Global Wires Research Articles

Global Interconnect Optimization

We propose a new comprehensive solution to global interconnect optimization. Traditional buffering algorithms mostly insert repeaters on a net-by-net basis based on slacks and possibly guided by global wires. We show how to integrate routing congestion, placement congestion, global timing constraints, power consumption, and additional constraints into a single resource sharing formulation. The core of our algorithm is a new buffered routing subroutine. Given a net and Lagrangean resource prices for routing, timing, placement, and power, it computes a buffered Steiner tree. The resource sharing framework provides a special multiplicative price update for fast convergence. Our algorithm is fast enough for practical instances. We demonstrate experimentally on 7nm microprocessor units that it significantly improves timing while reducing netlength and power consumption in an industrial design flow. Our implementation scales well under parallelization with up to 128 threads.

Hierarchical Modular Structure of the Drosophila Connectome.

The structure of neural circuitry plays a crucial role in brain function. Previous studies of brain organization generally had to trade off between coarse descriptions at a large scale and fine descriptions on a small scale. Researchers have now reconstructed tens to hundreds of thousands of neurons at synaptic resolution, enabling investigations into the interplay between global, modular organization, and cell type-specific wiring. Analyzing data of this scale, however, presents unique challenges. To address this problem, we applied novel community detection methods to analyze the synapse-level reconstruction of an adult female Drosophila melanogaster brain containing >20,000 neurons and 10 million synapses. Using a machine-learning algorithm, we find the most densely connected communities of neurons by maximizing a generalized modularity density measure. We resolve the community structure at a range of scales, from large (on the order of thousands of neurons) to small (on the order of tens of neurons). We find that the network is organized hierarchically, and larger-scale communities are composed of smaller-scale structures. Our methods identify well-known features of the fly brain, including its sensory pathways. Moreover, focusing on specific brain regions, we are able to identify subnetworks with distinct connectivity types. For example, manual efforts have identified layered structures in the fan-shaped body. Our methods not only automatically recover this layered structure, but also resolve finer connectivity patterns to downstream and upstream areas. We also find a novel modular organization of the superior neuropil, with distinct clusters of upstream and downstream brain regions dividing the neuropil into several pathways. These methods show that the fine-scale, local network reconstruction made possible by modern experimental methods are sufficiently detailed to identify the organization of the brain across scales, and enable novel predictions about the structure and function of its parts.Significance Statement The Hemibrain is a partial connectome of an adult female Drosophila melanogaster brain containing >20,000 neurons and 10 million synapses. Analyzing the structure of a network of this size requires novel and efficient computational tools. We applied a new community detection method to automatically uncover the modular structure in the Hemibrain dataset by maximizing a generalized modularity measure. This allowed us to resolve the community structure of the fly hemibrain at a range of spatial scales revealing a hierarchical organization of the network, where larger-scale modules are composed of smaller-scale structures. The method also allowed us to identify subnetworks with distinct cell and connectivity structures, such as the layered structures in the fan-shaped body, and the modular organization of the superior neuropil. Thus, network analysis methods can be adopted to the connectomes being reconstructed using modern experimental methods to reveal the organization of the brain across scales. This supports the view that such connectomes will allow us to uncover the organizational structure of the brain, which can ultimately lead to a better understanding of its function.

Operation Zarb-e-Azb in the Global Wire Services: A Framing Analysis

Pakistan has become a victim of terrorism after its involvement in the ongoing war on terror. The country has lost thousands of civilians and security personnel in this American-led war. Though, Pakistan has always been treated negatively by the media organizations of elite nations. Operation Zarb-e-Azb was a combined military action of the Pakistan army against the armed insurgent groups in North Waziristan which was launched in the year 2014. The current study attempted to examine the framing of Operation Zarb-e-Azb in global wire services. For this purpose, AFP, AP and Reuters were selected. Through the technique of convenient sampling, a total of 300 news items from the entire period of operation were selected for analysis.Quantitative as well as qualitative content analysis and interpretive analysis have been used as a research design for this study. The results indicated that the global wire services framed the news stories of military operations in a positive way. The terrorism and militant threat frame was more dominant in global wires as compared to other frames. The results also revealed that the global wires framed this operation differently by representing the foreign policy and interests of their respective states.

Differences in Intrinsic Gray Matter Connectivity and Their Genomic Underpinnings in Autism Spectrum Disorder

BackgroundAutism is a heterogeneous neurodevelopmental condition accompanied by differences in brain connectivity. Structural connectivity in autism has mainly been investigated within the white matter. However, many genetic variants associated with autism highlight genes related to synaptogenesis and axonal guidance, thus also implicating differences in intrinsic (i.e., gray matter) connections in autism. Intrinsic connections may be assessed in vivo via so-called intrinsic global and local wiring costs. MethodsHere, we examined intrinsic global and local wiring costs in the brain of 359 individuals with autism and 279 healthy control participants ages 6 to 30 years from the EU-AIMS LEAP (Longitudinal European Autism Project). FreeSurfer was used to derive surface mesh representations to compute the estimated length of connections required to wire the brain within the gray matter. Vertexwise between-group differences were assessed using a general linear model. A gene expression decoding analysis based on the Allen Human Brain Atlas was performed to link neuroanatomical differences to putative underpinnings. ResultsGroup differences in global and local wiring costs were predominantly observed in medial and lateral prefrontal brain regions, in inferior temporal regions, and at the left temporoparietal junction. The resulting neuroanatomical patterns were enriched for genes that had been previously implicated in the etiology of autism at genetic and transcriptomic levels. ConclusionsBased on intrinsic gray matter connectivity, the current study investigated the complex neuroanatomy of autism and linked between-group differences to putative genomic and/or molecular mechanisms to parse the heterogeneity of autism and provide targets for future subgrouping approaches.

Superconformal Film Growth: From Smoothing Surfaces to Interconnect Technology.

ConspectusElectronics manufacturing involves Cu electrodeposition to form 3D circuitry of arbitrary complexity. This ranges from nanometer-wide interconnects between individual transistors to increasingly large multilevel intermediate and global scale on-chip wiring. At larger scale, similar technology is used to form micrometer-sized high aspect ratio through-silicon vias (TSV) that facilitate chip stacking and multilevel printed circuit board (PCB) metallization. Common to all of these applications is void-free Cu filling of lithographically defined trenches and vias. While line-of-sight physical vapor deposition processes cannot accomplish this feat, the combination of surfactants and electrochemical or chemical vapor deposition enables preferential metal deposition within recessed surface features known as superfilling. The same superconformal film growth processes account for the long-reported but poorly understood smoothing and brightening action provided by certain electroplating additives. Prototypical surfactant additives for superconformal Cu deposition from acid-based CuSO4 electrolytes include a combination of halide, polyether suppressor, sulfonate-terminated disulfide, and/or thiol accelerator and possibly a N-bearing cationic leveler. Many competitive and coadsorption dynamics underlie functional operation of the additives. Upon immersion, Cu surfaces are rapidly covered by a saturated halide layer that makes the interface more hydrophobic, thereby supporting the formation of a polyether suppressor layer. Also, halide serves as a cosurfactant supporting the adsorption of amphiphilic molecular disulfide species on the surface while inhibiting copper sulfide formation and incorporation into the growing deposit. Furthermore, the dangling hydrophilic sulfonate end group of the accelerator enables activated metal deposition by hindering polyether suppressor assembly. A common thread in superconformal feature filling is additive-derived positive feedback of the metal deposition reaction within recessed or re-entrant regions. For submicrometer features or optically rough surfaces, area reduction that accompanies the motion of concave surface segments results in the most strongly bound adsorbates' enrichment, which for the suppressor-accelerator systems is the sulfonate-terminated disulfide accelerator species. The superfilling and smoothing process is quantitatively captured by the curvature-enhanced adsorbate coverage mechanism. For larger features, such as TSV, whose depths approach the thickness of the hydrodynamic boundary layer, significant compositional and electrical gradients couple with the metal deposition process to give a negative differential resistance and related nonlinear effects on morphological evolution. For certain suppressor-only electrolytes, remarkable bottom-up feature filling occurs where metal deposition disrupts inhibiting adsorbates at the bottom of the TSV or overruns the ability of the suppressor to form due to kinetic or transport limitations. Because the electrical response to changes in interface chemistry is more rapid than mass transport processes, deposition on planar substrates proceeds by bifurcation into passive and active zones, generating Turing patterns. On patterned substrates, active zone development is biased toward the most recessed regions. The distinction between packaging and on-chip metallization will be blurred as the dimensions of the former merge with those of early day on-chip 3D metallization.

Ordered Escape Routing via Assignment of Routability-Driven Detouring Paths

In board-level routing, ordered escape routing becomes a key problem. In this paper, given a set of escape pins inside a pin array, a set of available boundaries and the capacity constraint between two adjacent pins, an efficient algorithm can be proposed to solve the routing problem in ordered escape routing under capacity constraints. Firstly, based on the mapping process of the detouring paths of the untangled nets in one-sided net untangling, the routability-driven pins of the untangled nets can be assigned onto feasible positions and the target pins of the escape nets can be assigned on some available boundaries. Furthermore, based on the assignment of the routability-driven detouring paths with the capacity consideration, the global wires of the escape nets in a pin array can be assigned in single-layer global routing and the routing paths of the escape nets in a pin array can be assigned in single-layer detailed routing. Compared with Luo’s SAT-based algorithm, Jiao’s flow-based algorithm and Yan’s heuristic algorithm for the 6 tested examples with capacity as 1, our proposed algorithm can obtain the same 100% routability of the escape nets. Compared with Yan’s heuristic algorithm for the other 6 tested examples with capacity as 2, our proposed algorithm can use reasonable CPU time to improve 1.9% of the total length of the routed escape nets and 0.25% of routability of the routed escape nets on the achievement of the 100% routability on the average.

Constructive connectomics: How neuronal axons get from here to there using gene-expression maps derived from their family trees.

During brain development, billions of axons must navigate over multiple spatial scales to reach specific neuronal targets, and so build the processing circuits that generate the intelligent behavior of animals. However, the limited information capacity of the zygotic genome puts a strong constraint on how, and which, axonal routes can be encoded. We propose and validate a mechanism of development that can provide an efficient encoding of this global wiring task. The key principle, confirmed through simulation, is that basic constraints on mitoses of neural stem cells—that mitotic daughters have similar gene expression to their parent and do not stray far from one another—induce a global hierarchical map of nested regions, each marked by the expression profile of its common progenitor population. Thus, a traversal of the lineal hierarchy generates a systematic sequence of expression profiles that traces a staged route, which growth cones can follow to their remote targets. We have analyzed gene expression data of developing and adult mouse brains published by the Allen Institute for Brain Science, and found them consistent with our simulations: gene expression indeed partitions the brain into a global spatial hierarchy of nested contiguous regions that is stable at least from embryonic day 11.5 to postnatal day 56. We use this experimental data to demonstrate that our axonal guidance algorithm is able to robustly extend arbors over long distances to specific targets, and that these connections result in a qualitatively plausible connectome. We conclude that, paradoxically, cell division may be the key to uniting the neurons of the brain.

Visual Haptic Feedback for Training of Robotic Suturing.

Current surgical robotic systems are teleoperated and do not have force feedback. Considerable practice is required to learn how to use visual input such as tissue deformation upon contact as a substitute for tactile sense. Thus, unnecessarily high forces are observed in novices, prior to specific robotic training, and visual force feedback studies demonstrated reduction of applied forces. Simulation exercises with realistic suturing tasks can provide training outside the operating room. This paper presents contributions to realistic interactive suture simulation for training of suturing and knot-tying tasks commonly used in robotically-assisted surgery. To improve the realism of the simulation, we developed a global coordinate wire model with a new constraint development for the elongation. We demonstrated that a continuous modeling of the contacts avoids instabilities during knot tightening. Visual cues are additionally provided, based on the computation of mechanical forces or constraints, to support learning how to dose the forces. The results are integrated into a powerful system-agnostic simulator, and the comparison with equivalent tasks performed with the da Vinci Xi system confirms its realism.

Providing an Adaptive Routing along with a Hybrid Selection Strategy to Increase Efficiency in NoC‐Based Neuromorphic Systems

Effective and efficient routing is one of the most important parts of routing in NoC-based neuromorphic systems. In fact, this communication structure connects different units through the packets routed by routers and switches embedded in the network on a chip. With the help of this capability, not only high scalability and high development can be created, but by decreasing the global wiring to the chip level, power consumption can be reduced. In this paper, an adaptive routing algorithm for NoC-based neuromorphic systems is proposed along with a hybrid selection strategy. Accordingly, a traffic analyzer is first used to determine the type of local or nonlocal traffic depending on the number of hops. Then, considering the type of traffic, the RCA and NoP selection strategies are used for the nonlocal and local strategies, respectively. Finally, using the experiments that performed in the simulator environment, it has been shown that this solution can well reduce the average delay time and power consumption.

The Design of CMOS-Compatible Plasmonic Waveguides for Intra-Chip Communication

A CMOS-compatible plasmonic waveguide with a metal or metal-like strip sandwiched in-between dielectrics has been proposed for intra-chip communication in the more-than-Moore era. A sequence of numerical models has been presented to evaluate the plasmonic waveguide performance. For device-level consideration, we demonstrated through simulations that Cu (1450 nm pitch) and PLD-TiN (900 nm pitch) plasmonic waveguides symmetrically sandwiched by SiO2 with much smaller and hence denser interconnects, are promising candidates for use in global wires for the asynchronous communication. This design of plasmonic waveguide can bridge the CMOS circuitry and high-speed communication at optical frequencies within chip. For a system-level assessment, both of them have the same bandwidth throughput of ∼19.8 Gbps. The other performance parameters of Cu and PLD-TiN plasmonic waveguides are respectively, signal latency of ∼ $0.18\text{ ps} $ and $0.19\text{ ps},$ energy dissipation per computing bit of ∼ $2.5 \times {10^{ - 3}}{\rm{ fJ}}/{\rm{bit}}$ and $3.8 \times {10^{ - 3}}{\rm{ fJ}}/{\rm{bit}}$ , and 25% crosstalk coupling length of $155{\rm{ \mu m}}$ and $125{\rm{ \mu}} \text{m}$ . These findings suggest that plasmonic waveguide for intra-chip communication surpass those of existing electronic interconnects for all the categories of performance parameters.

Talking about the Management and Analysis of Intelligent Wiring in Data Center

For the application scenario of data center, the wiring management problem of data center equipment room is effectively solved through four purposes: visual wiring operation display, intelligent wiring selection construction scheme, automatic calculation of jumper length, and topology deduction of wiring link integrity. Eliminate the traditional operation and maintenance excel wiring ledger management method, eliminate the management pain points such as complicated wiring management, huge number of wiring, and inconsistent wiring ledger. In a visual way, make the wiring management intelligent, regular and efficient in a visual way. Select the start port and end port of the wiring, intelligently calculate all the connection paths of the wiring, and intelligently select the best wiring path for operation and maintenance personnel for reference. At present, the calculation method of the best path is the minimum number of device nodes. The jumper length of the route selected by the user is calculated automatically, and the wiring distance is calculated to facilitate the operation and maintenance personnel to select the suitable wiring length for construction. Support operation and maintenance personnel to quickly import construction information to generate construction orders. The intelligent wiring module supports the display and topology deduction verification of the global wiring in the equipment room, so as to check the integrity of the connection information of the upstream and downstream physical wiring of the current equipment in the form of topology, and supports the functions of hiding the distribution frame, changing the topology shape and saving. It makes the operation and maintenance personnel’s management of wiring in the equipment room simple and intuitive. The human-computer interaction mode can visually check the status of the equipment port occupation and all the device relationship sets passed by the entire wiring link.

DUPRFloor: Dynamic Modeling and Floorplanning for Partially Reconfigurable FPGAs

Nowadays, field-programmable gate array (FPGA) devices have been widely used in various fields. However, modules of circuits to be executed on FPGAs are placed within rectangular reconfigurable regions (RRs) with current floorplanners, leading to internal fragments, and lower utilization of resources. To address this, a dynamic description model of RRs and the corresponding floorplanner named dynamic union partial reconfiguration floorplan (DUPRFloor) are proposed in this article. The RR dynamic description modeling adds an anchor within a rectangular RR to reduce internal fragments. In this way, the modeling can represent both rectangular and nonrectangular shapes. Then, to find the optimal anchor, a clipping method is devised by constraining width and height of the candidate region. Finally, the mixed-integer linear programming (MILP) is used to optimize an objective function which considers the resources utilization and communication costs to obtain a desirable floorplanning result. The proposed method has been validated by simulation on three kinds of devices. And experimental results show that reconfigurable resources can be saved as much as 19.16% compared to rectangular modeling method. The DUPRFloor is also validated on the Microelectronics Center of North Carolina standard benchmark data sets. Results show that DUPRFloor can reduce 18.65% global wire length at most with almost the same execution time compared to state-of-the-art algorithms. Our approach is tested on a FPGA implemented software-defined radio (SDR) and reduced 29.41% wasted configurable frames, and to the overall design, 2% configurable frames are saved at most.

A two-step routing method with wire length budgeting for PTL routing of SFQ logic circuits

A PTL routing method for large-scale SFQ logic circuits is proposed. In this method, a routing problem is solved in two steps; global routing and detailed routing. In the global routing, a routing region is split into rectangular subregions and paths connecting them are obtained. Wire length budgeting is introduced into the global routing for allocating sufficient amount of routing resources to each net considering wire length matching in the detailed routing. In the detailed routing, exact wiring routes are determined based on a solution of the global routing and wire length matching is performed at each subregion. The global routing with wire length budgeting is formulated and an algorithm for it is proposed. In the proposed global routing algorithm, initial routes are searched at first using the rip-up and reroute technique, and then, routing resource distribution is calculated by constructing a flow-graph and solving a max-flow problem. If distribution of routing resources fails, global route extension is conducted to allocate additional routing resources to nets. The routing resource distribution and the global route extension are repeated until sufficient resources are allocated to all nets. As a design example, a 16 bit Sklansky adder was designed using the proposed method. Wire length matching in detailed routing was succeeded and the target frequency of 50 GHz was achieved.

Plasmonic interconnects for global wires in integrated circuits

Surface plasmon polaritons (SPPs) are bound electromagnetic waves propagating at a dielectric-metal interface, which have gained attention for high performance and ability for miniaturisation in high-speed dense circuits, due to their subwavelength properties. A dielectric-metal-dielectric (I-M-I) plasmonic waveguide with a 40 nm thick metal or metal-like strip on silicon substrate is proposed for intra-chip communication. The propagation characteristics of the I-M-I waveguide are investigated by numerical simulation and the modes are experimentally verified by scanning near-field optical microscopy. Metal lines as thin as 40 nm can have propagation lengths as large as 239 μm, which has small footprint compatible with the advanced interconnect process.

A scalable smart router architecture with intelligent adaptive routing and fault-tolerant management

High-radix routers that switch and route packets across large-scale racks become increasingly important and can crucially determine the latency and bandwidth of the interconnection network for super-computers and data centers. With the omnipresence of big data analysis there is a pressing need for scalable and self-diagnosing routers to construct more high-performance and reliable interconnect networks. This paper proposes an optimized aggregated-tile router micro-architecture with the reconfigurable multi-level routing and intelligent adaptive routing schemes to reduce the hardware requirement and optimize the router performance. The experiment results show that our approach achieves 98% throughput and maintains the same delay performance even better than YARC router while providing up to 40–50% reduction in memory consumption as well as global wire complexity. Moreover, by aggregating a built-in CPU and the intellectual network management structure, our router runs heuristic search algorithms to automatically reconstruct route tables for failure links or routers without any intervention of control plane, thereby implementing the automatical fault-tolerance and fault-recovery effects when maximizing the network performance.

Communication at the Speed of Light (CaSoL): A New Paradigm for Designing Global Wires

In this paper, we argue that communication at the speed of light (CaSoL) through on-chip copper interconnects is possible in the near future based on giga-scale integration (GSI) technologies. A three-step algorithm is introduced to design the optimum buffers in such systems. HSPICE simulations show that a $1.3\times $ time of flight ( ${T}_{\text {F}}$ ) is reachable in 7-nm FinFET technology. It is also shown that such a design is by nature, robust, and immune to process variations and crosstalk noise.

The basic principles of topology-dynamics relations in networks: An empirical approach

Inferring functional properties of a node from its topological role in the network is of utmost importance in many application fields. In this work, we try to give some hints on this issue focusing on the discovery of empirical topology/function rules located at different degrees of generalization going from a population of heterogeneous biological networks to a single wiring architecture.Here we report a simulation approach to this problem based on the analysis of the relationship between dissipation kinetics across the network of a perturbative stimulus applied on a single node and its topological properties. The empirical character of the study prompted us to rely on real biological networks instead of ‘ideal architectures’ and to adopt a statistical attitude with a relatively low number of affected nodes for each network that is much more realistic in real-world biological applications. The analysis allowed us to recognize some general topology-dynamics correlation rules variously modulated by global wiring architecture.

Capacitively Driven Global Interconnect With Energy-Efficient Receiver Based on Magneto-Electric Switching

We model a capacitively driven, low-swing, global interconnect circuit based on a receiver that utilizes magnetization switching induced by the magneto-electric (ME) effect. Capacitively driven wire was recently shown to be effective in improving the performance of global interconnects. Such techniques can reduce the signal swing in the interconnect with the use of a capacitive divider network, which does not require an additional voltage supply. However, the large reduction in signal swing makes it necessary to use differential signaling and amplification for successful regeneration at the receiver, which add wire area and require static power. The ME effect has been shown to reverse the magnetization of a nanomagnet by applying a low voltage to an adjacent multiferroic oxide. Here, we propose a receiver based on the ME effect that uses the low voltage at the receiving end of the global wire to switch a nanomagnet. The nanomagnet is also used as the free layer of a magnetic tunnel junction (MTJ), the resistance of which is tuned through the ME effect. This change in MTJ resistance is converted to full-swing binary signals with simple digital components. This process allows capacitive, low-swing interconnection without differential signaling or amplification, which leads to significant energy efficiency. Our simulation results indicate that for 5–10 mm long global wires in IBM 45 nm technology, the capacitive ME design consumes one third the energy of a full-swing complementary metal-oxide semiconductor (CMOS) design and one half the energy of a differential amplifier low-swing capacitive CMOS design.

Performance Analysis of Nanoelectromechanical Relay-Based Field-Programmable Gate Arrays

The energy consumption of field-programmable gate arrays (FPGA) is dominated by leakage currents and dynamic energy associated with programmable interconnect. An FPGA built entirely from nanoelectromechanical (NEM) relays can effectively eliminate leakage energy losses, reduce the interconnect dynamic energy, operate at temperatures >225 °C and tolerate radiation doses in excess of 100 Mrad, while hybrid FPGAs comprising both complementary metal-oxide-semiconductor (CMOS) transistors and NEM relays (NEM-CMOS) have the potential to realize improvements in performance and energy efficiency. Large-scale integration of NEM relays, however, poses a significant engineering challenge due to the presence of moving parts. We discuss the design of FPGAs utilizing NEM relays based on a heterogeneous 3-D integration scheme, and carry out a scaling study to quantify key metrics related to performance and energy efficiency in both NEM-only and NEM-CMOS FPGAs. We show how the integration scheme has a profound effect on these metrics by changing the length of global wires. The scaling regime beyond which net performance and energy benefits is seen in NEM-CMOS over a baseline 90 nm CMOS technology is defined by an effective relay beam length of 0.5 $\mu \text{m}$ , on-resistance of 200 $\text{k}\Omega$ , and a via pitch of 0.4 $\mu \text{m}$ , all achievable with existing process technology. For ultra-low energy applications that are not performance critical, NEM-only FPGAs can provide close to $15\times$ improvement in energy efficiency.

Low power NoC architecture based dynamic reconfigurable system

The on chip communication intention is difficult due to communication necessities and the difficulty of the objective application is great. Notably, different communication areas might be actualized utilizing a similar chip range, for example, to enable various parallel applications to be stacked onto the device. So the system on chip (SoC) deployed in different topologies with different design parameters to achieve the requirements of the target application. Classical communication methods such as point to point, the bus is not an appropriate solution for future SoCs. That is difficult to send signals starting with one end then onto the next term of a clock cycle. Issues, for example, global wire delay and global synchronization will restrict us. With a specific end goal to beat these problems, architect utilizes new models, procedures, and tools from network design field and apply them to SoCs plan that prompts modern worldview called network on a chip. In this paper, the design components used and the operation of the proposed architecture is same with network on chip (NoC) approach. But it differs in the communication architecture with the introduction of the on-chip peripheral bus. And it differs from the NoC by its switching networks. We modified the switching system that is developed to support dynamically reconfigurable network. Due to this modification in the switching system restrict the area and the power use of the NoC.