Antonio Pullini

Design Issues and Considerations for Low-Cost 3-D TSV IC Technology

In this paper key design issues and considerations of a low-cost 3-D Cu-TSV technology are investigated. The impact of TSV on BEOL interconnect reliability is limited, no failures have been observed. The impact of TSV stress on MOS devices causes shifts, further analysis is required to understand their importance. Thermal hot spots in 3-D chip stacks cause temperature increases three times higher than in 2-D chips, necessitating a careful thermal floorplanning to avoid thermal failures. We have monitored for ESD during 3-D processing and have found no events take place, however careful further monitoring is required. The noise coupling between two tiers in a 3-D chip-stack is 20 dB lower than in a 2-D SoC, opening opportunities for increased mixed signal system performance. The impact on digital circuit performance of TSVs is accurately modeled with the presented RC model and digital gates can directly drive signals through TSVs at high speed and low power. Experimental results of a 3-D Network-on-Chip implementation demonstrate that the NoC concept can be extended from 2-D SoC to 3-D SoCs at low area (0.018 ) and power (3%) overhead.

Invited paper: Network-on-Chip design and synthesis outlook

With the growing complexity in consumer embedded products, new tendencies forecast heterogeneous Multi-Processor Systems-On-Chip (MPSoCs) consisting of complex integrated components communicating with each other at very high-speed rates. Intercommunication requirements of MPSoCs made of hundreds of cores will not be feasible using a single shared bus or a hierarchy of buses due to their poor scalability with system size, their shared bandwidth between all the attached cores and the energy efficiency requirements of final products. To overcome these problems of scalability and complexity, Networks-On-Chip (NoCs) have been proposed as a promising replacement to eliminate many of the overheads of buses and MPSoCs connected by means of general-purpose communication architectures. However, the development of application-specific NoCs for MPSoCs is a complex engineering process that involves the definition of suitable protocols and topologies of switches, and which demands adequate design flows to minimize design time and effort. In fact, the development of suitable high-level design and synthesis tools for NoC-based interconnects is a key element to benefit from NoC-based interconnect design in nanometer-scale CMOS technologies. In this article we overview the benefits of state-of-the-art NoCs using a complete NoC synthesis flow, and a detailed scalability analysis of different NoC implementations for the latest nanometer-scale technology nodes. We present NoC-based solutions for the on-chip interconnects of MPSoCs that illustrate the benefits of competitive application-specific NoCs with respect to more regular NoC topologies regarding performance, area and power. Moreover, we show that it is currently feasible to synthesize in an automatic way a complete custom NoC interconnect from a high-level specification in few hours. Finally, we summarize future research challenges in the area of NoC interconnect design automation.

Fault tolerance overhead in network-on-chip flow control schemes

Flow control mechanisms in network-on-chip (NoC) architectures are critical for fast packet propagation across the network and for low idling of network resources. Buffer management and allocation are fundamental tasks of each flow control scheme. Buffered flow control is the focus of this work. We consider alternative schemes (STALL/GO, T-Error, ACK/NACK) for buffer and channel bandwidth allocation in presence of pipelined switch-to-switch links. These protocols provide varying degrees of fault tolerance support, resulting in different area and power tradeoffs. Our analysis is aimed at determining the overhead of such support when running in error-free environments, which are the typical operating mode. Implementation in the timespipes NoC architecture and functional simulation by means of a virtual platform allowed us to capture application perceived performance, thus providing guidelines for NoC designers

Bringing NoCs to 65nm

Very deep submicron process technologies are ideal application fields for NoCs, which offer a promising solution to the scalability problem. This article sheds light on the benefits and challenges of Noc-Based interconnect design in nanometer CMOS. The author present experimental results from fully working 65-NM Noc Designs and a detailed scalability analysis.

NoC Design and Implementation in 65nm Technology

As embedded computing evolves towards ever more powerful architectures, the challenge of properly interconnecting large numbers of on-chip computation blocks is becoming prominent. Networks-on-chip (NoCs) have been proposed as a scalable solution to both physical design issues and increasing bandwidth demands. However, this claim has not been fully validated yet, since the design properties and tradeoffs of NoCs have not been studied in detail below the 100 nm threshold. This work is aimed at shedding light on the opportunities and challenges, both expected and unexpected, of NoC design in nanometer CMOS. We present fully working 65 nm NoC designs, a complete NoC synthesis flow and detailed scalability analysis

Networks on Chips: from research to products

Research on Networks on Chips (NoCs) has spanned over a decade and its results are now visible in some products. Thus the seminal idea of using networking technology to address the chip-level interconnect problem has been shown to be correct. Moreover, as technology scales down in geometry and chips scale up in complexity, NoCs become the essential element to achieve the desired levels of performance and quality of service while curbing power consumption levels. Design and timing closure can only be achieved by a sophisticated set of tools that address NoC synthesis, optimization and validation.

Bringing NoCs to 65 nm

Very deep submicron process technologies are ideal application fields for NoCs, which offer a promising solution to the scalability problem. This article sheds light on the benefits and challenges of NoC-based interconnect design in nanometer CMOS. The experimental results from fully working 65-nm NoC designs and a detailed scalability analysis are presented. The network on chip (NoC) is a promising solution to the scalability problem. NoCs build upon improvements in bus architecture-for example, in terms of topology design.

Timing-driven row-based power gating

In this paper we focus on leakage reduction through automatic insertion of sleep transistors using a row-based granularity. In particular, we tackle here the two main issues involved in this methodology: (i) Clustering and (ii) the interfacing of power-gated and non power-gated regions within the same block. The clustering algorithm automatically selects an optimal subset of rows that can be power-gated with a tightly controlled delay overhead. We then address the issue of interfacing different gated regions and propose a novel technique to address this issue with minimal area and power penalty. Our approach is compatible with state-of-the art logic and physical synthesis flows and it does not significantly impact design closure. We achieve leakage power reductions as high as 89% for a set of standard benchmarks, with minimum timing and area overhead.

Design of compact imperfection-immune CNFET layouts for standard-cell-based logic synthesis

The quest for technologies with superior device characteristics has showcased carbon nanotube field effect transistors (CNFETs) into limelight. Among the several design aspects necessary for todays grail in CNFET technology, achieving functional immunity to carbon nanotube (CNT) manufacturing issues (such as mispositioned CNTs and metallic CNTs) is of paramount importance. In this work we present a new design technique to build compact layouts while ensuring 100% functional immunity to mispositioned CNTs. Then, as second contribution of this work, we have developed a CNFET design kit (DK) to realize a complete design flow from logic-to-GDSII traversing the conventional CMOS design flow. This flow enables a framework that allows accurate comparison between CMOS and CNFET-based circuits. This paper also presents simulation results to illustrate such analysis, namely, a CNFET-based inverter can achieve gains, with respect to the energy-delay product (EDP) metric, of more than 4times in delay, 2times in energy/cycle and significant area savings (more than 30%) when compared to a corresponding CMOS inverter benchmarked with an industrial 65 nm technology.

An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

Near-sensor data analytics is a promising direction for internet-of-things endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns, as valuable data are stored or sent over the network at various stages of the analytics pipeline. Using encryption to protect sensitive data at the boundary of the on-chip analytics engine is a way to address data security issues. To cope with the combined workload of analytics and encryption in a tight power envelope, we propose Fulmine, a system-on-chip (SoC) based on a tightly-coupled multi-core cluster augmented with specialized blocks for compute-intensive data processing and encryption functions, supporting software programmability for regular computing tasks. The Fulmine SoC, fabricated in 65-nm technology, consumes less than 20mW on average at 0.8V achieving an efficiency of up to 70pJ/B in encryption, 50pJ/px in convolution, or up to 25MIPS/mW in software. As a strong argument for real-life flexible application of our platform, we show experimental results for three secure analytics use cases: secure autonomous aerial surveillance with a state-of-the-art deep convolutional neural network (CNN) consuming 3.16pJ per equivalent reduced instruction set computer operation, local CNN-based face detection with secured remote recognition in 5.74pJ/op, and seizure detection with encrypted data collection from electroencephalogram within 12.7pJ/op.