internet. Birch introduces the technology from a number of perspectives before it is fleshed out with evidence and experience from a live project that took place in Belgium in 2012. Sideways was a festival that traversed Belgium over four weeks and 400?km, with artists walking and generating work en route. The possibilities offered by Field Broadcast are explored in relation to the expanded field of ecology amidst Bourriaud's The Radicant (2009), Guatarri's The Three Ecologies (2005) and Morton's Ecology Without Nature (2007 Morton, Timothy. 2007. Ecology Without Nature. Cambridge, MA: Harvard University Press. [Google Scholar]).