Research Paper Submission Categories

 

Artificial Intelligence (AI)

Artificial intelligence (AI) track highlights the advances in the field with a focus on machine learning model development, AI inspired models of computation, security aspects related to AI/ML, and application of AI to autonomous systems. While artificial intelligence and artificial neural network research have been ongoing for more than half a century, recent advances in accelerating the pace and scale of machine learning (ML) and deep neural networks (DNNs) are revolutionizing the impact of artificial intelligence on every aspect of our daily lives, ranging from smart consumer electronics to personalized medicine and services.

The AI sessions at DAC focuses on the fundamentals, accomplishments to date, and challenges ahead in models, algorithms, applications, and security/privacy issues, providing a forum for researchers and practitioners across all the widely varying disciplines involved to connect, engage, and join in shaping the future of this exciting field.

AI1. ML Algorithms and Applications

AI1.1    Hardware-aware ML model development
AI1.2    Efficient ML training, inference, and serving
AI1.3    Approximation techniques for neural network training and inference
AI1.4    Application-driven approximations in design for AI/ML
AI1.5    Testing, debugging, and monitoring of ML applications
AI1.6    Interpretability and explainability for ML models and applications

AI2. AI/ML Security/Privacy

AI2.1    Privacy and security for AI/ML applications
AI2.2    AI/ML-based attacks and defenses
AI2.3    Adversarial machine learning attacks and defenses
AI2.4        AI/ML for cyber defense
AI2.5    Fairness for AI/ML applications

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Autonomous Systems

Electronics content in modern autonomous systems (e.g., automotive, robotics, drones, etc.) is growing at an increasingly rapid pace. Nearly every aspect of these complex systems uses smart electronics and embedded software to make our experiences safer, more energy-efficient and enjoyable. For example, premium vehicles can have several million lines of embedded software code running on hundreds of electronic control units. Within autonomous systems, such as automotive, these sub-systems connect with one another by in-system networks. As the trend towards fully autonomous driving and connectivity accelerates, the ability to deliver these innovations depends more than ever on advanced electronics and software development.

AS1. Autonomous Systems (Automotive, Robotics, Drones)

AS1.1 Autonomous Systems Design Tools and Methodologies
AS1.2 Autonomous Systems Architectures
AS1.3 Autonomous Systems Safety and Reliability

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Design

DAC has served as a meeting place for designers of electronic systems and providers of electronic design automation tools for over five decades. Increasingly, the challenges faced by the industry require cross-domain interaction of researchers and practitioners working on electronic design (circuit, architecture, and embedded systems design) and researchers working on design methodologies and tools. DAC serves this need by covering design as a topic area in the research track, in addition to organizing a dedicated Engineering Tracks for practitioners.

The design topics covered in the research track include the design of cyber-physical and cloud systems, SoC architectures, in-memory and near-memory computing architectures, AI/ML hardware and systems, digital and analog circuits, emerging device technologies, and quantum computing.

Separately the Engineering Tracks allows tool users to share challenges and benefits of different tools, flows, and methodologies. In addition, it provides excellent opportunities for education and networking between end users and tool developers. There is no other way to improve your “design IQ” in such a short amount of time than to attend the Engineering Tracks.

DES1. Design of Cyber-physical Systems, Cloud Computing and IoT

DES1.1 Cyber-physical systems and Internet-of-Things (IoT) platforms
DES1.2 Low-power and energy-efficient design techniques for IoT
DES1.3 Partitioned Edge/hub/cloud processing
DES1.4 Dependable and safety-critical embedded system design
DES1.5 Networking and storage system design
DES1.6 Advanced wireless communication system design

DES2. SoC, Heterogeneous, and Reconfigurable Architectures

DES2.1 Architectures for stochastic, statistical and approximate computing
DES2.2 SoC and heterogeneous multi- and many-core architectures
DES2.3 Run-time and design-time reconfigurable processor architectures
DES2.4 2.5D/3D heterogeneous integration of compute, memory and communication platforms

DES3. In-memory and Near-memory Computing

DES3.1 Approximation techniques for neural network training and inference
DES3.2 Application-driven approximations in hardware architecture and design for AI/ML
DES3.3 AI/ML architecture-algorithm co-design for approximate computing 

DES4. AI/ML Design: Circuits and Architecture

DES4.1 AI/ML circuits and architecture design
DES4.2 AI/ML accelerator, processing engine design and architecture
DES4.3 Application-driven approximations techniques for hardware architecture
DES4.4 Neuromorphic and brain-inspired circuits, sensors, and processors

DES5.  AI/ML Design: System and Platform

DES5.1 Hardware/software codesign and co-optimization
DES5.2 Specialized AI/ML system design
DES5.3 Architecture-algorithm co-design for approximate computing
DES5.4 AI/ML system modeling and simulation methodologies
DES5.5 Evaluation and measurement of AI/ML systems

DES6. Emerging Models of Computation

DES6.1 Biologically-based or biologically-inspired computing systems
DES6.2 Design automation for system & synthetic biology
DES6.3 Neuromorphic and brain-inspired computing

DES7. Digital and Analog Circuits

DES7.1 2.5-D and 3-D integrated circuit designs
DES7.2 Clock network and interconnect designs
DES7.3 Low-power and energy-efficient digital circuits
DES7.4 Analog, mixed-signal and RF circuits
DES7.5 Circuits for advanced wireless communication
DES7.6 Memory design

DES8. Emerging Device Technologies

DES8.1 New transistor structures, beyond-CMOS devices (e.g., steep-slope devices, spintronics), and new process technologies
DES8.2 Nanotechnologies, nanowires, nanotubes
DES8.3 Emerging non-volatile memory devices

DES9. Quantum Computing

DES9.1 Quantum computing applications and algorithms
DES9.2 Quantum computing hardware architecture and design
DES9.3 Quantum computing technology

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Electronic Design Automation (EDA)

EDA (Electronics Design Automation) is becoming ever more important with the continuous scaling of semiconductor devices and the growing complexities of their use in circuits and systems. Demands for lower-power, higher-reliability and more agile electronic systems raise new challenges to both design and design automation of such systems. For the past five decades, the primary focus of research track at DAC has been to showcase leading-edge research and practice in tools and methodologies for the design of circuits and systems.

In addition to the traditional EDA topics ranges from physical design to system architectures, DAC features high-quality papers on design research, design practices, and design automation for cross-cutting topics including low-power, reliability, multicore/application specific/heterogeneous architectures, 3-D integrations, emerging device technologies, design automation of “things”, and their applications. The track also highlights the advances of AI/ML techniques in the field of design automation. DAC’s EDA technical program has been ensuring the best-in-class solutions that promise to advance EDA.

EDA1. System-on-Chip Design Methodology

EDA1.1 System-on-Chip (SoC) specification, modeling, analysis, simulation, and verification
EDA1.2 Application-specific processor design tools
EDA1.3 Design tools for accelerator-rich architectures and heterogeneous multi-cores
EDA1.4 Tools for reconfigurable computing
EDA1.5 HW/SW co-design, interface synthesis, and co-verification
EDA1.6 System-level methods for reliability and aging

 EDA2. In-Package and On-Chip Communication and Networks-on-Chip

EDA2.1 Communication architecture modeling and analysis
EDA2.2 Synthesis and optimization of communication architectures
EDA2.3 NoC architectures and design methodologies
EDA2.4 Communication architectures using alternative technologies (e.g., nanophotonics, RF, 3D, etc.)

EDA3. Cross-Layer Power Analysis and Low-Power Design

EDA3.1 System-level low-power design analysis and management
EDA3.2 Architectural power reduction techniques and analysis tools
EDA3.3 Low-power circuit design methods and tools
EDA3.4 System-level and architectural thermal analysis and management

EDA4. Timing and Low Power Design

EDA4.1 System-level low-power design analysis and management
EDA4.2 Architectural power reduction techniques and analysis tools
EDA4.3 Low-power circuit design methods and tools
EDA4.4 Thermal analysis and management
EDA4.5 Timing analysis and simulation/delay modeling
EDA4.6 Power/signal integrity analysis and simulation
EDA4.7 Process technology modeling

EDA4. RTL/Logic Level and High-level Synthesis 

EDA4.1 Combinational, sequential and asynchronous logic synthesis
EDA4.2 Technology mapping, cell-based design and optimization
EDA4.3 High-level, behavioral, algorithmic, and architectural synthesis, “C” to gates tools and methods
EDA4.4 Synthesis for FPGAs
EDA4.5 Synthesis for circuits in emerging device technologies

 EDA5. Analog Design, Simulation, Verification and Test

EDA5.1 Analog, mixed-signal, and RF design methodologies
EDA5.2 Automated synthesis and optimization of analog designs
EDA5.3 Analog, mixed-signal, RF, electromagnetic, substrate noise modeling and simulation
EDA5.4 Model order reduction techniques for analog/RF designs

EDA6. Physical Design and Verification, Lithography and DFM

EDA6.1 Floorplanning, partitioning, placement
EDA6.2 Interconnect and clock network planning and synthesis
EDA6.3 Cross-layer placement and routing optimization for timing/power/yield
EDA6.4 Post-Layout and post-silicon optimizations
EDA6.5 Physical design of 3-D integrated circuits
EDA6.6 Reticle enhancement, lithography-related design optimizations and design rule checking
EDA6.7 Design for manufacturability, yield, defect tolerance, cost issues, and DFM impact
EDA6.8 Device-, circuit- and gate-level techniques for reliability (e.g.: manufacturing variations, aging, etc.)

EDA7. Design Verification and Validation

EDA7.1 Functional and transaction-level modeling and validation, coverage and test generation for hardware and embedded systems
EDA7.2 Emulation and hardware acceleration
EDA7.3 Formal and semi-formal verification and verification technologies
EDA7.4 Verification of firmware, software, and hybrid hardware/software systems
EDA7.5 Machine learning techniques for verification
EDA7.6 Post-silicon design validation and debug
EDA7.7 Validation of cognitive systems

EDA8. Manufacturing Test and Reliability

EDA8.1 Fault modeling, ATPG, DFT, BIST, compression
EDA8.2 Memory, FPGA and emerging technology test and reliability
EDA8.3 SoC, board- and system-level test
EDA8.4 Post-silicon test and defect diagnosis
EDA8.5 Analog/mixed-signal/RF verification and test
EDA8.6 Noise, aging induced delays, and reliability analysis

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Embedded Systems & Software (ESS)

Embedded system design is the art of choosing and designing the proper combination of hardware and software components to achieve system level design goals like speed, efficiency, reliability, security, and safety. Embedded systems are an increasingly diverse, disruptive, and challenging field for designs ranging from mobile devices, medical devices, automotive, robotics, drones, industrial and beyond. Embedded software is built into devices that may not necessarily be recognized as computing devices (e.g., thermostats, toys, defibrillators, and anti-lock brakes), but nevertheless controls the functionality and perceived quality of these devices.

The ESS sessions at DAC provide a forum for discussing the challenges of embedded design and an opportunity for leaders in the industry and academia to come together to exchange ideas and roadmaps for the future for this rapidly expanding area.

ESS1. Embedded Software

ESS1.1 Embedded software verification methodologies
ESS1.2 Embedded operating systems, middleware, runtime support, resource management, and virtual machines
ESS1.3 Software techniques for multicores, GPUs, and multithreaded embedded architectures
ESS1.4 Compilation strategies, code transformation and parallelization techniques for embedded systems
ESS1.5 Domain-specific embedded libraries (e.g., for machine learning)
ESS1.6 Embedded Software Development Case Studies (e.g., ANDROID development, ARM-based systems, RISC-V based systems etc.)

ESS2. Embedded System Design Methodologies

ESS2.1 Embedded system specification, virtual prototyping and simulation
ESS2.2 Embedded system synthesis and optimization
ESS2.3 Analysis of embedded system QoS metrics - performance, battery life, reliability, etc.
ESS2.4 Design methodologies for self-aware, self-adaptive and autonomous embedded systems
ESS2.5 Design methodology for mobile, wearable and Internet of Things devices

ESS3. Embedded Memory, Storage and Networking

ESS3.1 On-chip memory architectures and management: Scratchpads, compiler controlled memories, etc.
ESS3.2 Embedded storage systems organization and management
ESS3.3 Memory and Storage hierarchies with emerging memory technologies

ESS4. Time-Critical System Design

ESS4.1 Real-time analysis and tool flows
ESS4.2 WCET methods and tools for embedded hardware/software systems
ESS4.3 Mixed-Criticality system design

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Security

Security sessions at DAC address an urgent need to create, analyze, evaluate, and improve the hardware, embedded systems and software base of the contemporary security solutions. Secure and trustworthy software and hardware components, platforms and supply chains are vital to all domains including financial, healthcare, transportation, and energy. Security of systems is becoming equally important. A revolution is underway in many industries that are “connecting the unconnected”. 

Cyber physical systems, e.g., automobiles, smart grid, medical devices, etc., are taking advantage of integration of physical systems with the information systems. Not withstanding the numerous benefits, these systems are appealing targets of attacks. Attacks on the cyber-part of such systems can have disastrous consequences in the physical world. The scope and variety of attacks on these systems present design challenges that span embedded hardware, software, networking, and system design.

Security topics will be featured through invited special sessions, panels, and lecture/poster presentations by both practitioners and researchers to share their knowledge and experience on this evolving environment.

SEC1. Hardware Security: Primitives, Architecture, Design & Test

SEC1.1 Hardware security primitives for cryptography, key generation, and authentication
SEC1.2 Trusted IP and system-on-chip (SoC) design and manufacturing
SEC1.3 Emerging technologies (Nanoscale devices, 3D, etc.) and security
SEC1.4 Hardware security verification, validation and test
SEC1.5 Post-quantum crypto algorithms and implementations

SEC2. Hardware Security: Attack and Defense

SEC2.1 Hardware-enabled side-channel attacks and defenses
SEC2.2 Software-driven side-channel attacks and defenses
SEC2.3 AI/ML-based attacks and defenses
SEC2.4 Adversarial machine learning attacks and defenses
SEC2.3 Hardware supply chain protection and anti-counterfeiting
SEC2.4 Reverse engineering and hardware obfuscation

SEC3. Embedded and Cross-Layer Security

SEC3.1 Embedded software and system-level techniques for security
SEC3.2 Architectural support for software and embedded systems security
SEC3.3 Cyber-physical systems and IoT security
SEC3.4 Embedded security: metrics, models, verification and validation
SEC3.5 Machine learning for cyber defense

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