Conferences · eligible papers
ICCAD
2022–2026 LIVE
2022 · 132 papers
このEditionに反映済みのmain full research papersのみ掲載しています。著者リンクは日本の大学への著者別所属根拠がある場合に限ります。
- A Combined Logical and Physical Attack on Logic Obfuscation
日本大学: 関与なし(対象大学)
- A High-Precision Stochastic Solver for Steady-State Thermal Analysis with Fourier Heat Transfer Robin Boundary Conditions
日本大学: 関与なし(対象大学)
- A Novel Blockage-Avoiding Macro Placement Approach for 3D ICs Based on POCS
日本大学: 関与なし(対象大学)
- A Novel Semi-Analytical Approach for Fast Electromigration Stress Analysis in Multi-Segment Interconnects
日本大学: 関与なし(対象大学)
- A Pragmatic Methodology for Blind Hardware Trojan Insertion in Finalized Layouts
日本大学: 関与なし(対象大学)
- A Robust Global Routing Engine with High-Accuracy Cell Movement under Advanced Constraints
日本大学: 関与なし(対象大学)
- A Robust Quantum Layout Synthesis Algorithm with a Qubit Mapping Checker
日本大学: 関与なし(対象大学)
- A Stochastic Approach to Handle Non-Determinism in Deep Learning-Based Design Rule Violation Predictions
日本大学: 関与なし(対象大学)
- ASPPLN: Accelerated Symbolic Probability Propagation in Logic Network
日本大学: 関与なし(対象大学)
- ATLAS: A Two-Level Layer-Aware Scheme for Routing with Cell Movement
日本大学: 関与なし(対象大学)
- Accelerating Cache Coherence in Manycore Processor through Silicon Photonic Chiplet
日本大学: 関与なし(対象大学)
- Accelerating Fully Homomorphic Encryption by Bridging Modular and Bit-Level Arithmetic
日本大学: 関与なし(対象大学)
- Accelerating N-Bit Operations over TFHE on Commodity CPU-FPGA
日本大学: 関与なし(対象大学)
- AdaOPC: A Self-Adaptive Mask Optimization Framework for Real Design Patterns
日本大学: 関与なし(対象大学)
- Aging-Aware Training for Printed Neuromorphic Circuits
日本大学: 関与なし(対象大学)
- All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management
日本大学: 関与なし(対象大学)
- An Approach to Unlocking Cyclic Logic Locking: LOOPLock 2.0
日本大学: 関与なし(対象大学)
- An MLIR-based Compiler Flow for System-Level Design and Hardware Acceleration
日本大学: 関与なし(対象大学)
- AntiSIFA-CAD: A Framework to Thwart SIFA at the Layout Level
日本大学: 関与なし(対象大学)
- AppGNN: Approximation-Aware Functional Reverse Engineering Using Graph Neural Networks
日本大学: 関与なし(対象大学)
- Arjun: An Efficient Independent Support Computation Technique and its Applications to Counting and Sampling
日本大学: 関与なし(対象大学)
- Associative Memory Based Experience Replay for Deep Reinforcement Learning
日本大学: 関与なし(対象大学)
- Attack Directories on ARM big.LITTLE Processors
日本大学: 関与なし(対象大学)
- Automatic Test Configuration and Pattern Generation (ATCPG) for Neuromorphic Chips
日本大学: 関与なし(対象大学)
- Batch Sequential Black-Box Optimization with Embedding Alignment Cells for Logic Synthesis
日本大学: 関与なし(対象大学)
- Big-Little Chiplets for In-Memory Acceleration of DNNs: A Scalable Heterogeneous Architecture
日本大学: 関与なし(対象大学)
- CASU: Compromise Avoidance via Secure Update for Low-End Embedded Systems
日本大学: 関与なし(対象大学)
- COSIME: FeFET Based Associative Memory for In-Memory Cosine Similarity Search
日本大学: 関与なし(対象大学)
- CoMUX: Combinatorial-Coding-Based High-Performance Microfluidic Control Multiplexer Design
日本大学: 関与なし(対象大学)
- Combining BMC and Complementary Approximate Reachability to Accelerate Bug-Finding
日本大学: 関与なし(対象大学)
- Combining Gradients and Probabilities for Heterogeneous Approximation of Neural Networks
日本大学: 関与なし(対象大学)
- Compositional Verification Using a Formal Component and Interface Specification
日本大学: 関与なし(対象大学)
- Computing-In-Memory Neural Network Accelerators for Safety-Critical Systems: Can Small Device Variations Be Disastrous?
日本大学: 関与なし(対象大学)
- DARL: Distributed Reconfigurable Accelerator for Hyperdimensional Reinforcement Learning
日本大学: 関与なし(対象大学)
- DCIM-GCN: Digital Computing-in-Memory to Efficiently Accelerate Graph Convolutional Networks
日本大学: 関与なし(対象大学)
- DEEP: Developing Extremely Efficient Runtime On-Chip Power Meters
日本大学: 関与なし(対象大学)
- DaS: Implementing Dense Ising Machines Using Sparse Resistive Networks
日本大学: 関与なし(対象大学)
- DeePEB: A Neural Partial Differential Equation Solver for Post Exposure Baking Simulation in Lithography
日本大学: 関与なし(対象大学)
- Deep Learning Toolkit-Accelerated Analytical Co-Optimization of CNN Hardware and Dataflow
日本大学: 関与なし(対象大学)
- Design Space and Memory Technology Co-Exploration for In-Memory Computing Based Machine Learning Accelerators
日本大学: 関与なし(対象大学)
- Design and Technology Co-Optimization Utilizing Multi-Bit Flip-Flop Cells
日本大学: 関与なし(対象大学)
- Designing Energy-Efficient Decision Tree Memristor Crossbar Circuits Using Binary Classification Graphs
日本大学: 関与なし(対象大学)
- Don't CWEAT It: Toward CWE Analysis Techniques in Early Stages of Hardware Design
日本大学: 関与なし(対象大学)
- DynaPAT: A Dynamic Pattern-Aware Encoding Technique for Robust MLC PCM-Based Deep Neural Networks
日本大学: 関与なし(対象大学)
- Dynamic Frequency Boosting Beyond Critical Path Delay
日本大学: 関与なし(対象大学)
- EI-MOR: A Hybrid Exponential Integrator and Model Order Reduction Approach for Transient Power/Ground Network Analysis
日本大学: 関与なし(対象大学)
- EVE: Environmental Adaptive Neural Network Models for Low-Power Energy Harvesting System
日本大学: 関与なし(対象大学)
- Equivalence Checking of Dynamic Quantum Circuits
日本大学: 関与なし(対象大学)
- Evaluating the Security of eFPGA-Based Redaction Algorithms
日本大学: 関与なし(対象大学)
- Exploiting Uniform Spatial Distribution to Design Efficient Random Number Source for Stochastic Computing
日本大学: 関与なし(対象大学)
- Fast and Compact Interleaved Modular Multiplication Based on Carry Save Addition
日本大学: 関与なし(対象大学)
- Fast, Robust and Accurate Detection of Cache-Based Spectre Attack Phases
日本大学: 関与なし(対象大学)
- FastStamp: Accelerating Neural Steganography and Digital Watermarking of Images on FPGAs
日本大学: 関与なし(対象大学)
- Fine-Granular Computation and Data Layout Reorganization for Improving Locality
日本大学: 関与なし(対象大学)
- Fuse and Mix: MACAM-Enabled Analog Activation for Energy-Efficient Neural Acceleration
日本大学: 関与なし(対象大学)
- GIA: A Reusable General Interposer Architecture for Agile Chiplet Integration
日本大学: 関与なし(対象大学)
- GPU-Accelerated Rectilinear Steiner Tree Generation
日本大学: 関与なし(対象大学)
- Garbled EDA: Privacy Preserving Electronic Design Automation
日本大学: 関与なし(対象大学)
- Generation of Mixed-Driving Multi-Bit Flip-Flops for Power Optimization
日本大学: 関与なし(対象大学)
- Graph Neural Networks for Idling Error Mitigation
日本大学: 関与なし(対象大学)
- GraphRC: Accelerating Graph Processing on Dual-Addressing Memory with Vertex Merging
日本大学: 関与なし(対象大学)
- Gzippo: Highly-Compact Processing-in-Memory Graph Accelerator Alleviating Sparsity and Redundancy
日本大学: 関与なし(対象大学)
- HDTorch: Accelerating Hyperdimensional Computing with GP-GPUs for Design Space Exploration
日本大学: 関与なし(対象大学)
- HECTOR: A Multi-Level Intermediate Representation for Hardware Synthesis Methodologies
日本大学: 関与なし(対象大学)
- Hardware Computation Graph for DNN Accelerator Design Automation without Inter-PU Templates
日本大学: 関与なし(対象大学)
- Heterogeneous Graph Neural Network-Based Imitation Learning for Gate Sizing Acceleration
日本大学: 関与なし(対象大学)
- Hidden-ROM: A Compute-in-ROM Architecture to Deploy Large-Scale Neural Networks on Chip with Flexible and Scalable Post-Fabrication Task Transfer Capability
日本大学: 関与なし(対象大学)
- HierPINN-EM: Fast Learning-Based Electromigration Analysis for Multi-Segment Interconnects Using Hierarchical Physics-Informed Neural Network
日本大学: 関与なし(対象大学)
- How Good Is Your Verilog RTL Code?: A Quick Answer from Machine Learning
日本大学: 関与なし(対象大学)
- HyperEF: Spectral Hypergraph Coarsening by Effective-Resistance Clustering
日本大学: 関与なし(対象大学)
- INDENT: Incremental Online Decision Tree Training for Domain-Specific Systems-on-Chip
日本大学: 関与なし(対象大学)
- ISSA: Input-Skippable, Set-Associative Computing-in-Memory (SA-CIM) Architecture for Neural Network Accelerators
日本大学: 関与なし(対象大学)
- Inhale: Enabling High-Performance and Energy-Efficient In-SRAM Cryptographic Hash for IoT
日本大学: 関与なし(対象大学)
- Language Equation Solving via Boolean Automata Manipulation
日本大学: 関与なし(対象大学)
- LayouTransformer: Generating Layout Patterns with Transformer via Sequential Pattern Modeling
日本大学: 関与なし(対象大学)
- Logic Synthesis for Digital In-Memory Computing
日本大学: 関与なし(対象大学)
- Low-Cost 7T-SRAM Compute-in-Memory Design Based on Bit-Line Charge-Sharing Based Analog-to-Digital Conversion
日本大学: 関与なし(対象大学)
- MCQA: Multi-Constraint Qubit Allocation for Near-FTQC Device
日本大学: 関与なし(対象大学)
- ModelMap: A Model-Based Multi-Domain Application Framework for Centralized Automotive Systems
日本大学: 関与なし(対象大学)
- Multi-Package Co-Design for Chiplet Integration
日本大学: 関与なし(対象大学)
- NASA: Neural Architecture Search and Acceleration for Hardware Inspired Hybrid Networks
日本大学: 関与なし(対象大学)
- Neurally-Inspired Hyperdimensional Classification for Efficient and Robust Biosignal Processing
日本大学: 関与なし(対象大学)
- Numerically-Stable and Highly-Scalable Parallel LU Factorization for Circuit Simulation
日本大学: 関与なし(対象大学)
- ObfuNAS: A Neural Architecture Search-Based DNN Obfuscation Approach
日本大学: 関与なし(対象大学)
- Obstacle-Avoiding Multiple Redistribution Layer Routing with Irregular Structures
日本大学: 関与なし(対象大学)
- On Minimizing the Read Latency of Flash Memory to Preserve Inter-Tree Locality in Random Forest
日本大学: 関与なし(対象大学)
- Personalized Heterogeneity-Aware Federated Search Towards Better Accuracy and Energy Efficiency
日本大学: 関与なし(対象大学)
- Physics-Aware Differentiable Discrete Codesign for Diffractive Optical Neural Networks
日本大学: 関与なし(対象大学)
- Pin Accessibility and Routing Congestion Aware DRC Hotspot Prediction Using Graph Neural Network and U-Net
日本大学: 関与なし(対象大学)
- PowerTouch: A Security Objective-Guided Automation Framework for Generating Wired Ghost Touch Attacks on Touchscreens
日本大学: 関与なし(対象大学)
- QCIR: Pattern Matching Based Universal Quantum Circuit Rewriting Framework
日本大学: 関与なし(対象大学)
- Qilin: Enabling Performance Analysis and Optimization of Shared-Virtual Memory Systems with FPGA Accelerators
日本大学: 関与なし(対象大学)
- QuBRIM: A CMOS Compatible Resistively-Coupled Ising Machine with Quantized Nodal Interactions
日本大学: 関与なし(対象大学)
- Quantitative Verification and Design Space Exploration under Uncertainty with Parametric Stochastic Contracts
日本大学: 関与なし(対象大学)
- Quantum Neural Network Compression
日本大学: 関与なし(対象大学)
- Qubit Mapping for Reconfigurable Atom Arrays
日本大学: 関与なし(対象大学)
- RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR/VR Rendering
日本大学: 関与なし(対象大学)
- Re <sup>2</sup> fresh: A Framework for Mitigating Read Disturbance in ReRAM-Based DNN Accelerators
日本大学: 関与なし(対象大学)
- Re-LSM: A ReRAM-Based Processing-in-Memory Framework for LSM-Based Key-Value Store
日本大学: 関与なし(対象大学)
- ReD-LUT: Reconfigurable In-DRAM LUTs Enabling Massive Parallel Computation
日本大学: 関与なし(対象大学)