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DAC 2027: Design Automation Conference

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投稿締切日:
2026-11-11 残り 22 日
通知日:
2027-03-08
開催日:
2027-07-11
開催地:
San Jose, California, USA
開催回数:
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ICORE: A*   QUALIS: A1   閲覧: 964926   フォロー: 126   参加: 23
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会伴インデックス (CP-I)

94.9 / 100
全 5,721 件中 第 18 位 · 上位 1%

ロボティクス・制御 分野 473 件中 第 1 位 システム・アーキテクチャ 分野 341 件中 第 5 位

学術的評価 (35%)
100
投稿の選択性 (20%)
88
開催回数 (20%)
100
コミュニティの注目度 (10%)
73
公開情報の充実度 (15%)
100

使用した入力: 収録ランク：QUALIS A1 · 採択率：22.1%（記録のある 5 回の平均） · 確認できる開催回数：64 · 会伴でフォローしている研究者：126 人 · 過去 24 か月にこのページを開いた研究者：32 人

信頼度 100% — スコアのうち、中立の基準値ではなく実際に観測されたデータに基づく割合。 このスコアの算出方法 · ランキングを見る · アルゴリズム版 1.2 · 算出日 2026-10-19

論文募集

DAC 2027 (Design Automation Conference) is a ICORE A* / QUALIS A1 conference held in San Jose, California, USA on 2027-07-11. The paper submission deadline is 2026-11-11. Acceptance notifications are sent on 2027-03-08.

Artificial Intelligence (AI) In addition to the traditional areas of AI models, processor architectures, and platforms, DAC 2027 invites papers on AI frontiers in hardware design including Agentic AI for verification, synthesis, physical design and flow automation, foundation models for EDA, as well as benchmarks, data sets, and model evaluation for EDA. Papers on the impact of emerging GenAI in chip and system design are encouraged. The focus will be in disruptive ideas that address inefficiencies in traditional flows and significantly improve power, performance, and area while reducing the design effort. AI1. AI/ML Frontiers for Hardware Design AI1.1 Benchmarks, data sets, and model evaluation for EDA AI1.2 Agentic AI for synthesis, physical design, and circuit design AI1.3 Agentic AI for RTL generation and PPA-driven refinement AI1.4 Agentic AI for verification AI1.5 AI-based chip design flow automation AI1.6 Foundation models for EDA AI1.7 AI/ML for hardware architecture design space exploration AI2. AI/ML Algorithms and Models AI2.1 Hardware-aware ML model development AI2.2 Efficient ML training, inference, and serving AI2.3 Approximation techniques for neural network training and inference AI2.4 Testing, debugging, and monitoring of ML applications AI2.5 Interpretability and explainability for ML models AI3. AI/ML Application and Systems AI3.1 Application-driven Al/ML learning/models/inferences AI3.2 Application-driven approximations in design for AI/ML AI3.3 Infrastructures for AI (including datasets, implementations) AI3.4 Interpretability and explainability for ML applications AI4. AI/ML Architecture Design AI4.1 AI/ML accelerator, processing engine design and architecture AI4.2 Application-specific AI/ML architectures AI4.3 Approximation techniques for hardware architecture AI5. AI/ML Infrastructure and Platform Design AI5.1 Hardware/software codesign and co-optimization AI5.2 Specialized AI/ML system design AI5.3 Architecture-algorithm co-design for ML/AI computing AI5.4 AI/ML system modeling and simulation methodologies AI5.5 Evaluation and measurement of AI/ML systems Design (DES) DAC is not only the leading conference in EDA, but also a vibrant hub for sharing cutting-edge progress in chip design technologies. From circuits to architectures, and from established methodologies to emerging frontiers like neuromorphic and quantum computing, DAC brings together diverse communities to exchange knowledge and spark innovation. The exchange helps the EDA community gain deeper insight into the evolving needs of design disciplines and fosters cross-domain collaboration to address shared challenges and opportunities. DES1. SoC, Heterogeneous, and Reconfigurable Architectures DES1.1 Architectures for stochastic, statistical and approximate computing DES1.2 SoC and heterogeneous multi- and many-core architectures DES1.3 Run-time and design-time reconfigurable processor architectures DES1.4 2.5D/3D heterogeneous integration of compute, memory and communication platforms DES1.5 Fault-tolerant architectures DES2A. In-memory and Near-memory Computing Circuits DES2A.1 Circuit techniques for near- or in-memory processing DES2A.2 Memory and storage technologies for in-memory and near-memory computing DES2A.3 Emerging technologies for in-memory and near-memory computing DES2A.4 Circuit-Inspired architectures for in/near-memory computing DES2B. In-memory and Near-memory Computing Architectures, Applications and Systems DES2B.1 Near- or in-memory data management and processing models DES2B.2 Architectures for near- or in-memory processing DES2B.3 Memory and storage architectures for near- or in-memory processing DES2B.4 Data reorganization engines for specific applications DES2B.5 System/architecture interaction, execution model, interfaces DES2B.6 Specialized architectures for key workloads taking advantage of near- and -in-memory processing DES3. Emerging Models of Computation DES3.1 Biologically-based or biologically-inspired computing systems DES3.2 Design automation for system & synthetic biology DES3.3 Neuromorphic and brain-inspired computing DES3.4 Neuromorphic and brain-inspired circuits DES3.5 Hyperdimensional computing DES3.6 Silicon photonics-based computing DES3.7 Ising machine-based computing DES4. Digital and Analog Circuits DES4.1 Novel circuits for emerging AI/ML workloads DES4.2 Digital circuits and systems DES4.3 Analog circuits and data converters DES4.4 RF, wireless & wireline circuits and systems DES4.5 Imagers, MEMS, medical, and display circuits DES4.6 Circuits for memory design DES4.7 Power management circuits DES4.8 2.5-D and 3-D integrated circuit designs DES4.9 Circuit design for secure computing DES5. Emerging Device and Interconnect Technologies DES5.1 New transistor structures DES5.2 Beyond-CMOS devices (e.g., steep-slope devices, spintronics) DES5.3 New process technologies (e.g. superconducting) DES5.4 Emerging interconnect and other nano-technologies DES5.5 Emerging non-volatile memory devices DES5.6 Microfluidic circuits DES6. Quantum Computing DES6.1 Quantum computing applications and algorithms DES6.2 Quantum computing hardware architecture and design DES6.3 Quantum computing technology DES6.4 EDA for quantum computing systems Electronic Design Automation (EDA) As the premier conference in EDA, DAC invites cutting-edge research submissions in all aspects of design automation for circuits, chips, and systems. This includes both traditional optimization and the latest AI/ML-based technologies for automated chip and system design. The focus will be on breakthrough advancements that significantly improve power, performance, and area while reducing design effort and overall time to market. EDA1. Design Methodologies for System-on-Chip and 3D/2.5D System-in-Package 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 EDA1.7 3D/2.5D In-Package and On-Chip Communication architecture modeling and analysis EDA1.8 Synthesis and optimization of communication architectures EDA1.9 NoC architectures and design methodologies EDA1.10 Communication architectures using alternative technologies (e.g., nanophotonics, RF) EDA2. Design Verification and Validation EDA2.1 Functional and transaction-level modeling and validation, coverage and test generation for hardware and embedded systems EDA2.2 Emulation and hardware acceleration EDA2.3 Formal and semi-formal verification and verification technologies EDA2.4 Verification of firmware, software, and hybrid hardware/software systems EDA2.5 AI/ML for functional verification, bug localization and debug EDA2.6 Validation of cognitive systems EDA2.7 Verification on the cloud EDA3. Timing Analysis and Optimization EDA3.1 Timing analysis and simulation/delay modeling EDA3.2 Signal integrity and noise analysis EDA3.3 Process technology modeling for timing analysis EDA3.4 Timing analysis and optimization for 3D/2.5D EDA3.5 Cell characterization EDA3.6 Parasitic extraction EDA3.7 AI/ML for timing analysis and optimization EDA4. Power/Thermal Analysis and Optimization 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 Power analysis related process technology modeling EDA4.6 Power and thermal analysis and optimization for 3D/2.5D EDA4.7 Power supply network modeling EDA4.8 AI/ML for power/thermal analysis and optimization EDA5. RTL/Logic Level and High-level Synthesis EDA5.1 Combinational, sequential and asynchronous logic synthesis EDA5.2 Technology mapping, cell-based design and optimization EDA5.3 High-level, behavioral, algorithmic, and architectural synthesis, “C” to gates tools and methods EDA5.4 Synthesis for FPGAs EDA5.5 Synthesis for circuits in emerging device technologies EDA5.6 Synthesis on the cloud EDA5.7 AI/ML techniques for synthesis EDA6. Analog CAD, Simulation, Verification and Test EDA6.1 Analog, mixed-signal, and RF design methodologies EDA6.2 Automated synthesis, place and route, and optimization of analog designs EDA6.3 Analog, mixed-signal, RF, electromagnetic, substrate noise modeling and simulation EDA6.4 AI/ML for analog design automation EDA6.5 Model order reduction techniques for analog/RF designs EDA6.6 Design automation for photonic interconnect and circuits EDA7. Physical Design and Verification EDA7.1 Floorplanning, partitioning, placement, and routing EDA7.2 Interconnect and clock network planning and synthesis EDA7.3 Cross-layer placement and routing optimization for timing/power/yield EDA7.4 Physical design of 3D/2.5D IC and package (e.g., TSV, interposer, monolithic) EDA7.5 Layout optimization for optical interconnects EDA7.6 Layout verification EDA7.7 Physical design on the cloud EDA7.8 Physical Design for secure computing EDA7.9 FPGA physical design EDA7.10 Gate sizing and buffering EDA7.11 Power grid layout EDA7.12 AI/ML for physical design and verification EDA8. Design for Manufacturability and Reliability EDA8.1 System/Design-technology co-optimization (STCO/DTCO) EDA8.2 Standard and custom cell design and optimization EDA8.3 Process technology characterization, extraction, and modeling EDA8.4 Reticle enhancement, lithography-related design optimizations and design rule checking EDA8.5 Design for manufacturability, yield, defect tolerance, cost issues, and DFM impact EDA8.6 Device-, gate, and circuit-level techniques for reliability analysis and optimization (e.g., soft error, aging, etc.) EDA8.7 3D/2.5D manufacturability, yield, and reliability EDA8.8 Post-Layout optimizations EDA9. Test, Validation and Silicon Lifecycle Management EDA9.1 Fault modeling, ATPG, DFT, BIST, compression EDA9.2 Memory, FPGA, and emerging technology test and reliability EDA9.3 SoC, board- and system-level test EDA9.4 Post-silicon test, optimization, and defect diagnosis EDA9.5 Post-silicon validation and debug EDA9.6 Test for analog/mixed-signal/RF circuits EDA9.7 Silicon lifecycle management and system sustainability EDA9.8 Silicon health monitoring and predictive maintenance Security (SEC) The Security track at DAC covers the areas of privacy and security for AI/ML applications as well as AI/ML-based attacks and defenses, alongside hardware security fundamentals like cryptographic primitives, trusted system design, and post-quantum cryptography. Topics also address hardware-based threats and countermeasures, hardware supply chain integrity, and the intersection of AI/ML with hardware security. Additionally, the scope includes embedded architecture and cross-layer security techniques for cyber-physical systems, IoT, and cloud. SEC1. AI/ML Security/Privacy SEC1.1 Privacy and security for AI/ML applications SEC1.2 AI/ML-based attacks and defenses SEC1.3 Adversarial machine learning attacks and defenses SEC1.4 AI/ML for cyber defense SEC1.5 Fairness for AI/ML applications SEC2. Hardware Security: Primitives, Architecture, Design & Test SEC2.1 Hardware security primitives for cryptography, key generation, and authentication SEC2.2 Trusted IP and system-on-chip (SoC) design and manufacturing SEC2.3 Emerging technologies (Nanoscale devices, 3D, etc.) and security SEC2.4 Hardware security verification, validation and test SEC2.5 Post-quantum crypto algorithms and implementations SEC2.6 Design automation for security and privacy preserving SEC2.7 Hardware acceleration for trust/security computing, e.g., homomorphic encryption and zero knowledge proof SEC3. Hardware Security: Attack and Defense SEC3.1 Hardware-enabled side-channel attacks and defenses SEC3.2 Hardware supply chain protection and anti-counterfeiting SEC3.3 Reverse engineering and hardware obfuscation SEC4. Embedded and Cross-Layer Security SEC4.1 Embedded architecture, software and system-level techniques for security and privacy SEC4.2 Cyber-physical systems, IoT and edge security SEC4.3 Embedded security: metrics, models, verification and validation SEC4.4 Cloud security SEC4.5 Software-driven side-channel attacks and defenses SEC4.6 Privacy preserving computing Systems (SYS) System design involves the design, selection, and integration of the right mix of hardware and software components to meet overarching goals such as speed, efficiency, reliability, security, and safety. Today’s systems span a wide range of applications—from mobile devices and medical equipment to automotive, robotics, drones, and industrial systems—making the field both diverse and dynamic. Embedded software plays a crucial role in devices that often aren’t recognized as computers, like thermostats, toys, defibrillators, and anti-lock braking systems, influencing both their operation and perceived quality. The SYS sessions at DAC showcase cutting-edge research in this area and serve as a platform for discussing the complex issues and future strategies for this rapidly evolving discipline. SYS1. Autonomous Systems, Cyber-Physical Systems and IoT SYS1.1 Autonomous Systems Design Tools and Methodologies SYS1.2 Autonomous Systems Architectures SYS1.3 Autonomous Systems Safety and Reliability SYS1.4 Cyber-physical systems and Internet-of-Things (IoT) platforms SYS1.5 Low-power and energy-efficient design techniques for IoT SYS1.6 Partitioned Edge/hub/cloud processing SYS1.7 Dependable and safety-critical embedded system design SYS1.8 Networking and storage system design SYS1.9 Advanced wireless communication system design SYS2. System Design Tools, Software, and Methodologies SYS2.1 Embedded software verification methodologies SYS2.2 Embedded operating systems, middleware, runtime support, resource management, and virtual machines SYS2.3 Software techniques for multicores, GPUs, and multithreaded embedded architectures SYS2.4 Compilation strategies, code transformation and parallelization techniques for embedded systems SYS2.5 Domain-specific embedded libraries SYS2.6 Embedded Software Development Case Studies SYS2.7 Embedded system specification, virtual prototyping and simulation SYS2.8 Embedded system synthesis and optimization SYS2.9 Analysis of embedded system QoS metrics - performance, battery life, reliability, etc. SYS2.10 Design methodologies for self-aware, self-adaptive and autonomous embedded systems SYS2.11 Design methodology for mobile, wearable and Internet of Things devices SYS3. Embedded Memory and Storage Systems SYS3.1 On-chip memory architectures and management: Scratchpads, compiler controlled memories, etc. SYS3.2 Embedded storage systems organization and management SYS3.3 Memory and Storage hierarchies with emerging memory technologies SYS4. Time-Critical and Fault-Tolerant System Design SYS4.1 Real-time analysis and tool flows SYS4.2 WCET methods and tools for embedded hardware/software systems SYS4.3 Mixed-Criticality system design SYS4.4 Fault-tolerant embedded system design
最終更新：Admin Agent （）

採択率

平均採択率: 26.1% 10 年間 (2000–2014).

年投稿数採択数採択率(%)
201478717422.1%
201374015621.1%
201274116422.1%
200686520924.2%
200573515421%
200478516320.8%
200362815224.2%
200249114729.9%
200141016039%
200039014236.4%

ベストペーパー

年ベストペーパー
2022Towards a formally verified hardware root-of-trust for data-oblivious computing
2019Dreamplace: Deep Learning Toolkit-enabled GPU Acceleration for Modern VLSI Placement
2018Compensated-DNN: Energy Efficient Low-Precision Deep Neural Networks by Compensating Quantization Errors
2018Exact Algorithms for Delay-Bounded Steiner Arborescences
2017Toward Optimal Legalization for Mixed-Cell-Height Circuit Designs
2017Low-Power On-Chip Network Providing Guaranteed Services for Snoopy Coherent and Artificial Neural Network Systems
2016Accurate Phase-level Cross-platform Power and Performance Estimation
2016Distributed On-chip Regulation: Theoretical Stability Foundation, Over-design Reduction and Performance Optimization
2015Battery Lifetime-Aware Automotive Climate Control for Electric Vehicles
2015HAFIX: Hardware-Assisted Flow Integrity Extension
2014Containing Timing-Related Certification Cost in Automotive Systems Deploying Complex Hardware
2014Code Coverage of Assertions Using RTL Source Code Analysis
2012Triple Patterning Aware Routing and its Comparison with Double Patterning Aware Routing in 14nm Technology
2010Bayesian virtual probe: minimizing variation characterization cost for nanoscale IC technologies via Bayesian inference
2009A robust and efficient harmonic balance (HB) using direct solution of HB Jacobian
2008IFRA: instruction footprint recording and analysis for post-silicon bug localization in processors
2008WavePipe: parallel transient simulation of analog and digital circuits on multi-core shared-memory machines
2007Period Optimization for Hard Real-time Distributed Automotive Systems
2007Interdependent Latch Setup/Hold Time Characterization via Euler-Newton Curve Tracing on State-Transition Equations
2006SAT sweeping with local observability don't-cares
2006Power grid physics and implications for CAD
2005A new canonical form for fast boolean matching in logic synthesis and verification
2005An efficient algorithm for statistical minimization of total power under timing yield constraints
2004A recursive paradigm to solve Boolean relations
2004First-order incremental block-based statistical timing analysis
2003Automatic application-specific instruction-set extensions under microarchitectural constraints
2003Random walks in a supply network
2003NORM: compact model order reduction of weakly nonlinear systems
2003The synthesis of cyclic combinational circuits
2002A universal technique for fast and flexible instruction-set architecture simulation
2002Remembrance of circuits past: macromodeling by data mining in large analog design spaces
2002Guaranteed passive balancing transformations for model order reduction
2001Energy Efficient Fixed-Priority Scheduling for Real-Time Systems on Variable Voltage Processors
2001A Practical Methodology for Early Buffer and Wire Resource Allocation
2001Analysis of On-Chip Inductance Effects using a Novel Performance Optimization Methodology for Distributed RLC Interconnects
2001Improving Bus Test Via IDDT and Boundary Scan
2000Communication architecture tuners: a methodology for the design of high-performance communication architectures for systems-on-chips
2000A multi-interval Chebyshev collocation method for efficient high-accuracy RF circuit simulation
2000On-chip inductance modeling and analysis
2000To split or to conjoin: the question in image computation
1999Coverage Estimation for Symbolic Model Checking
1999Reducing Cross-Coupling Among Interconnect Wires in Deep-Submicron Datapath Design
1999Common-Case Computation: A High-Level Technique for Power and Performance Optimization
1999Improving the Test Quality for Scan-Based BIST Using a General Test Application Scheme
1999Reliability-Constrained Area Optimization of VLSI Power/Ground Networks via Sequence of Linear Programmings
1998A Decision Procedure for Bit-Vector Arithmetic
1998A Fast Hierarchical Algorithm for 3-D Capacitance Extraction
1998OCCOM: Efficient Computation of Observability-Based Code Coverage Metrics for Functional Verification
1998Functional Verification of a Multiple-issue, Out-of-Order, Superscalar Alpha Processor - The DEC Alpha 21264 Microprocessor
1998Generic Global Placement and Floorplanning
1997Computer-Aided Design of Free-Space Opto-Electronic Systems
1997An Improved Algorithm for Minimum-Area Retiming
1997Equivalence Checking Using Cuts and Heaps
1997Efficient Methods for Simulating Highly Nonlinear Multi-Rate Circuits
1996A Probability-Based Approach to VLSI Circuit Partitioning
1996POSE: Power Optimization and Synthesis Environment
1996HEAT: Hierarchical Energy Analysis Tool
1996Using Register-Transfer Paths in Code Generation for Heterogeneous Memory-Register Architectures
1996On Solving Covering Problems
1995Verification of Arithmetic Circuits with Binary Moment Diagrams
1995DELAY: An Efficient Tool for Retiming with Realistic Delay Modeling
1995Spectral Partitioning: The More Eigenvectors, The Better
1995Behavioral Synthesis Methodology for HDL-Based Specification and Validation
1994Basic Concept of Cooperative Timing-driven Design Automation Technology for High-speed RISC Processor HARP-1
1994Resynthesis and Retiming for Optimum Partial Scan

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BA89.8RTASIEEE Real-Time and Embedded Technology and Applications Symposium2026-11-052027-05-11
BB76.9DASFAAInternational Conference on Database Systems for Advanced Applications2026-11-252027-05-27
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AA*94.7CVPRIEEE Conference on Computer Vision and Pattern Recognition2026-11-102027-06-20
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CB62.9IJCNNInternational Joint Conference on Neural Networks2027-01-312027-06-14
B91.2ICASSPInternational Conference on Acoustics, Speech and Signal Processing2026-09-162027-05-16

関連ジャーナル

CCF正式名称インパクトファクター出版社ISSN
Design Automation for Embedded Systems0.9Springer0929-5585
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536

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