An Investigation of Clock Skew Using a Wirelength-Aware Floorplanning Process in the Pre-Placement Stages of MSV Layouts

Managing the timing constraints has become an important factor in the physical design of multiple supply voltage (MSV) integrated circuits (IC). Clock distribution and module scheduling are some of the conventional methods used to satisfy the timing constraints of a chip. In this paper, we propose a simulated annealing-based MSV floorplanning methodology for the design of ICs within the timing budget. Additionally, we propose a modified SKB tree representation for floorplanning the modules in the design. Our algorithm finds the optimal dimensions and position of the clocked modules in the design to reduce the wirelength and satisfy the timing constraints. The proposed algorithm is implemented in IWLS 2005 benchmark circuits and considers power, wirelength, and timing as the optimization parameters. Simulation results were obtained from the Cadence Innovus digital system taped-out at 45 nm. Our simulation results show that the proposed algorithm satisfies timing constraints through a 30.6% reduction in wirelength.

Temporo-cerebellar connectivity underlies timing constraints in audition

The flexible and efficient adaptation to dynamic, rapid changes in the auditory environment likely involves generating and updating of internal models. Such models arguably exploit connections between the neocortex and the cerebellum, supporting proactive adaptation. Here we tested whether temporo-cerebellar disconnection is associated with the processing of sound at short-timescales. First, we identify lesion-specific deficits for the encoding of short timescale spectro-temporal non-speech and speech properties in patients with left posterior temporal cortex stroke. Second, using lesion- guided probabilistic tractography in healthy participants, we revealed bidirectional temporo-cerebellar connectivity with cerebellar dentate nuclei and crura I/II. These findings support the view that the encoding and modeling of rapidly modulated auditory spectro-temporal properties can rely on a temporo-cerebellar interface. We discuss these findings in view of the conjecture that proactive adaptation to a dynamic environment via internal models is a generalizable principle.

Geometry, kinematics, and magnitude of extension across the Thakkhola Graben, Central Nepal Himalaya

The Thakkhola Graben has been a region of geologic inquiry for many decades. Although it is widely viewed to be in a class of structures that are important in accommodating the three-dimensional strain within the Himalayan thrust wedge, we still lack a detailed understanding of the total finite strain accommodated by graben-bounding faults, as well as their shape and cross-cutting relationships with structures deeper in the thrust wedge. Using geologic mapping and structural analysis, we show that a suite of pre-extensional shortening structures is offset by normal-oblique faults bounding the Thakkhola Graben that we use to define a piercing line. We calculate these faults to have accommodated 8.7 kilometers of vertical thinning, 7.2 kilometers of arc-perpendicular shear, and only 2.2 kilometers of arc-parallel extension. The magnitude of arc-parallel extension is quite low compared to extensional structures to the west in the Gurla Mandhata-Humla region. The cross-cutting relationships established in this study and timing constraints determined by previous works are consistent with a structural history of crustal thickening leading to foreland propagation of the locus of arc-perpendicular shortening contemporaneous with hinterland extension.

Answer-Set Programming for Lexicographical Makespan Optimisation in Parallel Machine Scheduling

We deal with a challenging scheduling problem on parallel-machines with sequence-dependent setup times and release dates from a real-world application of semiconductor work-shop production. There, jobs can only be processed by dedicated machines, thus few machines can determine the makespan almost regardless of how jobs are scheduled on the remaining ones. This causes problems when machines fail and jobs need to be rescheduled. Instead of optimising only the makespan, we put the individual machine spans in non-ascending order and lexicographically minimise the resulting tuples. This achieves that all machines complete as early as possible and increases the robustness of the schedule. We study the application of Answer-Set Programming (ASP) to solve this problem. While ASP eases modelling, the combination of timing constraints and the considered objective function challenges current solving technology. The former issue is addressed by using an extension of ASP by difference logic. For the latter, we devise different algorithms that use multi-shot solving. To tackle industrial-sized instances, we study different approximations and heuristics. Our experimental results show that ASP is indeed a promising KRR paradigm for this problem and is competitive with state-of-the-art CP and MIP solvers.

Energy-Efficient NoC-Based Systems for Real-Time Multimedia Applications using Approximate Computing

This work presents an energy-efficient NoC-based system for real-time multimedia applications employing approximate computing. The proposed video processing system, called SApp-NoC, is efficient in both energy and quality (QoS), employing a scalable NoC architecture composed of processing elements designed to accelerate the HEVC Fractional Motion Estimation (FME). Two solutions are proposed: HSApp-NoC (Heuristc-based SApp-NoC), and MLSApp-NoC (Machine Learning-based SApp-NoC). When compared to a precise solution processing 4K videos at 120 fps, HSApp-NoC and MLSApp-NoC reduce about 48.19% and 31.81% the energy consumption, at small quality reduction of 2.74% and 1.09%, respectively. Furthermore, a set of schedulability analysis is also proposed in order to guarantee the meeting of timing constraints at typical workload scenarios.

An MQTT Brokers Distribution Based on Mist Computing for Real-Time IoT Communications

As we consider the number of IoT time-sensitive applications , the transfer of data to a remote data center and server such as Cloud, Fog, and Edge becomes inefficient since the deadline constraint is not satisfied. Thus, ensuring that the IoT time-sensitive applications meet their timing constraints is a challenge. Mist Computing is closer to IoT devices, presenting the lowest communication delay but less computational resource than the Cloud, Fog, and Edge. Seeing several IoT devices use MQTT protocol to access the data due to its lightness and flexibility, we propose an architecture for IoT time-sensitive applications based on MQTT protocol and integrating Mist Computing. We focus on distributing the MQTT brokers over Mist nodes to satisfy the deadline constraints with the consideration of the limited resource of Mist nodes. Hence, we propose an approach for the selection of the appropriate MQTT Mist broker. We have also proposed MQTT communication model that provides the M/M/1 based analysis for delay computing and energy conception. The experiment results show that our proposal is very effective for time-sensitive applications and also maximize the lifetime of IoT systems since it minimizes the cumulative energy of the system. Compared to MQTT Edge broker distribution, our solution provides the lesser delay of communication between IoT devices.

On Improving Model Checking of Time Petri Nets and Its Application to the Formal Verification

Time Petri nets (TPN) are successfully used in the specification and analysis of distributed systems that involve explicit timing constraints. Especially, model checking TPN is a hopeful method for the formal verification of such complex systems. For this, it is promising to lean to the construction of an optimized version of the state space. The well-known methods of state space abstraction are SCG (state class graph) and ZBG (graph based on zones). For ZBG, a symbolic state represents the real evaluations of the clocks of the TPN; it is thus possible to directly check quantitative time properties. However, this method suffers from the state space explosion. To attenuate this problem, the authors propose in this paper to combine the ZBG approach with the partial order reduction technique based on stubborn set, leading thus to the proposal of a new state space abstraction called reduced zone-based graph (RZBG). The authors show via case studies the efficiency of the RZBG which is implemented and integrated within the 〖TPN-TCTL〗_h^∆ model checking in the model checker Romeo.

Concurrent Transaction Logic with Priority and Timing Constraints

Concurrent Transaction Logic with Priority and Timing Constraints

Concurrent Transaction Logic with Priority and Timing Constraints

Concurrent Transaction Logic with Priority and Timing Constraints