108 research outputs found
A Scalable & Energy Efficient Graphene-Based Interconnection Framework for Intra and Inter-Chip Wireless Communication in Terahertz Band
Network-on-Chips (NoCs) have emerged as a communication infrastructure for the multi-core System-on-Chips (SoCs). Despite its advantages, due to the multi-hop communication over the metal interconnects, traditional Mesh based NoC architectures are not scalable in terms of performance and energy consumption. Folded architectures such as Torus and Folded Torus were proposed to improve the performance of NoCs while retaining the regular tile-based structure for ease of manufacturing. Ultra-low-latency and low-power express channels between communicating cores have also been proposed to improve the performance of conventional NoCs. However, the performance gain of these approaches is limited due to metal/dielectric based interconnection.
Many emerging interconnect technologies such as 3D integration, photonic, Radio Frequency (RF), and wireless interconnects have been envisioned to alleviate the issues of a metal/dielectric interconnect system. However, photonic and RF interconnects need the additional physically overlaid optical waveguides or micro-strip transmission lines to enable data transmission across the NoC. Several on-chip antennas have shown to improve energy efficiency and bandwidth of on-chip data communications. However, the date rates of the mm-wave wireless channels are limited by the state-of-the-art power-efficient transceiver design. Recent research has brought to light novel graphene based antennas operating at THz frequencies. Due to the higher operating frequencies compared to mm-wave transceivers, the data rate that can be supported by these antennas are significantly higher. Higher operating frequencies imply that graphene based antennas are just hundred micrometers in size compared to dimensions in the range of a millimeter of mm-wave antennas. Such reduced dimensions are suitable for integration of several such transceivers in a single NoC for relatively low overheads.
In this work, to exploit the benefits of a regular NoC structure in conjunction with emerging Graphene-based wireless interconnect. We propose a toroidal folding based NoC architecture. The novelty of this folding based approach is that we are using low power, high bandwidth, single hop direct point to point wireless links instead of multihop communication that happens through metallic wires. We also propose a novel phased based communication protocol through which multiple wireless links can be made active at a time without having any interference among the transceiver. This offers huge gain in terms of performance as compared to token based mechanism where only a single wireless link can be made active at a time. We also propose to extend Graphene-based wireless links to enable energy-efficient, phase-based chip-to-chip communication to create a seamless, wireless interconnection fabric for multichip systems as well. Through cycle-accurate system-level simulations, we demonstrate that such designs with torus like folding based on THz links instead of global wires along with the proposed phase based multichip systems. We provide estimates that they are able to provide significant gains (about 3 to 4 times better in terms of achievable bandwidth, packet latency and average packet energy when compared to wired system) in performance and energy efficiency in data transfer in a NoC as well as multichip system. Thus, realization of these kind of interconnection framework that could support high data rate links in Tera-bits-per-second that will alleviate the capacity limitations of current interconnection framework
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Heterogeneous Integration on Silicon-Interconnect Fabric using fine-pitch interconnects (≤10 �m)
Today, the ever-growing data-bandwidth demand is pushing the boundaries of the traditional printed circuit board (PCB) based integration schemes. Moreover, with the apparent saturation of semiconductor scaling, commonly called Moore's law, system scaling warrants a paradigm shift in packaging technologies, assembly techniques, and integration methodologies. In this work, a superior alternative to PCBs called the Silicon-Interconnect Fabric (Si-IF) is investigated. The Si-IF is a silicon-based, package-less, fine-pitch, highly scalable, heterogeneous integration platform for wafer-scale systems. In this technology, unpackaged dielets are assembled on the Si-IF at small inter-dielet spacings (≤100 �m) using fine-pitch (≤10 �m) die-to-substrate interconnects. A novel assembly process using a solder-less direct metal-metal (gold-gold and copper-copper) thermal compression bonding was developed. Using this process, sub-10 �m pitch interconnects with a low specific contact resistance of ≤0.7 Ω-�m2 were successfully demonstrated. Because of the tightly packed Si-IF assembly, the communication links between the neighboring dies are short (≤500 �m) with low loss (≤2 dB), comparable to on-chip connections. Consequently, simple buffers can transfer data between dies using a Simple Universal Parallel intERface for chips (SuperCHIPS) at low latency (<30 ps), low energy per bit (≤0.03 pJ/b), and high data-rates (up to 10 Gbps/link), corresponding to an aggregate bandwidth up to 8 Tbps/mm. The benefits of the SuperCHIPS protocol were experimentally demonstrated to provide 5-90X higher data-bandwidth, 8-30X lower latency, and 5-40X lower energy per bit compared to existing integration schemes. This dissertation addresses the assembly technology and communication protocols of the Si-IF technology
Architecting a One-to-many Traffic-Aware and Secure Millimeter-Wave Wireless Network-in-Package Interconnect for Multichip Systems
With the aggressive scaling of device geometries, the yield of complex Multi Core Single Chip(MCSC) systems with many cores will decrease due to the higher probability of manufacturing defects especially, in dies with a large area. Disintegration of large System-on-Chips(SoCs) into smaller chips called chiplets has shown to improve the yield and cost of complex systems. Therefore, platform-based computing modules such as embedded systems and micro-servers have already adopted Multi Core Multi Chip (MCMC) architectures overMCSC architectures. Due to the scaling of memory intensive parallel applications in such systems, data is more likely to be shared among various cores residing in different chips resulting in a significant increase in chip-to-chip traffic, especially one-to-many traffic. This one-to-many traffic is originated mainly to maintain cache-coherence between many cores residing in multiple chips. Besides, one-to-many traffics are also exploited by many parallel programming models, system-level synchronization mechanisms, and control signals. How-ever, state-of-the-art Network-on-Chip (NoC)-based wired interconnection architectures do not provide enough support as they handle such one-to-many traffic as multiple unicast trafficusing a multi-hop MCMC communication fabric. As a result, even a small portion of such one-to-many traffic can significantly reduce system performance as traditional NoC-basedinterconnect cannot mask the high latency and energy consumption caused by chip-to-chipwired I/Os. Moreover, with the increase in memory intensive applications and scaling of MCMC systems, traditional NoC-based wired interconnects fail to provide a scalable inter-connection solution required to support the increased cache-coherence and synchronization generated one-to-many traffic in future MCMC-based High-Performance Computing (HPC) nodes. Therefore, these computation and memory intensive MCMC systems need an energy-efficient, low latency, and scalable one-to-many (broadcast/multicast) traffic-aware interconnection infrastructure to ensure high-performance.
Research in recent years has shown that Wireless Network-in-Package (WiNiP) architectures with CMOS compatible Millimeter-Wave (mm-wave) transceivers can provide a scalable, low latency, and energy-efficient interconnect solution for on and off-chip communication. In this dissertation, a one-to-many traffic-aware WiNiP interconnection architecture with a starvation-free hybrid Medium Access Control (MAC), an asymmetric topology, and a novel flow control has been proposed. The different components of the proposed architecture are individually one-to-many traffic-aware and as a system, they collaborate with each other to provide required support for one-to-many traffic communication in a MCMC environment. It has been shown that such interconnection architecture can reduce energy consumption and average packet latency by 46.96% and 47.08% respectively for MCMC systems.
Despite providing performance enhancements, wireless channel, being an unguided medium, is vulnerable to various security attacks such as jamming induced Denial-of-Service (DoS), eavesdropping, and spoofing. Further, to minimize the time-to-market and design costs, modern SoCs often use Third Party IPs (3PIPs) from untrusted organizations. An adversary either at the foundry or at the 3PIP design house can introduce a malicious circuitry, to jeopardize an SoC. Such malicious circuitry is known as a Hardware Trojan (HT). An HTplanted in the WiNiP from a vulnerable design or manufacturing process can compromise a Wireless Interface (WI) to enable illegitimate transmission through the infected WI resulting in a potential DoS attack for other WIs in the MCMC system. Moreover, HTs can be used for various other malicious purposes, including battery exhaustion, functionality subversion, and information leakage. This information when leaked to a malicious external attackercan reveals important information regarding the application suites running on the system, thereby compromising the user profile. To address persistent jamming-based DoS attack in WiNiP, in this dissertation, a secure WiNiP interconnection architecture for MCMC systems has been proposed that re-uses the one-to-many traffic-aware MAC and existing Design for Testability (DFT) hardware along with Machine Learning (ML) approach. Furthermore, a novel Simulated Annealing (SA)-based routing obfuscation mechanism was also proposed toprotect against an HT-assisted novel traffic analysis attack. Simulation results show that,the ML classifiers can achieve an accuracy of 99.87% for DoS attack detection while SA-basedrouting obfuscation could reduce application detection accuracy to only 15% for HT-assistedtraffic analysis attack and hence, secure the WiNiP fabric from age-old and emerging attacks
Interconnects for DNA, quantum, in-memory and optical computing: insights from a panel discussion
The computing world is witnessing a proverbial Cambrian explosion of emerging paradigms propelled by applications such as Artificial Intelligence, Big Data, and Cybersecurity. The recent advances in technology to store digital data inside a DNA strand, manipulate quantum bits (qubits), perform logical operations with photons, and perform computations inside memory systems are ushering in the era of emerging paradigms of DNA computing, quantum computing, optical computing, and in-memory computing. In an orthogonal direction, research on interconnect design using advanced electro-optic, wireless, and microfluidic technologies has shown promising solutions to the architectural limitations of traditional von-Neumann computers. In this article, experts present their comments on the role of interconnects in the emerging computing paradigms and discuss the potential use of chiplet-based architectures for the heterogeneous integration of such technologies.This work was supported in part by the US NSF CAREER Grant CNS-1553264 and EU H2020 research and innovation programme under Grant 863337.Peer ReviewedPostprint (author's final draft
Towards Cache-Coherent Chiplet-Based Architectures with Wireless Interconnects
Cache-coherent chiplet-based architectures have gained significant attention due to their potential for scalability and improved performance in modern computing systems. However, the interconnects in such architectures often pose challenges in maintaining cache coherence across chiplets, leading to increased latency and energy consumption. This thesis focuses on exploring the feasibility and advantages of integrating wireless interconnects into cache-coherent chiplet-based architectures. Through extensive simulations of 16 and 64 core systems segmented in 4 and 8 chiplet systems with multiple inter-chiplet latencies we debug and obtain traffic data. By studying the inter-chiplet traffic for different chiplet-based configurations and analyzing it in terms of spatial, temporal and time variance we derive that chiplet scaling degrades performance. Further we formulate the impact of hybrid wired and wireless interconnects and assess the potential performance benefits they offer. The findings from this research will contribute to the design and optimization of cache-coherent chiplet-based architectures, shedding light on the practicality and advantages of utilizing wireless interconnects in future computing systems
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Cross-Layer Pathfinding for Off-Chip Interconnects
Off-chip interconnects for integrated circuits (ICs) today induce a diverse design space, spanning many different applications that require transmission of data at various bandwidths, latencies and link lengths. Off-chip interconnect design solutions are also variously sensitive to system performance, power and cost metrics, while also having a strong impact on these metrics. The costs associated with off-chip interconnects include die area, package (PKG) and printed circuit board (PCB) area, technology and bill of materials (BOM). Choices made regarding off-chip interconnects are fundamental to product definition, architecture, design implementation and technology enablement. Given their cross-layer impact, it is imperative that a cross-layer approach be employed to architect and analyze off-chip interconnects up front, so that a top-down design flow can comprehend the cross-layer impacts and correctly assess the system performance, power and cost tradeoffs for off-chip interconnects. Chip architects are not exposed to all the tradeoffs at the physical and circuit implementation or technology layers, and often lack the tools to accurately assess off-chip interconnects. Furthermore, the collaterals needed for a detailed analysis are often lacking when the chip is architected; these include circuit design and layout, PKG and PCB layout, and physical floorplan and implementation. To address the need for a framework that enables architects to assess the system-level impact of off-chip interconnects, this thesis presents power-area-timing (PAT) models for off-chip interconnects, optimization and planning tools with the appropriate abstraction using these PAT models, and die/PKG/PCB co-design methods that help expose the off-chip interconnect cross-layer metrics to the die/PKG/PCB design flows. Together, these models, tools and methods enable cross-layer optimization that allows for a top-down definition and exploration of the design space and helps converge on the correct off-chip interconnect implementation and technology choice. The tools presented cover off-chip memory interfaces for mobile and server products, silicon photonic interfaces, 2.5D silicon interposers and 3D through-silicon vias (TSVs). The goal of the cross-layer framework is to assess the key metrics of the interconnect (such as timing, latency, active/idle/sleep power, and area/cost) at an appropriate level of abstraction by being able to do this across layers of the design flow. In additional to signal interconnect, this thesis also explores the need for such cross-layer pathfinding for power distribution networks (PDN), where the system-on-chip (SoC) floorplan and pinmap must be optimized before the collateral layouts for PDN analysis are ready. Altogether, the developed cross-layer pathfinding methodology for off-chip interconnects enables more rapid and thorough exploration of a vast design space of off-chip parallel and serial links, inter-die and inter-chiplet links and silicon photonics. Such exploration will pave the way for off-chip interconnect technology enablement that is optimized for system needs. The basis of the framework can be extended to cover other interconnect technology as well, since it fundamentally relates to system-level metrics that are common to all off-chip interconnects
Massive Data-Centric Parallelism in the Chiplet Era
Traditionally, massively parallel applications are executed on distributed
systems, where computing nodes are distant enough that the parallelization
schemes must minimize communication and synchronization to achieve scalability.
Mapping communication-intensive workloads to distributed systems requires
complicated problem partitioning and dataset pre-processing. With the current
AI-driven trend of having thousands of interconnected processors per chip,
there is an opportunity to re-think these communication-bottlenecked workloads.
This bottleneck often arises from data structure traversals, which cause
irregular memory accesses and poor cache locality.
Recent works have introduced task-based parallelization schemes to accelerate
graph traversal and other sparse workloads. Data structure traversals are split
into tasks and pipelined across processing units (PUs). Dalorex demonstrated
the highest scalability (up to thousands of PUs on a single chip) by having the
entire dataset on-chip, scattered across PUs, and executing the tasks at the PU
where the data is local. However, it also raised questions on how to scale to
larger datasets when all the memory is on chip, and at what cost.
To address these challenges, we propose a scalable architecture composed of a
grid of Data-Centric Reconfigurable Array (DCRA) chiplets. Package-time
reconfiguration enables creating chip products that optimize for different
target metrics, such as time-to-solution, energy, or cost, while software
reconfigurations avoid network saturation when scaling to millions of PUs
across many chip packages. We evaluate six applications and four datasets, with
several configurations and memory technologies, to provide a detailed analysis
of the performance, power, and cost of data-local execution at scale. Our
parallelization of Breadth-First-Search with RMAT-26 across a million PUs
reaches 3323 GTEPS
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