TAG: Learning Circuit Spatial Embedding From Layouts

Analog and mixed-signal (AMS) circuit designs still rely on human design expertise. Machine learning has been assisting circuit design automation by replacing human experience with artificial intelligence. This paper presents TAG, a new paradigm of learning the circuit representation from layouts leveraging text, self-attention and graph. The embedding network model learns spatial information without manual labeling. We introduce text embedding and a self-attention mechanism to AMS circuit learning. Experimental results demonstrate the ability to predict layout distances between instances with industrial FinFET technology benchmarks. The effectiveness of the circuit representation is verified by showing the transferability to three other learning tasks with limited data in the case studies: layout matching prediction, wirelength estimation, and net parasitic capacitance prediction.Comment: Accepted by ICCAD 202

Algorithmic techniques for physical design : macro placement and under-the-cell routing

With the increase of chip component density and new manufacturability constraints imposed by modern technology nodes, the role of algorithms for electronic design automation is key to the successful implementation of integrated circuits. Two of the critical steps in the physical design flows are macro placement and ensuring all design rules are honored after timing closure. This thesis proposes contributions to help in these stages, easing time-consuming manual steps and helping physical design engineers to obtain better layouts in reduced turnaround time. The first contribution is under-the-cell routing, a proposal to systematically connect standard cell components via lateral pins in the lower metal layers. The aim is to reduce congestion in the upper metal layers caused by extra metal and vias, decreasing the number of design rule violations. To allow cells to connect by abutment, a standard cell library is enriched with instances containing lateral pins in a pre-selected sharing track. Algorithms are proposed to maximize the numbers of connections via lateral connection by mapping placed cell instances to layouts with lateral pins, and proposing local placement modifications to increase the opportunities for such connections. Experimental results show a significant decrease in the number of pins, vias, and in number of design rule violations, with negligible impact on wirelength and timing. The second contribution, done in collaboration with eSilicon (a leading ASIC design company), is the creation of HiDaP, a macro placement tool for modern industrial designs. The proposed approach follows a multilevel scheme to floorplan hierarchical blocks, composed of macros and standard cells. By exploiting RTL information available in the netlist, the dataflow affinity between these blocks is modeled and minimized to find a macro placement with good wirelength and timing properties. The approach is further extended to allow additional engineer input, such as preferred macro locations, and also spectral and force methods to guide the floorplanning search. Experimental results show that the layouts generated by HiDaP outperforms those obtained by a state-of-the-art EDA physical design software, with similar wirelength and better timing when compared to manually designed tape-out ready macro placements. Layouts obtained by HiDaP have successfully been brought to near timing closure with one to two rounds of small modifications by physical design engineers. HiDaP has been fully integrated in the design flows of the company and its development remains an ongoing effort.A causa de l'increment de la densitat de components en els xip i les noves restriccions de disseny imposades pels últims nodes de fabricació, el rol de l'algorísmia en l'automatització del disseny electrònic ha esdevingut clau per poder implementar circuits integrats. Dos dels passos crucials en el procés de disseny físic és el placement de macros i assegurar la correcció de les regles de disseny un cop les restriccions de timing del circuit són satisfetes. Aquesta tesi proposa contribucions per ajudar en aquests dos reptes, facilitant laboriosos passos manuals en el procés i ajudant als enginyers de disseny físic a obtenir millors resultats en menys temps. La primera contribució és el routing "under-the-cell", una proposta per connectar cel·les estàndard usant pins laterals en les capes de metall inferior de manera sistemàtica. L'objectiu és reduir la congestió en les capes de metall superior causades per l'ús de metall i vies, i així disminuir el nombre de violacions de regles de disseny. Per permetre la connexió lateral de cel·les, estenem una llibreria de cel·les estàndard amb dissenys que incorporen connexions laterals. També proposem modificacions locals al placement per permetre explotar aquest tipus de connexions més sovint. Els resultats experimentals mostren una reducció significativa en el nombre de pins, vies i nombre de violacions de regles de disseny, amb un impacte negligible en wirelength i timing. La segona contribució, desenvolupada en col·laboració amb eSilicon (una empresa capdavantera en disseny ASIC), és el desenvolupament de HiDaP, una eina de macro placement per a dissenys industrials actuals. La proposta segueix un procés multinivell per fer el floorplan de blocks jeràrquics, formats per macros i cel·les estàndard. Mitjançant la informació RTL disponible en la netlist, l'afinitat de dataflow entre els mòduls es modela i minimitza per trobar macro placements amb bones propietats de wirelength i timing. La proposta també incorpora la possibilitat de rebre input addicional de l'enginyer, com ara suggeriments de les posicions de les macros. Finalment, també usa mètodes espectrals i de forçes per guiar la cerca de floorplans. Els resultats experimentals mostren que els dissenys generats amb HiDaP són millors que els obtinguts per eines comercials capdavanteres de EDA. Els resultats també mostren que els dissenys presentats poden obtenir un wirelength similar i millor timing que macro placements obtinguts manualment, usats per fabricació. Alguns dissenys obtinguts per HiDaP s'han dut fins a timing-closure en una o dues rondes de modificacions incrementals per part d'enginyers de disseny físic. L'eina s'ha integrat en el procés de disseny de eSilicon i el seu desenvolupament continua més enllà de les aportacions a aquesta tesi.Postprint (published version

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

Algorithmic techniques for physical design : macro placement and under-the-cell routing

With the increase of chip component density and new manufacturability constraints imposed by modern technology nodes, the role of algorithms for electronic design automation is key to the successful implementation of integrated circuits. Two of the critical steps in the physical design flows are macro placement and ensuring all design rules are honored after timing closure. This thesis proposes contributions to help in these stages, easing time-consuming manual steps and helping physical design engineers to obtain better layouts in reduced turnaround time. The first contribution is under-the-cell routing, a proposal to systematically connect standard cell components via lateral pins in the lower metal layers. The aim is to reduce congestion in the upper metal layers caused by extra metal and vias, decreasing the number of design rule violations. To allow cells to connect by abutment, a standard cell library is enriched with instances containing lateral pins in a pre-selected sharing track. Algorithms are proposed to maximize the numbers of connections via lateral connection by mapping placed cell instances to layouts with lateral pins, and proposing local placement modifications to increase the opportunities for such connections. Experimental results show a significant decrease in the number of pins, vias, and in number of design rule violations, with negligible impact on wirelength and timing. The second contribution, done in collaboration with eSilicon (a leading ASIC design company), is the creation of HiDaP, a macro placement tool for modern industrial designs. The proposed approach follows a multilevel scheme to floorplan hierarchical blocks, composed of macros and standard cells. By exploiting RTL information available in the netlist, the dataflow affinity between these blocks is modeled and minimized to find a macro placement with good wirelength and timing properties. The approach is further extended to allow additional engineer input, such as preferred macro locations, and also spectral and force methods to guide the floorplanning search. Experimental results show that the layouts generated by HiDaP outperforms those obtained by a state-of-the-art EDA physical design software, with similar wirelength and better timing when compared to manually designed tape-out ready macro placements. Layouts obtained by HiDaP have successfully been brought to near timing closure with one to two rounds of small modifications by physical design engineers. HiDaP has been fully integrated in the design flows of the company and its development remains an ongoing effort.A causa de l'increment de la densitat de components en els xip i les noves restriccions de disseny imposades pels últims nodes de fabricació, el rol de l'algorísmia en l'automatització del disseny electrònic ha esdevingut clau per poder implementar circuits integrats. Dos dels passos crucials en el procés de disseny físic és el placement de macros i assegurar la correcció de les regles de disseny un cop les restriccions de timing del circuit són satisfetes. Aquesta tesi proposa contribucions per ajudar en aquests dos reptes, facilitant laboriosos passos manuals en el procés i ajudant als enginyers de disseny físic a obtenir millors resultats en menys temps. La primera contribució és el routing "under-the-cell", una proposta per connectar cel·les estàndard usant pins laterals en les capes de metall inferior de manera sistemàtica. L'objectiu és reduir la congestió en les capes de metall superior causades per l'ús de metall i vies, i així disminuir el nombre de violacions de regles de disseny. Per permetre la connexió lateral de cel·les, estenem una llibreria de cel·les estàndard amb dissenys que incorporen connexions laterals. També proposem modificacions locals al placement per permetre explotar aquest tipus de connexions més sovint. Els resultats experimentals mostren una reducció significativa en el nombre de pins, vies i nombre de violacions de regles de disseny, amb un impacte negligible en wirelength i timing. La segona contribució, desenvolupada en col·laboració amb eSilicon (una empresa capdavantera en disseny ASIC), és el desenvolupament de HiDaP, una eina de macro placement per a dissenys industrials actuals. La proposta segueix un procés multinivell per fer el floorplan de blocks jeràrquics, formats per macros i cel·les estàndard. Mitjançant la informació RTL disponible en la netlist, l'afinitat de dataflow entre els mòduls es modela i minimitza per trobar macro placements amb bones propietats de wirelength i timing. La proposta també incorpora la possibilitat de rebre input addicional de l'enginyer, com ara suggeriments de les posicions de les macros. Finalment, també usa mètodes espectrals i de forçes per guiar la cerca de floorplans. Els resultats experimentals mostren que els dissenys generats amb HiDaP són millors que els obtinguts per eines comercials capdavanteres de EDA. Els resultats també mostren que els dissenys presentats poden obtenir un wirelength similar i millor timing que macro placements obtinguts manualment, usats per fabricació. Alguns dissenys obtinguts per HiDaP s'han dut fins a timing-closure en una o dues rondes de modificacions incrementals per part d'enginyers de disseny físic. L'eina s'ha integrat en el procés de disseny de eSilicon i el seu desenvolupament continua més enllà de les aportacions a aquesta tesi

An integrated placement and routing approach

As the feature size continues scaling down, interconnects become the major contributor of signal delay. Since interconnects are mainly determined by placement and routing, these two stages play key roles to achieve high performance. Historically, they are divided into two separate stages to make the problem tractable. Therefore, the routing information is not available during the placement process. Net models such as HPWL, are employed to approximate the routing to simplify the placement problem. However, the good placement in terms of these objectives may not be routable at all in the routing stage because different objectives are optimized in placement and routing stages. This inconsistancy makes the results obtained by the two-step optimization method far from optimal;In order to achieve high-quality placement solution and ensure the following routing, we propose an integrated placement and routing approach. In this approach, we integrate placement and routing into the same framework so that the objective optimized in placement is the same as that in routing. Since both placement and routing are very hard problems (NP-hard), we need to have very efficient algorithms so that integrating them together will not lead to intractable complexity;In this dissertation, we first develop a highly efficient placer - FastPlace 3.0 for large-scale mixed-size placement problem. Then, an efficient and effective detailed placer - FastDP is proposed to improve global placement by moving standard cells in designs. For high-degree nets in designs, we propose a novel performance-driven topology design algorithm to generate good topologies to achieve very strict timing requirement. In the routing phase, we develop two global routers, FastRoute and FastRoute 2.0. Compared to traditional global routers, they can generate better solutions and are two orders of magnitude faster. Finally, based on these efficient and high-quality placement and routing algorithms, we propose a new flow which integrates placement and routing together closely. In this flow, global routing is extensively applied to obtain the interconnect information and direct the placement process. In this way, we can get very good placement solutions with guaranteed routability

Towards Machine Learning-Based FPGA Backend Flow: Challenges and Opportunities

Field-Programmable Gate Array (FPGA) is at the core of System on Chip (SoC) design across various Industry 5.0 digital systems—healthcare devices, farming equipment, autonomous vehicles and aerospace gear to name a few. Given that pre-silicon verification using Computer Aided Design (CAD) accounts for about 70% of the time and money spent on the design of modern digital systems, this paper summarizes the machine learning (ML)-oriented efforts in different FPGA CAD design steps. With the recent breakthrough of machine learning, FPGA CAD tasks—high-level synthesis (HLS), logic synthesis, placement and routing—are seeing a renewed interest in their respective decision-making steps. We focus on machine learning-based CAD tasks to suggest some pertinent research areas requiring more focus in CAD design. The development of open-source benchmarks optimized for an end-to-end machine learning experience, intra-FPGA optimization, domain-specific accelerators, lack of explainability and federated learning are the issues reviewed to identify important research spots requiring significant focus. The potential of the new cloud-based architectures to understand the application of the right ML algorithms in FPGA CAD decision-making steps is discussed, together with visualizing the scenario of incorporating more intelligence in the cloud platform, with the help of relatively newer technologies such as CAD as Adaptive OpenPlatform Service (CAOS). Altogether, this research explores several research opportunities linked with modern FPGA CAD flow design, which will serve as a single point of reference for modern FPGA CAD flow design

MachineFlow: A Web Tool to Adaptively Select EDA Tool Parameters for Digital ICs Using Statistical Learning

Digital integrated circuits (ICs) are the driving force behind computing, communication and entertainment in today’s world. More powerful and energy efficient ICs continue to be designed and built by the semiconductor industry to meet current demands. In addition, complexity in Electronic Design Automation(EDA) software continues to grow to keep up with the design and technological advances in ICs. Design parameters that control various aspects of EDA software, such as synthesis, placement and routing settings, can affect the performance of ICs, and current standard cell logic synthesis and physical design flow tools consist of hundreds of such parameters to be specified by the designer. Discovering the optimal value for each parameter can result in significant performance and power efficiency gains. In this thesis, we develop a proof of concept web tool that uses open source EDA software to generate datasets for a large number of circuits and uses the data to build predictive models using statistical learning techniques. We use these models to select design parameters for the VLSI physical design flow floorplanning and placement stages that minimize the total wirelength of the integrated circuit. Using empirical evaluation on three real-world test circuits, we show a 15x-35x reduction in time spent to discover predicted values of one of the studied parameters that reduces total wire-length with statistical significance compared to a brute force exploration of the design space, with an error rate below 5%. The key contributions of this thesis are: • Development of a web based tool to perform VLSI physical design flow of a standard cell based integrated circuit, as well as to generate and record datapoints at various stages of the flow. • Development and investigation of predictive models through the web based tool, using the recorded datapoints and utilizing statistical learning techniques, to predict VLSI physical design flow floorplanning and placement tool parameters that minimize total wirelength in a particular integrated circuit