Motion estimation and CABAC VLSI co-processors for real-time high-quality H.264/AVC video coding

Real-time and high-quality video coding is gaining a wide interest in the research and industrial community for different applications. H.264/AVC, a recent standard for high performance video coding, can be successfully exploited in several scenarios including digital video broadcasting, high-definition TV and DVD-based systems, which require to sustain up to tens of Mbits/s. To that purpose this paper proposes optimized architectures for H.264/AVC most critical tasks, Motion estimation and context adaptive binary arithmetic coding. Post synthesis results on sub-micron CMOS standard-cells technologies show that the proposed architectures can actually process in real-time 720 × 480 video sequences at 30 frames/s and grant more than 50 Mbits/s. The achieved circuit complexity and power consumption budgets are suitable for their integration in complex VLSI multimedia systems based either on AHB bus centric on-chip communication system or on novel Network-on-Chip (NoC) infrastructures for MPSoC (Multi-Processor System on Chip

User flexibility aware price policy synthesis for smart grids

In order to optimally manage a modern electricity distribution network, peaks in residential users demand should be avoided, as this can reduce energy and network asset management costs. Furthermore, this must be done without compressing residential users demand. To this aim, in a demand response setting, residential users are given a price policy, which economically motivates them to shift their loads in order to achieve this goal. However, if the price policy for all users is similar, this demand response may result in simply shifting the demand peaks (peak rebound), leaving the problem unsolved. In this paper we propose a novel methodology which i) for each network substation s, automatically computes the desired power profile to be kept in order to optimally manage the network itself, ii) for each network substation s, automatically synthesizes individualized price policies for residential users connected to s, so that s is kept at the desired profile. Note that price policies individualization avoids the peak rebound problem, as different users have different low tariff areas. Furthermore, our methodology measures the flexibility of a residential user as the capacity needed by a home energy storage system (e.g., a battery) to always follow the given price policy, thus mitigating residential users discomfort. We show the feasibility of our approach on a realistic scenario taken from an existing medium voltage Danish distribution network

KAPow: A System Identification Approach to Online Per-Module Power Estimation in FPGA Designs

In a modern FPGA system-on-chip design, it is often insufficient to simply assess the total power consumption of the entire circuit by design-time estimation or runtime power rail measurement. Instead, to make better runtime decisions, it is desirable to understand the power consumed by each individual module in the system. In this work, we combine boardlevel power measurements with register-level activity counting to build an online model that produces a breakdown of power consumption within the design. Online model refinement avoids the need for a time-consuming characterisation stage and also allows the model to track long-term changes to operating conditions. Our flow is named KAPow, a (loose) acronym for ‘K’ounting Activity for Power estimation, which we show to be accurate, with per-module power estimates as close to ±5mW of true measurements, and to have low overheads. We also demonstrate an application example in which a permodule power breakdown can be used to determine an efficient mapping of tasks to modules and reduce system-wide power consumption by over 8%

The Chameleon project in retrospective

In this paper we describe in retrospective the main results of a four year project, called Chameleon. As part of this project we developed a coarse-grained reconfigurable core for DSP algorithms in wireless devices denoted MONTIUM. After presenting the main achievements within this project we present the lessons learned from this project

Dynamic and Leakage Power-Composition Profile Driven Co-Synthesis for Energy and Cost Reduction

Recent research has shown that combining dynamic voltage scaling (DVS) and adaptive body bias (ABB) techniques achieve the highest reduction in embedded systems energy dissipation [1]. In this paper we show that it is possible to produce comparable energy saving to that obtained using combined DVS and ABB techniques but with reduced hardware cost achieved by employing processing elements (PEs) with separate DVS or ABB capability. A co-synthesis methodology which is aware of tasks’ power-composition profile (the ratio of the dynamic power to the leakage power) is presented. The methodology selects voltage scaling capabilities (DVS, ABB, or combined DVS and ABB) for the PEs, maps, schedules, and voltage scales applications given as task graphs with timing constraints, aiming to dynamic and leakage energy reduction at low hardware cost. We conduct detailed experiments, including a real-life example, to demonstrate the effectiveness of our methodology. We demonstrate that it is possible to produce designs that contain PEs with only DVS or ABB technique but have energy dissipation that are only 4.4% higher when compared with the same designs that employ PEs with combined DVS and ABB capabilities